./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img
./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img

📌 S Retain class distribution for seed 3:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 3:
Class 0: 527
Class 1: 527

📊 Updated class distribution:
Retain set:
  Class 0: 5679
  Class 1: 4605
Forget set:
  Class 0: 132
  Class 1: 132
./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img
./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img
⚠️ Warning: Retain train loader may not be shuffled.
Training Epoch: 1 [256/10284]	Loss: 0.7170	LR: 0.000000
Training Epoch: 1 [512/10284]	Loss: 0.7053	LR: 0.002439
Training Epoch: 1 [768/10284]	Loss: 0.6960	LR: 0.004878
Training Epoch: 1 [1024/10284]	Loss: 0.7475	LR: 0.007317
Training Epoch: 1 [1280/10284]	Loss: 0.7425	LR: 0.009756
Training Epoch: 1 [1536/10284]	Loss: 0.7037	LR: 0.012195
Training Epoch: 1 [1792/10284]	Loss: 0.8143	LR: 0.014634
Training Epoch: 1 [2048/10284]	Loss: 0.8459	LR: 0.017073
Training Epoch: 1 [2304/10284]	Loss: 0.6534	LR: 0.019512
Training Epoch: 1 [2560/10284]	Loss: 0.8490	LR: 0.021951
Training Epoch: 1 [2816/10284]	Loss: 0.7452	LR: 0.024390
Training Epoch: 1 [3072/10284]	Loss: 0.6651	LR: 0.026829
Training Epoch: 1 [3328/10284]	Loss: 0.8098	LR: 0.029268
Training Epoch: 1 [3584/10284]	Loss: 1.2302	LR: 0.031707
Training Epoch: 1 [3840/10284]	Loss: 1.7168	LR: 0.034146
Training Epoch: 1 [4096/10284]	Loss: 0.9993	LR: 0.036585
Training Epoch: 1 [4352/10284]	Loss: 0.7134	LR: 0.039024
Training Epoch: 1 [4608/10284]	Loss: 0.8765	LR: 0.041463
Training Epoch: 1 [4864/10284]	Loss: 1.8247	LR: 0.043902
Training Epoch: 1 [5120/10284]	Loss: 1.2272	LR: 0.046341
Training Epoch: 1 [5376/10284]	Loss: 0.7252	LR: 0.048780
Training Epoch: 1 [5632/10284]	Loss: 0.7306	LR: 0.051220
Training Epoch: 1 [5888/10284]	Loss: 0.7356	LR: 0.053659
Training Epoch: 1 [6144/10284]	Loss: 0.7452	LR: 0.056098
Training Epoch: 1 [6400/10284]	Loss: 0.7100	LR: 0.058537
Training Epoch: 1 [6656/10284]	Loss: 0.6894	LR: 0.060976
Training Epoch: 1 [6912/10284]	Loss: 0.7629	LR: 0.063415
Training Epoch: 1 [7168/10284]	Loss: 0.6876	LR: 0.065854
Training Epoch: 1 [7424/10284]	Loss: 0.6993	LR: 0.068293
Training Epoch: 1 [7680/10284]	Loss: 0.6979	LR: 0.070732
Training Epoch: 1 [7936/10284]	Loss: 0.7585	LR: 0.073171
Training Epoch: 1 [8192/10284]	Loss: 0.6794	LR: 0.075610
Training Epoch: 1 [8448/10284]	Loss: 0.6870	LR: 0.078049
Training Epoch: 1 [8704/10284]	Loss: 0.7062	LR: 0.080488
Training Epoch: 1 [8960/10284]	Loss: 0.7028	LR: 0.082927
Training Epoch: 1 [9216/10284]	Loss: 0.6492	LR: 0.085366
Training Epoch: 1 [9472/10284]	Loss: 0.7212	LR: 0.087805
Training Epoch: 1 [9728/10284]	Loss: 0.7074	LR: 0.090244
Training Epoch: 1 [9984/10284]	Loss: 0.7150	LR: 0.092683
Training Epoch: 1 [10240/10284]	Loss: 0.7068	LR: 0.095122
Training Epoch: 1 [10284/10284]	Loss: 0.6997	LR: 0.097561
Epoch 1 - Average Train Loss: 0.8120, Train Accuracy: 0.5293
Epoch 1 training time consumed: 340.31s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0051, Accuracy: 0.5230, Time consumed:8.03s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-1-best.pth
Training Epoch: 2 [256/10284]	Loss: 0.6962	LR: 0.100000
Training Epoch: 2 [512/10284]	Loss: 0.7664	LR: 0.100000
Training Epoch: 2 [768/10284]	Loss: 0.7467	LR: 0.100000
Training Epoch: 2 [1024/10284]	Loss: 0.7401	LR: 0.100000
Training Epoch: 2 [1280/10284]	Loss: 0.6742	LR: 0.100000
Training Epoch: 2 [1536/10284]	Loss: 0.7679	LR: 0.100000
Training Epoch: 2 [1792/10284]	Loss: 0.8998	LR: 0.100000
Training Epoch: 2 [2048/10284]	Loss: 0.8400	LR: 0.100000
Training Epoch: 2 [2304/10284]	Loss: 0.7652	LR: 0.100000
Training Epoch: 2 [2560/10284]	Loss: 0.8006	LR: 0.100000
Training Epoch: 2 [2816/10284]	Loss: 0.7655	LR: 0.100000
Training Epoch: 2 [3072/10284]	Loss: 0.7797	LR: 0.100000
Training Epoch: 2 [3328/10284]	Loss: 0.8016	LR: 0.100000
Training Epoch: 2 [3584/10284]	Loss: 0.7550	LR: 0.100000
