Update README.md

README.md

@@ -28,13 +28,13 @@ model-index:
       type: fer2013
     metrics:
     - type: mae
-      value: XX.XX  # Update with actual value
+      value: 22.66
       name: Mean Absolute Error
     - type: rmse
-      value: XX.XX  # Update with actual value
+      value: 27.29
       name: Root Mean Squared Error
     - type: accuracy
-      value: XX.XX  # Update with actual value
+      value: 77.3
       name: Approximate Accuracy
 pipeline_tag: image-feature-extraction
 ---
@@ -103,12 +103,15 @@ fear     → 90  (Extreme stress)
 
 ## Performance Metrics
 
-- **Mean Absolute Error (MAE):** ~XX.XX stress points (update with your actual results)
-- **Root Mean Squared Error (RMSE):** ~XX.XX (update with your actual results)
-- **Approximate Accuracy:** ~XX% (update with your actual results)
-- **Target Performance:** 60-70% accuracy for MVP deployment
+- **Mean Absolute Error (MAE):** 22.66 stress points
+- **Root Mean Squared Error (RMSE):** 27.29
+- **Approximate Accuracy:** 77.3%
+- **Target Performance:** 60-70% accuracy for MVP deployment ✅ **Achieved!**
 
-*Note: Update the metrics above based on your actual training results from the evaluation cell.*
+**Training Set Performance:**
+- Training MAE: 6.15 stress points
+- Training RMSE: 8.12
+- Training Accuracy: 93.9%
 
 ## Intended Use