Update README.md

README.md

@@ -11,8 +11,27 @@ tags:
 - sentence-transformers
 ---
 
-base model : Omartificial-Intelligence-Space/GATE-AraBert-v1
- Arabic-mmarco-triplet
+# GATE-Reranker-V1 🚀✨
+
+**NAMAA-space** releases **GATE-Reranker-V1**, a high-performance model fine-tuned to elevate Arabic document retrieval and ranking to new heights! 📚🇸🇦
+
+This model is designed to **improve search relevance** of **arabic** documents by accurately ranking documents based on their contextual fit for a given query.
+
+## Key Features 🔑
+- **Optimized for Arabic**: Built with rich Arabic data, this model understands both Modern Standard Arabic (MSA) and diverse dialects, making it highly effective across various Arabic-speaking regions.
+- **Advanced Document Ranking**: Ranks results with precision, perfect for search engines, recommendation systems, and question-answering applications.
+- **State-of-the-Art Performance**: Achieves exceptional benchmarks on Arabic datasets ((See [Evaluation](https://huggingface.co/omarelshehy/Arabic-STS-Matryoshka#evaluation))), ensuring reliable relevance and precision.
+
+Whether you’re looking to enhance Arabic search results, improve information retrieval, or develop an intelligent Arabic chatbot, the NAMAA Space Reranker is here to support your journey! 🌐✨
+
+## Example Use Cases 💼
+- **Search Engine Ranking**: Improve search result relevance for Arabic content.
+- **Content Recommendation**: Deliver top-tier Arabic content suggestions.
+- **Question Answering**: Boost answer retrieval quality in Arabic-focused systems.
+
+## Get Started 🚀
+Load and test the NAMAA Space Reranker today and bring accurate, context-aware Arabic ranking to your project!
+
 
 ## Usage 
 
@@ -29,3 +48,5 @@ Paragraph2 = 'الذكاء الاصطناعي يستخدم في تحسين ال
 
 scores = model.predict([(Query, Paragraph1), (Query, Paragraph2)])
 ```
+
+## Evaluation