Improve input warning for evaluation metrics
Hi, 

I am the author of `bert_score`. Recently, we received [ an issue ](https://github.com/Tiiiger/bert_score/issues/62) reporting a problem in using `bert_score` from the `nlp` package (also see #238 in this repo).  After looking into this, I realized that the problem arises from the format `nlp.Metric` takes input. 

Here is a minimal example:
```python
import nlp

scorer = nlp.load_metric("bertscore")
with open("pred.txt") as p, open("ref.txt") as g:
    for lp, lg in zip(p, g):
        scorer.add(lp, lg)
score = scorer.compute(lang="en")
```

The problem in the above code is that `scorer.add()` expects a list of strings as input for the references. As a result, the `scorer` here would take a list of characters in `lg` to be the references. The correct implementation would be calling
```python
scorer.add(lp, [lg])
```

I just want to raise this issue to you to prevent future user errors of a similar kind. I assume some simple type checking can prevent this from happening?

Thanks!