Training Epoch: 2 [3840/10284]	Loss: 0.8087	LR: 0.100000
Training Epoch: 2 [4096/10284]	Loss: 0.7354	LR: 0.100000
Training Epoch: 2 [4352/10284]	Loss: 0.7617	LR: 0.100000
Training Epoch: 2 [4608/10284]	Loss: 0.7363	LR: 0.100000
Training Epoch: 2 [4864/10284]	Loss: 0.6926	LR: 0.100000
Training Epoch: 2 [5120/10284]	Loss: 0.6835	LR: 0.100000
Training Epoch: 2 [5376/10284]	Loss: 0.7066	LR: 0.100000
Training Epoch: 2 [5632/10284]	Loss: 0.7893	LR: 0.100000
Training Epoch: 2 [5888/10284]	Loss: 0.7078	LR: 0.100000
Training Epoch: 2 [6144/10284]	Loss: 0.7324	LR: 0.100000
Training Epoch: 2 [6400/10284]	Loss: 0.7620	LR: 0.100000
Training Epoch: 2 [6656/10284]	Loss: 0.7914	LR: 0.100000
Training Epoch: 2 [6912/10284]	Loss: 0.7181	LR: 0.100000
Training Epoch: 2 [7168/10284]	Loss: 0.8418	LR: 0.100000
Training Epoch: 2 [7424/10284]	Loss: 0.7961	LR: 0.100000
Training Epoch: 2 [7680/10284]	Loss: 0.7823	LR: 0.100000
Training Epoch: 2 [7936/10284]	Loss: 0.7489	LR: 0.100000
Training Epoch: 2 [8192/10284]	Loss: 1.1785	LR: 0.100000
Training Epoch: 2 [8448/10284]	Loss: 0.6882	LR: 0.100000
Training Epoch: 2 [8704/10284]	Loss: 0.8724	LR: 0.100000
Training Epoch: 2 [8960/10284]	Loss: 0.8624	LR: 0.100000
Training Epoch: 2 [9216/10284]	Loss: 0.7872	LR: 0.100000
Training Epoch: 2 [9472/10284]	Loss: 0.8808	LR: 0.100000
Training Epoch: 2 [9728/10284]	Loss: 0.7445	LR: 0.100000
Training Epoch: 2 [9984/10284]	Loss: 0.7119	LR: 0.100000
Training Epoch: 2 [10240/10284]	Loss: 0.7043	LR: 0.100000
Training Epoch: 2 [10284/10284]	Loss: 0.7376	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7754, Train Accuracy: 0.5160
Epoch 2 training time consumed: 150.33s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0743, Accuracy: 0.5550, Time consumed:7.96s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-2-best.pth
Training Epoch: 3 [256/10284]	Loss: 0.7558	LR: 0.100000
Training Epoch: 3 [512/10284]	Loss: 0.6530	LR: 0.100000
Training Epoch: 3 [768/10284]	Loss: 0.6767	LR: 0.100000
Training Epoch: 3 [1024/10284]	Loss: 0.7385	LR: 0.100000
Training Epoch: 3 [1280/10284]	Loss: 0.7423	LR: 0.100000
Training Epoch: 3 [1536/10284]	Loss: 0.6818	LR: 0.100000
Training Epoch: 3 [1792/10284]	Loss: 0.8313	LR: 0.100000
Training Epoch: 3 [2048/10284]	Loss: 0.7175	LR: 0.100000
Training Epoch: 3 [2304/10284]	Loss: 0.9173	LR: 0.100000
Training Epoch: 3 [2560/10284]	Loss: 0.6987	LR: 0.100000
Training Epoch: 3 [2816/10284]	Loss: 0.8614	LR: 0.100000
Training Epoch: 3 [3072/10284]	Loss: 0.7262	LR: 0.100000
Training Epoch: 3 [3328/10284]	Loss: 0.7043	LR: 0.100000
Training Epoch: 3 [3584/10284]	Loss: 0.7179	LR: 0.100000
Training Epoch: 3 [3840/10284]	Loss: 0.7140	LR: 0.100000
Training Epoch: 3 [4096/10284]	Loss: 0.7004	LR: 0.100000
Training Epoch: 3 [4352/10284]	Loss: 0.7003	LR: 0.100000
Training Epoch: 3 [4608/10284]	Loss: 0.6889	LR: 0.100000
Training Epoch: 3 [4864/10284]	Loss: 0.7097	LR: 0.100000
Training Epoch: 3 [5120/10284]	Loss: 0.6968	LR: 0.100000
Training Epoch: 3 [5376/10284]	Loss: 0.7119	LR: 0.100000
Training Epoch: 3 [5632/10284]	Loss: 0.6935	LR: 0.100000
Training Epoch: 3 [5888/10284]	Loss: 0.6939	LR: 0.100000
Training Epoch: 3 [6144/10284]	Loss: 0.6842	LR: 0.100000
Training Epoch: 3 [6400/10284]	Loss: 0.6811	LR: 0.100000
Training Epoch: 3 [6656/10284]	Loss: 0.6858	LR: 0.100000
Training Epoch: 3 [6912/10284]	Loss: 0.6825	LR: 0.100000
Training Epoch: 3 [7168/10284]	Loss: 0.6898	LR: 0.100000
Training Epoch: 3 [7424/10284]	Loss: 0.6889	LR: 0.100000
Training Epoch: 3 [7680/10284]	Loss: 0.6874	LR: 0.100000
Training Epoch: 3 [7936/10284]	Loss: 0.7402	LR: 0.100000
Training Epoch: 3 [8192/10284]	Loss: 0.6892	LR: 0.100000
Training Epoch: 3 [8448/10284]	Loss: 0.7167	LR: 0.100000
Training Epoch: 3 [8704/10284]	Loss: 0.6644	LR: 0.100000
Training Epoch: 3 [8960/10284]	Loss: 0.6815	LR: 0.100000
Training Epoch: 3 [9216/10284]	Loss: 0.6674	LR: 0.100000
