NER support for Albert in run_ner.py and NerPipeline
Author: marma
Pull request: yes

I have added a class, AlbertForTokenClassification, based on BertForTokenClassification and added it to lists used for checking NER capabilities in run_ner.py and NerPipeline.

I tested NER fine-tuning on albert-base-v2, albert-large-v2 and albert-xlarge-v2 on the english CONLL 2003 dataset and they all get F1 of around 0.93-0.94, so it seems to be working. The fine-tuned models are published [here](https://huggingface.co/KB).

I've also added some command-line options to better control tokenization since different tokenizers have different possible arguments and defaults. I guess that in the end, when all tokenizers behave the same, these options will be unnecessary.

I changed how NerPipeline outputs tokens, from .decode(..) to .convert_ids_to_tokens(...) since it removes '_' at the beginning of tokens making it impossible (for sentencepiece tokens) to know which tokens form a word. Using .convert(...) would make sense if it were  outputting whole words and not words split into tokens. It might make sense to change this so that NerPipeline outputs whole words. That would assume that all the tokens in a word gets classified with the same label, which is not always the case.

I had one weird thing happening: when fine-tuning albert-large-v2 specifically for 3 or 4 epochs F1 would be reported as exactly 0. When setting num_train_epochs to 2 or 5 this did not happen. I'm going to assume that this has nothing to do with the code submitted :)

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2983?src=pr&el=h1) Report
> Merging [#2983](https://codecov.io/gh/huggingface/transformers/pull/2983?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/129f0604acb9e8b9cebd2897437324198fa37a0a?src=pr&el=desc) will **decrease** coverage by `0.11%`.
> The diff coverage is `19.23%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/2983/graphs/tree.svg?width=650&token=9qOlN6Hb1c&height=150&src=pr)](https://codecov.io/gh/huggingface/transformers/pull/2983?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #2983      +/-   ##
==========================================
- Coverage   77.17%   77.05%   -0.12%     
==========================================
  Files          98       98              
  Lines       15997    16023      +26     
==========================================
+ Hits        12345    12347       +2     
- Misses       3652     3676      +24
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/2983?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/\_\_init\_\_.py](https://codecov.io/gh/huggingface/transformers/pull/2983/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9fX2luaXRfXy5weQ==) | `98.91% <ø> (ø)` | :arrow_up: |
| [src/transformers/modeling\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/2983/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `75.47% <ø> (ø)` | :arrow_up: |
| [src/transformers/pipelines.py](https://codecov.io/gh/huggingface/transformers/pull/2983/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9waXBlbGluZXMucHk=) | `70.88% <ø> (ø)` | :arrow_up: |
| [src/transformers/modeling\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/2983/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hbGJlcnQucHk=) | `75.25% <19.23%> (-3.9%)` | :arrow_down: |
| [src/transformers/tokenization\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/2983/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `90.05% <0%> (-0.44%)` | :arrow_down: |

------

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> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2983?src=pr&el=footer). Last update [129f060...f711575](https://codecov.io/gh/huggingface/transformers/pull/2983?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).