changed metric based on testing

ArtistCoherencyModel.py

@@ -83,19 +83,9 @@ class ArtistCoherencyModel(nn.Module, PyTorchModelHubMixin):
         self, artist_name: str, song_or_embedding: Union[str, torch.Tensor]
     ) -> float:
         coherent_index = self.ffnn.label2id[f"{artist_name}-coherent"]
-        incoherent_index = self.ffnn.label2id[f"{artist_name}-incoherent"]
         logits = self.generate_artist_coherency_logits(song_or_embedding)
         coherent_score = logits[coherent_index]
-        incoherent_score = logits[incoherent_index]
-        score = (
-            100
-            * coherent_score
-            * (coherent_score - incoherent_score)
-            / (coherent_score + incoherent_score)
-        )
-        print(f"coherent_score: {float(coherent_score)}")
-        print(f"incoherent_score: {float(incoherent_score)}")
-        return float(score)
+        return float(coherent_score)
 
     def predict(
         self, song_or_embedding: Union[str, torch.Tensor], return_ids: bool = False