Training Epoch: 3 [9472/10284]	Loss: 0.6700	LR: 0.100000
Training Epoch: 3 [9728/10284]	Loss: 0.6832	LR: 0.100000
Training Epoch: 3 [9984/10284]	Loss: 0.6777	LR: 0.100000
Training Epoch: 3 [10240/10284]	Loss: 0.6841	LR: 0.100000
Training Epoch: 3 [10284/10284]	Loss: 0.6285	LR: 0.100000
Epoch 3 - Average Train Loss: 0.7098, Train Accuracy: 0.5426
Epoch 3 training time consumed: 150.44s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5588, Time consumed:8.00s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-3-best.pth
Training Epoch: 4 [256/10284]	Loss: 0.6967	LR: 0.100000
Training Epoch: 4 [512/10284]	Loss: 0.7334	LR: 0.100000
Training Epoch: 4 [768/10284]	Loss: 0.6624	LR: 0.100000
Training Epoch: 4 [1024/10284]	Loss: 0.6888	LR: 0.100000
Training Epoch: 4 [1280/10284]	Loss: 0.6876	LR: 0.100000
Training Epoch: 4 [1536/10284]	Loss: 0.6770	LR: 0.100000
Training Epoch: 4 [1792/10284]	Loss: 0.6771	LR: 0.100000
Training Epoch: 4 [2048/10284]	Loss: 0.6930	LR: 0.100000
Training Epoch: 4 [2304/10284]	Loss: 0.6886	LR: 0.100000
Training Epoch: 4 [2560/10284]	Loss: 0.7173	LR: 0.100000
Training Epoch: 4 [2816/10284]	Loss: 0.6807	LR: 0.100000
Training Epoch: 4 [3072/10284]	Loss: 0.6867	LR: 0.100000
Training Epoch: 4 [3328/10284]	Loss: 0.7144	LR: 0.100000
Training Epoch: 4 [3584/10284]	Loss: 0.7391	LR: 0.100000
Training Epoch: 4 [3840/10284]	Loss: 0.7367	LR: 0.100000
Training Epoch: 4 [4096/10284]	Loss: 0.6503	LR: 0.100000
Training Epoch: 4 [4352/10284]	Loss: 0.6962	LR: 0.100000
Training Epoch: 4 [4608/10284]	Loss: 0.7268	LR: 0.100000
Training Epoch: 4 [4864/10284]	Loss: 0.6863	LR: 0.100000
Training Epoch: 4 [5120/10284]	Loss: 0.6859	LR: 0.100000
Training Epoch: 4 [5376/10284]	Loss: 0.6981	LR: 0.100000
Training Epoch: 4 [5632/10284]	Loss: 0.6828	LR: 0.100000
Training Epoch: 4 [5888/10284]	Loss: 0.6935	LR: 0.100000
Training Epoch: 4 [6144/10284]	Loss: 0.7089	LR: 0.100000
Training Epoch: 4 [6400/10284]	Loss: 0.6915	LR: 0.100000
Training Epoch: 4 [6656/10284]	Loss: 0.6744	LR: 0.100000
Training Epoch: 4 [6912/10284]	Loss: 0.7093	LR: 0.100000
Training Epoch: 4 [7168/10284]	Loss: 0.7169	LR: 0.100000
Training Epoch: 4 [7424/10284]	Loss: 0.6787	LR: 0.100000
Training Epoch: 4 [7680/10284]	Loss: 0.6916	LR: 0.100000
Training Epoch: 4 [7936/10284]	Loss: 0.7063	LR: 0.100000
Training Epoch: 4 [8192/10284]	Loss: 0.7141	LR: 0.100000
Training Epoch: 4 [8448/10284]	Loss: 0.6885	LR: 0.100000
Training Epoch: 4 [8704/10284]	Loss: 0.6884	LR: 0.100000
Training Epoch: 4 [8960/10284]	Loss: 0.7175	LR: 0.100000
Training Epoch: 4 [9216/10284]	Loss: 0.6881	LR: 0.100000
Training Epoch: 4 [9472/10284]	Loss: 0.6978	LR: 0.100000
Training Epoch: 4 [9728/10284]	Loss: 0.6651	LR: 0.100000
Training Epoch: 4 [9984/10284]	Loss: 0.6970	LR: 0.100000
Training Epoch: 4 [10240/10284]	Loss: 0.6847	LR: 0.100000
Training Epoch: 4 [10284/10284]	Loss: 0.8243	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6960, Train Accuracy: 0.5582
Epoch 4 training time consumed: 151.54s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0029, Accuracy: 0.5898, Time consumed:8.13s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-4-best.pth
Training Epoch: 5 [256/10284]	Loss: 0.7054	LR: 0.100000
Training Epoch: 5 [512/10284]	Loss: 0.7005	LR: 0.100000
Training Epoch: 5 [768/10284]	Loss: 0.7724	LR: 0.100000
Training Epoch: 5 [1024/10284]	Loss: 0.7129	LR: 0.100000
Training Epoch: 5 [1280/10284]	Loss: 0.7564	LR: 0.100000
Training Epoch: 5 [1536/10284]	Loss: 0.7064	LR: 0.100000
Training Epoch: 5 [1792/10284]	Loss: 0.6793	LR: 0.100000
Training Epoch: 5 [2048/10284]	Loss: 0.6909	LR: 0.100000
Training Epoch: 5 [2304/10284]	Loss: 0.6998	LR: 0.100000
Training Epoch: 5 [2560/10284]	Loss: 0.6870	LR: 0.100000
Training Epoch: 5 [2816/10284]	Loss: 0.7215	LR: 0.100000
Training Epoch: 5 [3072/10284]	Loss: 0.6754	LR: 0.100000
Training Epoch: 5 [3328/10284]	Loss: 0.7224	LR: 0.100000
Training Epoch: 5 [3584/10284]	Loss: 0.6771	LR: 0.100000
