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README.md

@@ -1,5 +1,5 @@
 # Training Logs - EfficientNet-B3
-## Experiment: 20251110_181006
+## Experiment: 20251111_031138
 
 ### Model Architecture
 - **Base Model**: EfficientNet-B3 (pretrained on ImageNet)
@@ -11,28 +11,28 @@
 - **Learning Rate**: 0.0002
 - **Optimizer**: AdamW (weight_decay=1e-4)
 - **Scheduler**: CosineAnnealingWarmRestarts
-- **Epochs Trained**: 12 / 40
+- **Epochs Trained**: 34 / 40
 
 ### Best Results
-- **Validation Harmonic Mean**: 0.9683
-- **Validation Age RMSE**: 0.1185 years
-- **Validation Gender F1**: 0.9439
-- **Best Epoch**: 8
+- **Validation Harmonic Mean**: 0.9699
+- **Validation Age RMSE**: 0.1175 years
+- **Validation Gender F1**: 0.9469
+- **Best Epoch**: 12
 
 ### Final Metrics (Last Epoch)
-- **Val Loss**: 0.2825
-- **Val Harmonic Mean**: 0.9680
-- **Val Age RMSE**: 0.1185
-- **Val Age MAE**: 0.0850
-- **Val Gender F1**: 0.9432
+- **Val Loss**: 0.2847
+- **Val Harmonic Mean**: 0.9650
+- **Val Age RMSE**: 0.1177
+- **Val Age MAE**: 0.0875
+- **Val Gender F1**: 0.9375
 
 ### Files in this Dataset
-- `pytorch_lightning/metrics_20251110_181006.csv` - Complete training history
-- `summaries/training_summary_20251110_181006.json` - Detailed metrics and config
-- `trackio/trackio_logs_20251110_181006.zip` - TrackIO logs (if available)
+- `pytorch_lightning/metrics_20251111_031138.csv` - Complete training history
+- `summaries/training_summary_20251111_031138.json` - Detailed metrics and config
+- `trackio/trackio_logs_20251111_031138.zip` - TrackIO logs (if available)
 
 ### Next Steps
 Use the best checkpoint for inference:
 ```python
-checkpoint_path = "checkpoints/efficientnet/effnet-epoch=08-val_harmonic_mean=0.9683.ckpt"
+checkpoint_path = "checkpoints/efficientnet/effnet-epoch=12-val_harmonic_mean=0.9699.ckpt"
 ```