Update README.md

README.md

@@ -1,13 +1,52 @@
 ---
-title: LexCAT Sentiment-Analysis
-emoji: 💻
-colorFrom: purple
-colorTo: gray
+title: 'LexCAT: Taglish Sentiment Analysis'
+colorFrom: blue
+colorTo: purple
 sdk: gradio
-sdk_version: 5.47.0
 app_file: app.py
-pinned: false
+pinned: true
 license: cc-by-4.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# LexCAT: Lexicon-Enhanced Sentiment Analysis for Tagalog–English Code-Switched Text
+
+**Author**: Glenn Marcus D. Cinco  
+**Institution**: Mapúa University  
+**Thesis**: *LexCAT: A Lexicon-Based Approach for Code-Switching Analysis with Transformers Using XLM-RoBERTa and LexiLiksik*  
+**Model**: Fine-tuned XLM-RoBERTa + LexiLiksik lexicon  
+**Dataset**: FiReCS (10,487 Taglish reviews)  
+**Accuracy**: 84.31%  
+**Specialty**: Detects intra-sentential sentiment shifts (e.g., “Maganda pero expensive” → Negative)
+
+---
+
+## 🧠 Try It Out
+
+Enter any Taglish sentence — LexCAT will predict its sentiment and show confidence scores.
+
+Examples:
+- *“sobrang lambot ng burger pero expensive tlga”* → ❌ Negative
+- *“Salamat sa nyo nagana nmn po sya kaya super thank you ako”* → ✅ Positive
+- *“Ang ganda ng service, one star!”* → ❌ Negative
+
+---
+
+## 📚 Model Card
+
+See full documentation, methodology, and citation at:  
+👉 https://huggingface.co/your-hf-username/LexCAT-LexiLiksik-Final
+
+---
+
+## 🎓 Academic Use
+
+Cite this model in your research:
+
+```bibtex
+@mastersthesis{cinco2025lexcat,
+  author = {Cinco, Glenn Marcus D.},
+  title = {LexCAT: A Lexicon-Based Approach for Code-Switching Analysis with Transformers Using XLM-RoBERTa and LexiLiksik},
+  school = {Mapúa University},
+  year = {2025}
+}
+```