Training Epoch: 5 [3840/10284]	Loss: 0.6787	LR: 0.100000
Training Epoch: 5 [4096/10284]	Loss: 0.7051	LR: 0.100000
Training Epoch: 5 [4352/10284]	Loss: 0.6814	LR: 0.100000
Training Epoch: 5 [4608/10284]	Loss: 0.6948	LR: 0.100000
Training Epoch: 5 [4864/10284]	Loss: 0.6976	LR: 0.100000
Training Epoch: 5 [5120/10284]	Loss: 0.6877	LR: 0.100000
Training Epoch: 5 [5376/10284]	Loss: 0.6739	LR: 0.100000
Training Epoch: 5 [5632/10284]	Loss: 0.6745	LR: 0.100000
Training Epoch: 5 [5888/10284]	Loss: 0.6776	LR: 0.100000
Training Epoch: 5 [6144/10284]	Loss: 0.6957	LR: 0.100000
Training Epoch: 5 [6400/10284]	Loss: 0.6600	LR: 0.100000
Training Epoch: 5 [6656/10284]	Loss: 0.6829	LR: 0.100000
Training Epoch: 5 [6912/10284]	Loss: 0.6849	LR: 0.100000
Training Epoch: 5 [7168/10284]	Loss: 0.6756	LR: 0.100000
Training Epoch: 5 [7424/10284]	Loss: 0.6901	LR: 0.100000
Training Epoch: 5 [7680/10284]	Loss: 0.6924	LR: 0.100000
Training Epoch: 5 [7936/10284]	Loss: 0.6900	LR: 0.100000
Training Epoch: 5 [8192/10284]	Loss: 0.6871	LR: 0.100000
Training Epoch: 5 [8448/10284]	Loss: 0.6614	LR: 0.100000
Training Epoch: 5 [8704/10284]	Loss: 0.6638	LR: 0.100000
Training Epoch: 5 [8960/10284]	Loss: 0.6642	LR: 0.100000
Training Epoch: 5 [9216/10284]	Loss: 0.6974	LR: 0.100000
Training Epoch: 5 [9472/10284]	Loss: 0.6827	LR: 0.100000
Training Epoch: 5 [9728/10284]	Loss: 0.6844	LR: 0.100000
Training Epoch: 5 [9984/10284]	Loss: 0.6693	LR: 0.100000
Training Epoch: 5 [10240/10284]	Loss: 0.6742	LR: 0.100000
Training Epoch: 5 [10284/10284]	Loss: 0.7710	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6912, Train Accuracy: 0.5661
Epoch 5 training time consumed: 150.62s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0029, Accuracy: 0.6092, Time consumed:8.19s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-5-best.pth
Training Epoch: 6 [256/10284]	Loss: 0.6766	LR: 0.100000
Training Epoch: 6 [512/10284]	Loss: 0.6813	LR: 0.100000
Training Epoch: 6 [768/10284]	Loss: 0.6713	LR: 0.100000
Training Epoch: 6 [1024/10284]	Loss: 0.6764	LR: 0.100000
Training Epoch: 6 [1280/10284]	Loss: 0.6665	LR: 0.100000
Training Epoch: 6 [1536/10284]	Loss: 0.6759	LR: 0.100000
Training Epoch: 6 [1792/10284]	Loss: 0.6699	LR: 0.100000
Training Epoch: 6 [2048/10284]	Loss: 0.6718	LR: 0.100000
Training Epoch: 6 [2304/10284]	Loss: 0.6612	LR: 0.100000
Training Epoch: 6 [2560/10284]	Loss: 0.6681	LR: 0.100000
Training Epoch: 6 [2816/10284]	Loss: 0.6554	LR: 0.100000
Training Epoch: 6 [3072/10284]	Loss: 0.6687	LR: 0.100000
Training Epoch: 6 [3328/10284]	Loss: 0.6769	LR: 0.100000
Training Epoch: 6 [3584/10284]	Loss: 0.6767	LR: 0.100000
Training Epoch: 6 [3840/10284]	Loss: 0.6818	LR: 0.100000
Training Epoch: 6 [4096/10284]	Loss: 0.6738	LR: 0.100000
Training Epoch: 6 [4352/10284]	Loss: 0.6923	LR: 0.100000
Training Epoch: 6 [4608/10284]	Loss: 0.6797	LR: 0.100000
Training Epoch: 6 [4864/10284]	Loss: 0.6847	LR: 0.100000
Training Epoch: 6 [5120/10284]	Loss: 0.6994	LR: 0.100000
Training Epoch: 6 [5376/10284]	Loss: 0.6828	LR: 0.100000
Training Epoch: 6 [5632/10284]	Loss: 0.6717	LR: 0.100000
Training Epoch: 6 [5888/10284]	Loss: 0.6763	LR: 0.100000
Training Epoch: 6 [6144/10284]	Loss: 0.6724	LR: 0.100000
Training Epoch: 6 [6400/10284]	Loss: 0.6725	LR: 0.100000
Training Epoch: 6 [6656/10284]	Loss: 0.6836	LR: 0.100000
Training Epoch: 6 [6912/10284]	Loss: 0.6719	LR: 0.100000
Training Epoch: 6 [7168/10284]	Loss: 0.6723	LR: 0.100000
Training Epoch: 6 [7424/10284]	Loss: 0.6707	LR: 0.100000
Training Epoch: 6 [7680/10284]	Loss: 0.6463	LR: 0.100000
Training Epoch: 6 [7936/10284]	Loss: 0.6948	LR: 0.100000
Training Epoch: 6 [8192/10284]	Loss: 0.6640	LR: 0.100000
Training Epoch: 6 [8448/10284]	Loss: 0.6536	LR: 0.100000
Training Epoch: 6 [8704/10284]	Loss: 0.6724	LR: 0.100000
Training Epoch: 6 [8960/10284]	Loss: 0.6857	LR: 0.100000
Training Epoch: 6 [9216/10284]	Loss: 0.6852	LR: 0.100000
