Clipping outputs

Fluency_Score.py

@@ -42,7 +42,6 @@ class Fluency_Score(evaluate.Measurement):
         
         with torch.no_grad():
             output = self.model(**inputs)
-            prediction = torch.softmax(output.logits / temperature, dim=-1)
-            classical_prob = prediction[:, 1].detach().cpu().numpy()
+            prediction = output.logits.clip(0, 1)
 
-        return {"classical_score": classical_prob}
+        return {"classical_score": prediction}