Feature Request: Support training and evaluating on Squad-format (json) files in SquadDataset for easy Squad fine-tuning
I am currently working on a project using [run_squad_trainer.py](https://github.com/huggingface/transformers/blob/master/examples/question-answering/run_squad_trainer.py)
to quickly fine-tune on new Squad-format (v2.0 json) files. However, the current SquadDataset class only allows training/evaluating on the original Squad jsons (train-v2.0.json, dev-v2.0.json). I have used a quick work around by using softlinks, to the actual training/evaluation files, but feel this is a little contrived.

I believe if the arguments `train_file` and `predict_file` are added in [SquadArguments](https://github.com/huggingface/transformers/blob/aa6c3c14b4ff8fbd5d40b100f4aae71fb359d6ae/src/transformers/data/datasets/squad.py#L36) and also line 152 in [SquadDataset](https://github.com/huggingface/transformers/blob/aa6c3c14b4ff8fbd5d40b100f4aae71fb359d6ae/src/transformers/data/datasets/squad.py#L152) is changed to 
                   
 `self.examples = self.processor.get_dev_examples(args.data_dir, filename=args.predict_file)`

and line 154 in [SquadDataset](https://github.com/huggingface/transformers/blob/aa6c3c14b4ff8fbd5d40b100f4aae71fb359d6ae/src/transformers/data/datasets/squad.py#L154)



`self.examples = self.processor.get_train_examples(args.data_dir, filename=arg.train_file)`

that may do the trick. At least this approach works in [run_squad.py](https://github.com/huggingface/transformers/blob/aa6c3c14b4ff8fbd5d40b100f4aae71fb359d6ae/examples/question-answering/run_squad.py#L444).

Thanks for your great work!

Sorry duplicated my request.