Training Epoch: 6 [9472/10284]	Loss: 0.6674	LR: 0.100000
Training Epoch: 6 [9728/10284]	Loss: 0.6835	LR: 0.100000
Training Epoch: 6 [9984/10284]	Loss: 0.6572	LR: 0.100000
Training Epoch: 6 [10240/10284]	Loss: 0.6772	LR: 0.100000
Training Epoch: 6 [10284/10284]	Loss: 0.6789	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6743, Train Accuracy: 0.5843
Epoch 6 training time consumed: 151.05s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0033, Accuracy: 0.5075, Time consumed:8.12s
Training Epoch: 7 [256/10284]	Loss: 0.6562	LR: 0.100000
Training Epoch: 7 [512/10284]	Loss: 0.6321	LR: 0.100000
Training Epoch: 7 [768/10284]	Loss: 0.6989	LR: 0.100000
Training Epoch: 7 [1024/10284]	Loss: 0.6578	LR: 0.100000
Training Epoch: 7 [1280/10284]	Loss: 0.6790	LR: 0.100000
Training Epoch: 7 [1536/10284]	Loss: 0.6815	LR: 0.100000
Training Epoch: 7 [1792/10284]	Loss: 0.6786	LR: 0.100000
Training Epoch: 7 [2048/10284]	Loss: 0.6590	LR: 0.100000
Training Epoch: 7 [2304/10284]	Loss: 0.6536	LR: 0.100000
Training Epoch: 7 [2560/10284]	Loss: 0.6670	LR: 0.100000
Training Epoch: 7 [2816/10284]	Loss: 0.6737	LR: 0.100000
Training Epoch: 7 [3072/10284]	Loss: 0.6945	LR: 0.100000
Training Epoch: 7 [3328/10284]	Loss: 0.6763	LR: 0.100000
Training Epoch: 7 [3584/10284]	Loss: 0.6739	LR: 0.100000
Training Epoch: 7 [3840/10284]	Loss: 0.6774	LR: 0.100000
Training Epoch: 7 [4096/10284]	Loss: 0.6696	LR: 0.100000
Training Epoch: 7 [4352/10284]	Loss: 0.6742	LR: 0.100000
Training Epoch: 7 [4608/10284]	Loss: 0.6672	LR: 0.100000
Training Epoch: 7 [4864/10284]	Loss: 0.6744	LR: 0.100000
Training Epoch: 7 [5120/10284]	Loss: 0.6812	LR: 0.100000
Training Epoch: 7 [5376/10284]	Loss: 0.6575	LR: 0.100000
Training Epoch: 7 [5632/10284]	Loss: 0.6590	LR: 0.100000
Training Epoch: 7 [5888/10284]	Loss: 0.6527	LR: 0.100000
Training Epoch: 7 [6144/10284]	Loss: 0.6684	LR: 0.100000
Training Epoch: 7 [6400/10284]	Loss: 0.6484	LR: 0.100000
Training Epoch: 7 [6656/10284]	Loss: 0.6808	LR: 0.100000
Training Epoch: 7 [6912/10284]	Loss: 0.6864	LR: 0.100000
Training Epoch: 7 [7168/10284]	Loss: 0.6743	LR: 0.100000
Training Epoch: 7 [7424/10284]	Loss: 0.6764	LR: 0.100000
Training Epoch: 7 [7680/10284]	Loss: 0.6527	LR: 0.100000
Training Epoch: 7 [7936/10284]	Loss: 0.6570	LR: 0.100000
Training Epoch: 7 [8192/10284]	Loss: 0.6425	LR: 0.100000
Training Epoch: 7 [8448/10284]	Loss: 0.6635	LR: 0.100000
Training Epoch: 7 [8704/10284]	Loss: 0.6690	LR: 0.100000
Training Epoch: 7 [8960/10284]	Loss: 0.6697	LR: 0.100000
Training Epoch: 7 [9216/10284]	Loss: 0.6442	LR: 0.100000
Training Epoch: 7 [9472/10284]	Loss: 0.6771	LR: 0.100000
Training Epoch: 7 [9728/10284]	Loss: 0.6934	LR: 0.100000
Training Epoch: 7 [9984/10284]	Loss: 0.6586	LR: 0.100000
Training Epoch: 7 [10240/10284]	Loss: 0.6446	LR: 0.100000
Training Epoch: 7 [10284/10284]	Loss: 0.7598	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6680, Train Accuracy: 0.5978
Epoch 7 training time consumed: 151.22s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0029, Accuracy: 0.6184, Time consumed:8.15s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-7-best.pth
Training Epoch: 8 [256/10284]	Loss: 0.6388	LR: 0.100000
Training Epoch: 8 [512/10284]	Loss: 0.6428	LR: 0.100000
Training Epoch: 8 [768/10284]	Loss: 0.6717	LR: 0.100000
Training Epoch: 8 [1024/10284]	Loss: 0.6568	LR: 0.100000
Training Epoch: 8 [1280/10284]	Loss: 0.6552	LR: 0.100000
Training Epoch: 8 [1536/10284]	Loss: 0.6653	LR: 0.100000
Training Epoch: 8 [1792/10284]	Loss: 0.6654	LR: 0.100000
Training Epoch: 8 [2048/10284]	Loss: 0.6596	LR: 0.100000
Training Epoch: 8 [2304/10284]	Loss: 0.6576	LR: 0.100000
Training Epoch: 8 [2560/10284]	Loss: 0.6614	LR: 0.100000
Training Epoch: 8 [2816/10284]	Loss: 0.6437	LR: 0.100000
Training Epoch: 8 [3072/10284]	Loss: 0.6759	LR: 0.100000
Training Epoch: 8 [3328/10284]	Loss: 0.6630	LR: 0.100000
Training Epoch: 8 [3584/10284]	Loss: 0.7327	LR: 0.100000
Training Epoch: 8 [3840/10284]	Loss: 0.6827	LR: 0.100000
