I have got the same error here:
def collate_batch(self, features: List[Union[InputDataClass, Dict]]) → Dict[str, torch.Tensor]:
    first = features[0]

    if isinstance(first, dict):

      # NLP data sets current works presents features as lists of dictionary

      # (one per example), so we  will adapt the collate_batch logic for that

      if "labels" in first and first["labels"] is not None:

          if first["labels"].dtype == torch.int64:

              labels = torch.tensor([f["labels"] for f in features], dtype=torch.long)

          else:

              labels = torch.tensor([f["labels"] for f in features], dtype=torch.float)

          batch = {"labels": labels}

      for k, v in first.items():

          if k != "labels" and v is not None and not isinstance(v, str):

             print([f[k] for f in features][0])

              batch[k] = torch.stack([f[k] for f in features])

      return batch

 29                   print([f[k] for f in features][0])

—> 30                   batch[k] = torch.stack([f[k] for f in features])
31           return batch
TypeError: expected Tensor as element 0 in argument 0, but got list