dataset adversarial_qa has no answers in the "test" set
Makes sense, but not intuitive for someone searching through the datasets.  Thanks for adding the note to clarify.
## Describe the bug
When loading the adversarial_qa dataset the 'test' portion has no answers.  Only the 'train' and 'validation' portions do.  This occurs with all four of the configs ('adversarialQA', 'dbidaf', 'dbert', 'droberta')

## Steps to reproduce the bug
```
from   datasets import load_dataset
examples = load_dataset('adversarial_qa', 'adversarialQA', script_version="master")['test']
print('Loaded {:,} examples'.format(len(examples)))
has_answers = 0
for e in examples:
    if e['answers']['text']:
        has_answers += 1
print('{:,} have answers'.format(has_answers))
>>> Loaded 3,000 examples
>>> 0 have answers

examples = load_dataset('adversarial_qa', 'adversarialQA', script_version="master")['validation']
<...code above...>
>>> Loaded 3,000 examples
>>> 3,000 have answers
```

## Expected results
If 'test' is a valid dataset, it should have answers. Also note that all of the 'train' and 'validation' sets have answers, there are no "no answer" questions with this set (not sure if this is correct or not).

## Environment info
- `datasets` version: 1.7.0
- Platform: Linux-5.8.0-53-generic-x86_64-with-glibc2.29
- Python version: 3.8.5
- PyArrow version: 1.0.0


dataset adversarial_qa has no answers in the "test" set 
 ## Describe the bug
When loading the adversarial_qa dataset the 'test' portion has no answers.  Only the 'train' and 'validation' portions do.  This occurs with all four of the configs ('adversarialQA', 'dbidaf', 'dbert', 'droberta')

## Steps to reproduce the bug
```
from   datasets import load_dataset
examples = load_dataset('adversarial_qa', 'adversarialQA', script_version="master")['test']
print('Loaded {:,} examples'.format(len(examples)))
has_answers = 0
for e in examples:
    if e['answers']['text']:
        has_answers += 1
print('{:,} have answers'.format(has_answers))
>>> Loaded 3,000 examples
>>> 0 have answers

examples = load_dataset('adversarial_qa', 'adversarialQA', script_version="master")['validation']
<...code above...>
>>> Loaded 3,000 examples
>>> 3,000 have answers
```

## Expected results
If 'test' is a valid dataset, it should have answers. Also note that all of the 'train' and 'validation' sets have answers, there are no "no answer" questions with this set (not sure if this is correct or not).

## Environment info
- `datasets` version: 1.7.0
- Platform: Linux-5.8.0-53-generic-x86_64-with-glibc2.29
- Python version: 3.8.5
- PyArrow version: 1.0.0

 
 Makes sense, but not intuitive for someone searching through the datasets.  Thanks for adding the note to clarify.