Training Epoch: 8 [4096/10284]	Loss: 0.6627	LR: 0.100000
Training Epoch: 8 [4352/10284]	Loss: 0.6902	LR: 0.100000
Training Epoch: 8 [4608/10284]	Loss: 0.6911	LR: 0.100000
Training Epoch: 8 [4864/10284]	Loss: 0.6680	LR: 0.100000
Training Epoch: 8 [5120/10284]	Loss: 0.6759	LR: 0.100000
Training Epoch: 8 [5376/10284]	Loss: 0.6707	LR: 0.100000
Training Epoch: 8 [5632/10284]	Loss: 0.6816	LR: 0.100000
Training Epoch: 8 [5888/10284]	Loss: 0.6890	LR: 0.100000
Training Epoch: 8 [6144/10284]	Loss: 0.6779	LR: 0.100000
Training Epoch: 8 [6400/10284]	Loss: 0.6982	LR: 0.100000
Training Epoch: 8 [6656/10284]	Loss: 0.6672	LR: 0.100000
Training Epoch: 8 [6912/10284]	Loss: 0.6555	LR: 0.100000
Training Epoch: 8 [7168/10284]	Loss: 0.6660	LR: 0.100000
Training Epoch: 8 [7424/10284]	Loss: 0.6732	LR: 0.100000
Training Epoch: 8 [7680/10284]	Loss: 0.6924	LR: 0.100000
Training Epoch: 8 [7936/10284]	Loss: 0.6551	LR: 0.100000
Training Epoch: 8 [8192/10284]	Loss: 0.6539	LR: 0.100000
Training Epoch: 8 [8448/10284]	Loss: 0.6418	LR: 0.100000
Training Epoch: 8 [8704/10284]	Loss: 0.6332	LR: 0.100000
Training Epoch: 8 [8960/10284]	Loss: 0.6631	LR: 0.100000
Training Epoch: 8 [9216/10284]	Loss: 0.6428	LR: 0.100000
Training Epoch: 8 [9472/10284]	Loss: 0.6586	LR: 0.100000
Training Epoch: 8 [9728/10284]	Loss: 0.6750	LR: 0.100000
Training Epoch: 8 [9984/10284]	Loss: 0.6490	LR: 0.100000
Training Epoch: 8 [10240/10284]	Loss: 0.6463	LR: 0.100000
Training Epoch: 8 [10284/10284]	Loss: 0.6930	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6664, Train Accuracy: 0.6005
Epoch 8 training time consumed: 151.27s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0037, Accuracy: 0.5017, Time consumed:8.32s
Training Epoch: 9 [256/10284]	Loss: 0.6718	LR: 0.100000
Training Epoch: 9 [512/10284]	Loss: 0.6810	LR: 0.100000
Training Epoch: 9 [768/10284]	Loss: 0.6791	LR: 0.100000
Training Epoch: 9 [1024/10284]	Loss: 0.6368	LR: 0.100000
Training Epoch: 9 [1280/10284]	Loss: 0.6792	LR: 0.100000
Training Epoch: 9 [1536/10284]	Loss: 0.6610	LR: 0.100000
Training Epoch: 9 [1792/10284]	Loss: 0.6665	LR: 0.100000
Training Epoch: 9 [2048/10284]	Loss: 0.6796	LR: 0.100000
Training Epoch: 9 [2304/10284]	Loss: 0.6647	LR: 0.100000
Training Epoch: 9 [2560/10284]	Loss: 0.6379	LR: 0.100000
Training Epoch: 9 [2816/10284]	Loss: 0.6526	LR: 0.100000
Training Epoch: 9 [3072/10284]	Loss: 0.6777	LR: 0.100000
Training Epoch: 9 [3328/10284]	Loss: 0.6518	LR: 0.100000
Training Epoch: 9 [3584/10284]	Loss: 0.6666	LR: 0.100000
Training Epoch: 9 [3840/10284]	Loss: 0.6521	LR: 0.100000
Training Epoch: 9 [4096/10284]	Loss: 0.6389	LR: 0.100000
Training Epoch: 9 [4352/10284]	Loss: 0.6602	LR: 0.100000
Training Epoch: 9 [4608/10284]	Loss: 0.6393	LR: 0.100000
Training Epoch: 9 [4864/10284]	Loss: 0.6655	LR: 0.100000
Training Epoch: 9 [5120/10284]	Loss: 0.6753	LR: 0.100000
Training Epoch: 9 [5376/10284]	Loss: 0.6524	LR: 0.100000
Training Epoch: 9 [5632/10284]	Loss: 0.6644	LR: 0.100000
Training Epoch: 9 [5888/10284]	Loss: 0.6451	LR: 0.100000
Training Epoch: 9 [6144/10284]	Loss: 0.6677	LR: 0.100000
Training Epoch: 9 [6400/10284]	Loss: 0.6462	LR: 0.100000
Training Epoch: 9 [6656/10284]	Loss: 0.6239	LR: 0.100000
Training Epoch: 9 [6912/10284]	Loss: 0.6028	LR: 0.100000
Training Epoch: 9 [7168/10284]	Loss: 0.6495	LR: 0.100000
Training Epoch: 9 [7424/10284]	Loss: 0.6493	LR: 0.100000
Training Epoch: 9 [7680/10284]	Loss: 0.6377	LR: 0.100000
Training Epoch: 9 [7936/10284]	Loss: 0.6545	LR: 0.100000
Training Epoch: 9 [8192/10284]	Loss: 0.6566	LR: 0.100000
Training Epoch: 9 [8448/10284]	Loss: 0.6601	LR: 0.100000
Training Epoch: 9 [8704/10284]	Loss: 0.6392	LR: 0.100000
Training Epoch: 9 [8960/10284]	Loss: 0.6352	LR: 0.100000
Training Epoch: 9 [9216/10284]	Loss: 0.6540	LR: 0.100000
Training Epoch: 9 [9472/10284]	Loss: 0.6884	LR: 0.100000
Training Epoch: 9 [9728/10284]	Loss: 0.6437	LR: 0.100000
