Update README.md

README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+language:
+- en
+base_model:
+- nasa-ibm-ai4science/Surya-1.0
+---
+# 🌌 Surya – Active Region Segmentation 
+
+## 📖 Model Overview
+This repository hosts **fine-tuned weights of Surya** – a heliophysics foundation model – for the task of **solar Active Region (AR) segmentation**.  
+Solar Active Regions are magnetically complex structures associated with **flares** and **coronal mass ejections (CMEs)**. Within ARs, the **Polarity Inversion Line (PIL)** serves as a critical precursor of eruptions. Accurate segmentation of ARs containing PILs is essential for **space weather forecasting** and understanding solar magnetic complexity.  
+
+---
+
+## 📊 Results
+We benchmarked Surya against a standard UNet baseline on the ARPIL dataset.
+
+| Model  | Params | IoU   | Dice Coeff |
+|--------|--------|-------|------------|
+| UNet   | 9.2 M  | 0.688 | 0.801      |
+| **Surya (LoRA)** | **4.1 M**  | **0.768** | **0.853**      |
+
+Surya achieves **higher segmentation quality with fewer parameters**, highlighting the benefits of foundation model pretraining and parameter-efficient adaptation.
+
+---
+
+## 🖼 Example
+<p align="center">
+  <img src="figure/ar_seg_results.png" width="100%">
+</p>
+
+- **Top Row**: Input SDO/HMI data (Date: 2014-02-01, Time: 08:12)  
+- **Middle Row**: Surya segmentation output  
+- **Bottom Row**: Ground Truth  
+
+---
+
+## ⚡ Usage
+
+Follow the instructions at [Surya/downstream_examples/ar_segmentation](https://github.com/NASA-IMPACT/Surya/tree/main/downstream_examples/ar_segmentation)
+
+---
+
+## 🤝 Acknowledgements
+- **NASA IMPACT** and **IBM** for developing the Surya foundation model