Model card updated

README.md

@@ -28,11 +28,11 @@ Details of the dataset and the fine-tuning process are available upon request.
 
 This model is intended for use in identifying biased in text. Users can input a piece of text and receive a prediction indicating whether the text is biased or unbiased. 
 
-### Class-wise Performance Metrics
+<!-- ### Class-wise Performance Metrics
 
 | Class | Prec | Recall | F1  |
 |-------|------|--------|-----|
-        | 0.75 | 0.59   | 0.53|
+        | 0.75 | 0.59   | 0.53| -->
 
 ## How to Use
 
@@ -120,15 +120,15 @@ Predicted label: biased (Biased Probability: 0.70, Unbiased Probability: 0.30)
 - **Transparency:** Be transparent about the model's limitations and the potential for false positives and false negatives.
 - **Accountability:** Users are responsible for the decisions made based on the model's predictions and should consider multiple sources of information when making important decisions.
 
-## References
+<!-- ## References
 @misc{pollcheck2024,
 author = {Emrul Hasan, Shaina Raza, Veronica Chatrath},
-title = {Your Model Name},
+title = {POLLCHECK/Pollcheck-llama3-news-classifier},
 year = {2024},
 publisher = {Hugging Face},
 journal = {Hugging Face Model Hub},
-howpublished = {\url{https://huggingface.co/your-username/your-model-name}}
-}
+howpublished = {\url{https://huggingface.co/emrulphy/POLLCHECK/Pollcheck-llama3-news-classifier}}
+} -->
 ## Contact Information
 
 For questions, comments, or suggestions, please contact Emrul Hasan at [email protected].