tokenization progress made more sensible via tqdm
Because tokenization takes a relatively long time, having progress being visualized via tqdm would be nice.
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1944?src=pr&el=h1) Report
> Merging [#1944](https://codecov.io/gh/huggingface/transformers/pull/1944?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/5d3b8daad2cc6287d30f03f8a96d0a1f7bc8d0dc?src=pr&el=desc) will **increase** coverage by `<.01%`.
> The diff coverage is `100%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/1944/graphs/tree.svg?width=650&token=9qOlN6Hb1c&height=150&src=pr)](https://codecov.io/gh/huggingface/transformers/pull/1944?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #1944      +/-   ##
==========================================
+ Coverage      84%   84.01%   +<.01%     
==========================================
  Files          97       97              
  Lines       14340    14341       +1     
==========================================
+ Hits        12047    12048       +1     
  Misses       2293     2293
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1944?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [transformers/tokenization\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1944/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rva2VuaXphdGlvbl91dGlscy5weQ==) | `92.16% <100%> (+0.01%)` | :arrow_up: |

------

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> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1944?src=pr&el=footer). Last update [5d3b8da...36b211d](https://codecov.io/gh/huggingface/transformers/pull/1944?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
<|||||>Ok for me.
Ok for you @LysandreJik?<|||||>I feel this might output too much text when tokenizing a lot of small sequences (which is the case for practically every example). It would be useful when tokenizing large datasets though. Maybe test if the length is superior to, say, 10000 before? What do you think?<|||||>You might be right, I have never thought about that. But it's a stubborn fact that when the time comes to tokenize larger datasets. How could we test about length? It is not about the `tokenized_text` 's length.<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
