Weights of model checkpoint not initialized for RobertaModel for Bertscore
When applying bertscore out of the box, 

```Some weights of the model checkpoint at roberta-large were not used when initializing RobertaModel: ['lm_head.decoder.weight', 'lm_head.bias', 'lm_head.dense.bias', 'lm_head.layer_norm.bias', 'lm_head.dense.weight', 'lm_head.layer_norm.weight']```

Following the typical usage from https://huggingface.co/docs/datasets/loading_metrics.html

```
from datasets import load_metric
metric = load_metric('bertscore')

# Example of typical usage
for batch in dataset:
    inputs, references = batch
    predictions = model(inputs)
    metric.add_batch(predictions=predictions, references=references)
score = metric.compute(lang="en")
#score = metric.compute(model_type="roberta-large") # gives the same error
```

I am concerned about this because my usage shouldn't require any further fine-tuning and most people would expect to use BertScore out of the box? I realised the huggingface code is a wrapper around https://github.com/Tiiiger/bert_score, but I think this repo is anyway relying on the model code and weights from huggingface repo.... 

## Environment info
- `datasets` version: 1.7.0
- Platform: Linux-5.4.0-1041-aws-x86_64-with-glibc2.27
- Python version:  3.9.5
- PyArrow version: 3.0.0