Training Epoch: 9 [9984/10284]	Loss: 0.6527	LR: 0.100000
Training Epoch: 9 [10240/10284]	Loss: 0.6652	LR: 0.100000
Training Epoch: 9 [10284/10284]	Loss: 0.6165	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6555, Train Accuracy: 0.6219
Epoch 9 training time consumed: 151.23s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0029, Accuracy: 0.6281, Time consumed:8.39s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-9-best.pth
Training Epoch: 10 [256/10284]	Loss: 0.6470	LR: 0.020000
Training Epoch: 10 [512/10284]	Loss: 0.6605	LR: 0.020000
Training Epoch: 10 [768/10284]	Loss: 0.7375	LR: 0.020000
Training Epoch: 10 [1024/10284]	Loss: 0.6783	LR: 0.020000
Training Epoch: 10 [1280/10284]	Loss: 0.6616	LR: 0.020000
Training Epoch: 10 [1536/10284]	Loss: 0.6163	LR: 0.020000
Training Epoch: 10 [1792/10284]	Loss: 0.6467	LR: 0.020000
Training Epoch: 10 [2048/10284]	Loss: 0.6426	LR: 0.020000
Training Epoch: 10 [2304/10284]	Loss: 0.6558	LR: 0.020000
Training Epoch: 10 [2560/10284]	Loss: 0.6493	LR: 0.020000
Training Epoch: 10 [2816/10284]	Loss: 0.6506	LR: 0.020000
Training Epoch: 10 [3072/10284]	Loss: 0.6597	LR: 0.020000
Training Epoch: 10 [3328/10284]	Loss: 0.6484	LR: 0.020000
Training Epoch: 10 [3584/10284]	Loss: 0.6533	LR: 0.020000
Training Epoch: 10 [3840/10284]	Loss: 0.6572	LR: 0.020000
Training Epoch: 10 [4096/10284]	Loss: 0.6492	LR: 0.020000
Training Epoch: 10 [4352/10284]	Loss: 0.6147	LR: 0.020000
Training Epoch: 10 [4608/10284]	Loss: 0.6326	LR: 0.020000
Training Epoch: 10 [4864/10284]	Loss: 0.6458	LR: 0.020000
Training Epoch: 10 [5120/10284]	Loss: 0.6426	LR: 0.020000
Training Epoch: 10 [5376/10284]	Loss: 0.6346	LR: 0.020000
Training Epoch: 10 [5632/10284]	Loss: 0.6622	LR: 0.020000
Training Epoch: 10 [5888/10284]	Loss: 0.6557	LR: 0.020000
Training Epoch: 10 [6144/10284]	Loss: 0.6220	LR: 0.020000
Training Epoch: 10 [6400/10284]	Loss: 0.6218	LR: 0.020000
Training Epoch: 10 [6656/10284]	Loss: 0.6288	LR: 0.020000
Training Epoch: 10 [6912/10284]	Loss: 0.6261	LR: 0.020000
Training Epoch: 10 [7168/10284]	Loss: 0.6377	LR: 0.020000
Training Epoch: 10 [7424/10284]	Loss: 0.6321	LR: 0.020000
Training Epoch: 10 [7680/10284]	Loss: 0.6142	LR: 0.020000
Training Epoch: 10 [7936/10284]	Loss: 0.6586	LR: 0.020000
Training Epoch: 10 [8192/10284]	Loss: 0.6167	LR: 0.020000
Training Epoch: 10 [8448/10284]	Loss: 0.6595	LR: 0.020000
Training Epoch: 10 [8704/10284]	Loss: 0.6429	LR: 0.020000
Training Epoch: 10 [8960/10284]	Loss: 0.6049	LR: 0.020000
Training Epoch: 10 [9216/10284]	Loss: 0.6130	LR: 0.020000
Training Epoch: 10 [9472/10284]	Loss: 0.6210	LR: 0.020000
Training Epoch: 10 [9728/10284]	Loss: 0.5901	LR: 0.020000
Training Epoch: 10 [9984/10284]	Loss: 0.6193	LR: 0.020000
Training Epoch: 10 [10240/10284]	Loss: 0.6047	LR: 0.020000
Training Epoch: 10 [10284/10284]	Loss: 0.5648	LR: 0.020000
Epoch 10 - Average Train Loss: 0.6401, Train Accuracy: 0.6503
Epoch 10 training time consumed: 151.01s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0031, Accuracy: 0.6232, Time consumed:8.32s
Training Epoch: 11 [256/10284]	Loss: 0.6502	LR: 0.020000
Training Epoch: 11 [512/10284]	Loss: 0.6107	LR: 0.020000
Training Epoch: 11 [768/10284]	Loss: 0.6371	LR: 0.020000
Training Epoch: 11 [1024/10284]	Loss: 0.6473	LR: 0.020000
Training Epoch: 11 [1280/10284]	Loss: 0.6052	LR: 0.020000
Training Epoch: 11 [1536/10284]	Loss: 0.6205	LR: 0.020000
Training Epoch: 11 [1792/10284]	Loss: 0.6133	LR: 0.020000
Training Epoch: 11 [2048/10284]	Loss: 0.6554	LR: 0.020000
Training Epoch: 11 [2304/10284]	Loss: 0.6061	LR: 0.020000
Training Epoch: 11 [2560/10284]	Loss: 0.6182	LR: 0.020000
Training Epoch: 11 [2816/10284]	Loss: 0.6648	LR: 0.020000
Training Epoch: 11 [3072/10284]	Loss: 0.5809	LR: 0.020000
Training Epoch: 11 [3328/10284]	Loss: 0.6340	LR: 0.020000
Training Epoch: 11 [3584/10284]	Loss: 0.6094	LR: 0.020000
Training Epoch: 11 [3840/10284]	Loss: 0.6071	LR: 0.020000
Training Epoch: 11 [4096/10284]	Loss: 0.5825	LR: 0.020000
