Update README.md

README.md

@@ -26,15 +26,25 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-    More information needed
+    This model leverages the Vision Transformer (ViT) architecture to classify retinal images for early detection of Diabetic Retinopathy (DR). The fine-tuned model improves accuracy and generalization on medical imaging datasets.
+
 
 ## Intended uses & limitations
 
-More information needed
+### Intended Uses:
+- Medical diagnosis support for Diabetic Retinopathy  
+- Research applications in ophthalmology and AI-based healthcare  
+
+### Limitations:
+- Requires high-quality retinal images for accurate predictions  
+- Not a substitute for professional medical advice; should be used as an assistive tool  
+
 
 ## Training and evaluation data
 
-More information needed
+    The model was trained on a curated dataset containing labeled retinal images. The dataset includes various severity levels of Diabetic Retinopathy, ensuring robustness in classification.
+
+
 
 ## Training procedure