Update README.md

README.md

@@ -11,7 +11,6 @@ library_name: transformers
 ---
 # DeBERTa v3 Emotion Classifier
 
-Repository: ragunath-ravi/deberta-v3-emotion-classifier
 
 ## Model description
 This repository contains a DeBERTa v3 base model fine-tuned for emotion classification on the `dair-ai/emotion` dataset. The model is intended for short-text emotion labeling and was finetuned with standard Trainer-based training on Google Colab / Drive.
@@ -35,7 +34,7 @@ This repository contains a DeBERTa v3 base model fine-tuned for emotion classifi
 | 1     | 0.241200       | 0.249670         | 0.925000 |
 | 2     | 0.127800       | 0.176021         | 0.937500 |
 
-## Model card / intended use
+## intended use
 This model is intended to support emotion classification tasks. It may produce incorrect or biased outputs when used on out-of-distribution text, long-form inputs, or languages it was not trained on. Use a confidence-based fallback for important decisions and include human review for high-stakes applications.
 
 ## How to load
@@ -64,6 +63,7 @@ probs = F.softmax(logits, dim=-1).cpu().numpy()[0]
 print(probs)
 ```
 
-## Credits & contact
-Model fine-tuned by Ragunath R. Training logs available at the provided wandb link above.
-
+## Acknowledgements
+- This model is based on Microsoft DeBERTa v3 base.
+- Dataset: `dair-ai/emotion`.
+- Transformers library: Hugging Face `transformers`.