Question Answering for TF trainer (#4320)

* Add QA trainer example for TF

* Make data_dir optional

* Fix parameter logic

* Fix feature convert

* Update the READMEs to add the question-answering task

* Apply style

* Change 'sequence-classification' to 'text-classification' and prefix with 'eval' all the metric names

* Apply style

* Apply style

examples/README.md

@@ -20,6 +20,7 @@ This is still a work-in-progress – in particular documentation is still sparse
 | [`text-classification`](./text-classification) | GLUE, XNLI | ✅ | ✅ | ✅ | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/trainer/01_text_classification.ipynb) | [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fazure-quickstart-templates%2Fmaster%2F101-storage-account-create%2Fazuredeploy.json) |
 | [`token-classification`](./token-classification) | CoNLL NER | ✅ | ✅ | ✅ | - | - |
 | [`multiple-choice`](./multiple-choice) | SWAG, RACE, ARC | ✅ | ✅ | - | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ViktorAlm/notebooks/blob/master/MPC_GPU_Demo_for_TF_and_PT.ipynb) | - |
+| [`question-answering`](./question-answering) | SQuAD | - | ✅ | - | - | - |