Update README.md

README.md

@@ -6,10 +6,10 @@ datasets:
 language:
 - en
 metrics:
-- spearmanr
-- pearsonr
+- accuracy
 base_model:
 - answerdotai/ModernBERT-base
+- tasksource/ModernBERT-base-nli
 pipeline_tag: text-classification
 library_name: sentence-transformers
 tags:
@@ -20,7 +20,8 @@ tags:
 ---
 # ModernBERT Cross-Encoder: Natural Language Inference (NLI)
 
-This cross encoder performs sequence classification for contradiction/neutral/entailment labels.
+This cross encoder performs sequence classification for contradiction/neutral/entailment labels. This is
+a drop-in for the comparable sentence transformers cross encoders.
 
 I trained this model by initializaing the ModernBERT-base weights from the brilliant `tasksource/ModernBERT-base-nli` 
 zero-shot classification model. Then I trained it with a batch size of 64 using the `sentence-transformers` AllNLI
@@ -64,6 +65,7 @@ scores = model.predict([
 # Convert scores to labels
 label_mapping = ['contradiction', 'entailment', 'neutral']
 labels = [label_mapping[score_max] for score_max in scores.argmax(axis=1)]
+# ['entailment', 'contradiction']
 ```
 
 ---
@@ -120,4 +122,4 @@ If you use this model in your research, please cite:
 
 ## License
 
-This model is licensed under the [MIT License](LICENSE).
+This model is licensed under the [MIT License](LICENSE).