Update README.md

README.md

@@ -20,12 +20,11 @@ metrics:
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   <img src="https://img.shields.io/badge/License-Apache%202.0-green.svg?style=for-the-badge&logo=apache" alt="License"/>
   <img src="https://img.shields.io/badge/Language-English-blue?style=for-the-badge&logo=googletranslate&logoColor=white" alt="Language"/>
-  <img src="https://img.shields.io/badge/F1%20Score-0.981-brightgreen?style=for-the-badge&logo=checkmarx&logoColor=white" alt="F1 Score"/>
   <img src="https://img.shields.io/badge/Task-Text%20Classification-orange?style=for-the-badge&logo=openai&logoColor=white" alt="Task"/>
   <img src="https://img.shields.io/badge/Domain-ESG%20%7C%20Climate%20Finance-teal?style=for-the-badge&logo=leaflet&logoColor=white" alt="Domain"/>
 </p>
 
-*A fine-tuned NLP model for classifying climate-related shareholder proposals with high precision.*
+*A fine-tuned BERT-based language model for classifying environmental and climate-related shareholder proposals with high precision.*
 
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@@ -139,27 +138,11 @@ The model weights from **Epoch 8 (`checkpoint-600`)** were selected as the best
 
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-## ⚠️ Limitations and Bias
-
-While the model achieves high accuracy on the validation set, several limitations should be noted:
-
-- 🔗 **Domain dependency** — Performance is tightly coupled with the specific linguistic patterns and taxonomy of the ISS database *(e.g., SIC-2 sector descriptions, ISS agenda codes)*
-- 📰 **Unstructured text** — Lower confidence or accuracy is expected when processing unstructured news articles or raw corporate filings
-- 🌍 **Jurisdictional scope** — The model may not generalize well to proposals from jurisdictions outside the US/global norm represented in the training set
-
----
 
 ## 📚 Citation
 
 If you use this model in your research, please cite the associated working paper:
 
-```bibtex
-@misc{gprop_classifier,
-  title  = {Green Shareholder Proposal Classifier},
-  note   = {Citation details forthcoming},
-}
-```
-
 ---
 
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