CER function does not work properly, even when one tries to execute the example in help. Code is below
from datasets import load_metric
cer = load_metric("cer")
predictions = ["this is the prediction", "there is an other sample"]
references = ["this is the reference", "there is another one"]

cer_score = cer.compute(predictions=predictions, references=references)
print(cer_score)

outputs
ValueError                                Traceback (most recent call last)
/tmp/ipykernel_5923/623465361.py in <module>
      4 references = ["this is the reference", "there is another one"]
      5 
----> 6 cer_score = cer.compute(predictions=predictions, references=references)
      7 print(cer_score)

/opt/conda/lib/python3.7/site-packages/datasets/metric.py in compute(self, predictions, references, **kwargs)
    402             references = self.data["references"]
    403             with temp_seed(self.seed):
--> 404                 output = self._compute(predictions=predictions, references=references, **kwargs)
    405 
    406             if self.buf_writer is not None:

~/.cache/huggingface/modules/datasets_modules/metrics/cer/4e547cc82fc2e597c84fe25f48ed77e3a9acfd354308fe654ccbc6ea9473a61a/cer.py in _compute(self, predictions, references, concatenate_texts)
    132                 prediction,
    133                 truth_transform=cer_transform,
--> 134                 hypothesis_transform=cer_transform,
    135             )
    136             incorrect += measures["substitutions"] + measures["deletions"] + measures["insertions"]

/opt/conda/lib/python3.7/site-packages/jiwer/measures.py in compute_measures(truth, hypothesis, truth_transform, hypothesis_transform, **kwargs)
    208     # Preprocess truth and hypothesis
    209     truth, hypothesis = _preprocess(
--> 210         truth, hypothesis, truth_transform, hypothesis_transform
    211     )
    212 

/opt/conda/lib/python3.7/site-packages/jiwer/measures.py in _preprocess(truth, hypothesis, truth_transform, hypothesis_transform)
    327         raise ValueError(
    328             "number of ground truth inputs ({}) and hypothesis inputs ({}) must match.".format(
--> 329                 len(transformed_truth), len(transformed_hypothesis)
    330             )
    331         )

ValueError: number of ground truth inputs (21) and hypothesis inputs (22) must match.