Update negbleurt.py

negbleurt.py

@@ -24,7 +24,7 @@ Examples:
     >>> negBLEURT = evaluate.load('MiriUll/negbleurt')
     >>> predictions = ["Ray Charles is a legend.", "Ray Charles isn’t legendary."]
     >>> reference = "Ray Charles is legendary."
-    >>> results = rouge.compute(predictions=predictions, references=reference)
+    >>> results = negBLEURT.compute(predictions=predictions, references=reference)
     >>> print(results)
     {'negBLERUT': [0.8409, 0.2601]}
 """
@@ -63,10 +63,11 @@ class NegBLEURT(evaluate.Metric):
     ):
         single_ref = isinstance(references, str)
         if single_ref:
+            print("single reference")
             references = [references] * len(predictions)
 
         scores_negbleurt = []
-        for i in tqdm(range(0, len(references), batch_size)):
+        for i in range(0, len(references), batch_size):
             tokenized = self.tokenizer(references[i:i+batch_size], candidates[i:i+batch_size], return_tensors='pt', padding=True, max_length=512, truncation=True)
             scores_negbleurt += self.model(**tokenized).logits.flatten().tolist()
         return {'negBLEURT': scores_negbleurt}