🚀 BẮT ĐẦU HUẤN LUYỆN MÔ HÌNH SWIN-UNET (GPU & CACHE)
Initializing FeatureExtractor (mode=extended)...
📦 Đang load cache: training_data_507bd2ba4ec0d3fe107839cbf73a7a7d.joblib...
✅ Loaded 632 samples từ cache!
   ⚡ Đã bỏ qua download위성 data (tiết kiệm thời gian)
[CACHE HIT] Using cached dataset with 632 samples
Training SWIN-UNET model...
Building Swin-UNet model on cuda...
[SWIN-UNET] Class distribution: [ 48  89   3  86  74  38 117  50]
[SWIN-UNET] Class weights: [0.37418982 0.20181024 5.98703525 0.20885013 0.24271772 0.47266082
 0.15351377 0.35922223]
Training Swin-UNet model with PyTorch (with class weights)...
Swin-UNet Epoch 5/40, Train Loss: 1.4096, Val Loss: 1.2804, Val Acc: 48.03%, LR: 0.000293
[SWIN-UNET] Epoch 5/40 - Train Loss: 1.4096, Val Loss: 1.2804, Val Acc: 48.03%
Swin-UNet Epoch 10/40, Train Loss: 1.1129, Val Loss: 1.2746, Val Acc: 57.48%, LR: 0.000271
[SWIN-UNET] Epoch 10/40 - Train Loss: 1.1129, Val Loss: 1.2746, Val Acc: 57.48%
Swin-UNet Epoch 15/40, Train Loss: 1.0479, Val Loss: 1.3126, Val Acc: 50.39%, LR: 0.000238
[SWIN-UNET] Epoch 15/40 - Train Loss: 1.0479, Val Loss: 1.3126, Val Acc: 50.39%
Swin-UNet Epoch 20/40, Train Loss: 0.9548, Val Loss: 1.1118, Val Acc: 52.76%, LR: 0.000196
[SWIN-UNET] Epoch 20/40 - Train Loss: 0.9548, Val Loss: 1.1118, Val Acc: 52.76%
[SWIN-UNET] Early stopping at epoch 22 (best val loss: 1.1096)
Swin-UNet early stopped at epoch 22
Evaluating model...
Generating classification report...
Saving model...
[MODEL MANAGER] Saving model to: model_train/model_swin-unet_auto.joblib
[MODEL MANAGER] Saving metadata to: model_train/model_swin-unet_auto_info.json
[MODEL MANAGER] Model saved successfully!
Training complete!
✅ Hoàn thành! Accuracy: 0.5354