Script for squad_v2 for custom data not working
**Environment info**
transformers version: 4.3.3
Platform: Linux-4.15.0-91-generic-x86_64-with-debian-buster-sid
Python version: 3.7.6
Using GPU in script?: True
Using distributed or parallel set-up in script?: True

**Who can help**
@gowtham1997 @patil-suraj 

I am running the script from docs to train and evaluate squad_v2 data with custom arguments.
My dataset is as per the structure of squad format with every keys and values properly.
[colabJson2.zip](https://github.com/huggingface/transformers/files/6063805/colabJson2.zip)


```
python run_qa.py \
  --model_name_or_path bert-base-uncased \
  --version_2_with_negative\
  --train_file=/content/colabJson.json \
  --validation_file=/content/dev-v2.0.json \
  --do_train \
  --do_eval \
  --per_device_train_batch_size 12 \
  --learning_rate 3e-5 \
  --num_train_epochs 2 \
  --max_seq_length 384 \
  --doc_stride 128 \
  --output_dir /content/debug_squad_16
```

Output of the script i am getting error as 

```
Traceback (most recent call last):
  File "run_qa.py", line 507, in <module>
    main()
  File "run_qa.py", line 230, in main
    datasets = load_dataset(extension, data_files=data_files, field="data")
  File "/usr/local/lib/python3.7/dist-packages/datasets/load.py", line 750, in load_dataset
    ds = builder_instance.as_dataset(split=split, ignore_verifications=ignore_verifications, in_memory=keep_in_memory)
  File "/usr/local/lib/python3.7/dist-packages/datasets/builder.py", line 740, in as_dataset
    map_tuple=True,
  File "/usr/local/lib/python3.7/dist-packages/datasets/utils/py_utils.py", line 234, in map_nested
    _single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
  File "/usr/local/lib/python3.7/dist-packages/datasets/utils/py_utils.py", line 234, in <listcomp>
    _single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
  File "/usr/local/lib/python3.7/dist-packages/datasets/utils/py_utils.py", line 172, in _single_map_nested
    return function(data_struct)
  File "/usr/local/lib/python3.7/dist-packages/datasets/builder.py", line 757, in _build_single_dataset
    in_memory=in_memory,
  File "/usr/local/lib/python3.7/dist-packages/datasets/builder.py", line 831, in _as_dataset
    return Dataset(**dataset_kwargs)
  File "/usr/local/lib/python3.7/dist-packages/datasets/arrow_dataset.py", line 250, in __init__
    self.info.features, self.info.features.type, inferred_features, inferred_features.type
ValueError: External features info don't match the dataset:
Got
{'title': Value(dtype='string', id=None), 'paragraphs': [{'qas': [{'question': Value(dtype='string', id=None), 'id': Value(dtype='string', id=None), 'answers': [{'text': Value(dtype='string', id=None), 'answer_start': Value(dtype='int64', id=None)}], 'is_impossible': Value(dtype='bool', id=None), 'plausible_answers': [{'text': Value(dtype='string', id=None), 'answer_start': Value(dtype='int64', id=None)}]}], 'context': Value(dtype='string', id=None)}]}
with type
struct<paragraphs: list<item: struct<context: string, qas: list<item: struct<answers: list<item: struct<answer_start: int64, text: string>>, id: string, is_impossible: bool, plausible_answers: list<item: struct<answer_start: int64, text: string>>, question: string>>>>, title: string>

but expected something like
{'title': Value(dtype='string', id=None), 'paragraphs': [{'context': Value(dtype='string', id=None), 'qas': [{'answers': [{'text': Value(dtype='string', id=None), 'answer_start': Value(dtype='int64', id=None)}], 'question': Value(dtype='string', id=None), 'id': Value(dtype='string', id=None)}]}]}
with type
struct<paragraphs: list<item: struct<context: string, qas: list<item: struct<answers: list<item: struct<answer_start: int64, text: string>>, id: string, question: string>>>>, title: string>
```
In my dataset I don't have any field as **plausible_answers**, **is_impossible** ..
how to match it with expected format when it is already in that format
hi @BatMrE 

could you try the new `run_qa.py` example script and let us know if you still face the issue. You can find the new script here 
https://github.com/huggingface/transformers/tree/master/examples/question-answering<|||||>> hi @BatMrE
> 
> could you try the new `run_qa.py` example script and let us know if you still face the issue. You can find the new script here
> https://github.com/huggingface/transformers/tree/master/examples/question-answering

```
[INFO|tokenization_utils_base.py:1786] 2021-03-02 18:56:09,448 >> loading file https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt from cache at /root/.cache/huggingface/transformers/45c3f7a79a80e1cf0a489e5c62b43f173c15db47864303a55d623bb3c96f72a5.d789d64ebfe299b0e416afc4a169632f903f693095b4629a7ea271d5a0cf2c99
[INFO|tokenization_utils_base.py:1786] 2021-03-02 18:56:09,448 >> loading file https://huggingface.co/bert-base-uncased/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/534479488c54aeaf9c3406f647aa2ec13648c06771ffe269edabebd4c412da1d.7f2721073f19841be16f41b0a70b600ca6b880c8f3df6f3535cbc704371bdfa4
[INFO|modeling_utils.py:1027] 2021-03-02 18:56:09,548 >> loading weights file https://huggingface.co/bert-base-uncased/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/a8041bf617d7f94ea26d15e218abd04afc2004805632abc0ed2066aa16d50d04.faf6ea826ae9c5867d12b22257f9877e6b8367890837bd60f7c54a29633f7f2f
[WARNING|modeling_utils.py:1135] 2021-03-02 18:56:14,139 >> Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertForQuestionAnswering: ['cls.predictions.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.decoder.weight', 'cls.seq_relationship.weight', 'cls.seq_relationship.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.LayerNorm.bias']
- This IS expected if you are initializing BertForQuestionAnswering from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing BertForQuestionAnswering from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
[WARNING|modeling_utils.py:1146] 2021-03-02 18:56:14,139 >> Some weights of BertForQuestionAnswering were not initialized from the model checkpoint at bert-base-uncased and are newly initialized: ['qa_outputs.weight', 'qa_outputs.bias']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
  1% 3/227 [00:01<02:25,  1.54ba/s]thread '<unnamed>' panicked at 'assertion failed: stride < max_len', /__w/tokenizers/tokenizers/tokenizers/src/tokenizer/encoding.rs:322:9
note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace
```<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.