Training Epoch: 11 [4352/10284]	Loss: 0.5780	LR: 0.020000
Training Epoch: 11 [4608/10284]	Loss: 0.6300	LR: 0.020000
Training Epoch: 11 [4864/10284]	Loss: 0.5677	LR: 0.020000
Training Epoch: 11 [5120/10284]	Loss: 0.5904	LR: 0.020000
Training Epoch: 11 [5376/10284]	Loss: 0.5558	LR: 0.020000
Training Epoch: 11 [5632/10284]	Loss: 0.6674	LR: 0.020000
Training Epoch: 11 [5888/10284]	Loss: 0.6167	LR: 0.020000
Training Epoch: 11 [6144/10284]	Loss: 0.5524	LR: 0.020000
Training Epoch: 11 [6400/10284]	Loss: 0.6106	LR: 0.020000
Training Epoch: 11 [6656/10284]	Loss: 0.6530	LR: 0.020000
Training Epoch: 11 [6912/10284]	Loss: 0.6239	LR: 0.020000
Training Epoch: 11 [7168/10284]	Loss: 0.6064	LR: 0.020000
Training Epoch: 11 [7424/10284]	Loss: 0.6346	LR: 0.020000
Training Epoch: 11 [7680/10284]	Loss: 0.5948	LR: 0.020000
Training Epoch: 11 [7936/10284]	Loss: 0.5952	LR: 0.020000
Training Epoch: 11 [8192/10284]	Loss: 0.6488	LR: 0.020000
Training Epoch: 11 [8448/10284]	Loss: 0.5805	LR: 0.020000
Training Epoch: 11 [8704/10284]	Loss: 0.6259	LR: 0.020000
Training Epoch: 11 [8960/10284]	Loss: 0.6036	LR: 0.020000
Training Epoch: 11 [9216/10284]	Loss: 0.6040	LR: 0.020000
Training Epoch: 11 [9472/10284]	Loss: 0.6208	LR: 0.020000
Training Epoch: 11 [9728/10284]	Loss: 0.5815	LR: 0.020000
Training Epoch: 11 [9984/10284]	Loss: 0.6446	LR: 0.020000
Training Epoch: 11 [10240/10284]	Loss: 0.5892	LR: 0.020000
Training Epoch: 11 [10284/10284]	Loss: 0.6434	LR: 0.020000
Epoch 11 - Average Train Loss: 0.6131, Train Accuracy: 0.6708
Epoch 11 training time consumed: 151.23s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0029, Accuracy: 0.6407, Time consumed:8.14s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-11-best.pth
Training Epoch: 12 [256/10284]	Loss: 0.5861	LR: 0.020000
Training Epoch: 12 [512/10284]	Loss: 0.5858	LR: 0.020000
Training Epoch: 12 [768/10284]	Loss: 0.6118	LR: 0.020000
Training Epoch: 12 [1024/10284]	Loss: 0.6274	LR: 0.020000
Training Epoch: 12 [1280/10284]	Loss: 0.5947	LR: 0.020000
Training Epoch: 12 [1536/10284]	Loss: 0.5547	LR: 0.020000
Training Epoch: 12 [1792/10284]	Loss: 0.5757	LR: 0.020000
Training Epoch: 12 [2048/10284]	Loss: 0.5478	LR: 0.020000
Training Epoch: 12 [2304/10284]	Loss: 0.6817	LR: 0.020000
Training Epoch: 12 [2560/10284]	Loss: 0.6037	LR: 0.020000
Training Epoch: 12 [2816/10284]	Loss: 0.6279	LR: 0.020000
Training Epoch: 12 [3072/10284]	Loss: 0.5930	LR: 0.020000
Training Epoch: 12 [3328/10284]	Loss: 0.5975	LR: 0.020000
Training Epoch: 12 [3584/10284]	Loss: 0.5757	LR: 0.020000
Training Epoch: 12 [3840/10284]	Loss: 0.6259	LR: 0.020000
Training Epoch: 12 [4096/10284]	Loss: 0.5702	LR: 0.020000
Training Epoch: 12 [4352/10284]	Loss: 0.6320	LR: 0.020000
Training Epoch: 12 [4608/10284]	Loss: 0.6099	LR: 0.020000
Training Epoch: 12 [4864/10284]	Loss: 0.5906	LR: 0.020000
Training Epoch: 12 [5120/10284]	Loss: 0.6072	LR: 0.020000
Training Epoch: 12 [5376/10284]	Loss: 0.6096	LR: 0.020000
Training Epoch: 12 [5632/10284]	Loss: 0.5867	LR: 0.020000
Training Epoch: 12 [5888/10284]	Loss: 0.6404	LR: 0.020000
Training Epoch: 12 [6144/10284]	Loss: 0.6197	LR: 0.020000
Training Epoch: 12 [6400/10284]	Loss: 0.6099	LR: 0.020000
Training Epoch: 12 [6656/10284]	Loss: 0.5980	LR: 0.020000
Training Epoch: 12 [6912/10284]	Loss: 0.5702	LR: 0.020000
Training Epoch: 12 [7168/10284]	Loss: 0.5959	LR: 0.020000
Training Epoch: 12 [7424/10284]	Loss: 0.5858	LR: 0.020000
Training Epoch: 12 [7680/10284]	Loss: 0.5801	LR: 0.020000
Training Epoch: 12 [7936/10284]	Loss: 0.5607	LR: 0.020000
Training Epoch: 12 [8192/10284]	Loss: 0.5680	LR: 0.020000
Training Epoch: 12 [8448/10284]	Loss: 0.5855	LR: 0.020000
Training Epoch: 12 [8704/10284]	Loss: 0.5612	LR: 0.020000
Training Epoch: 12 [8960/10284]	Loss: 0.5774	LR: 0.020000
Training Epoch: 12 [9216/10284]	Loss: 0.5760	LR: 0.020000
Training Epoch: 12 [9472/10284]	Loss: 0.5283	LR: 0.020000
Training Epoch: 12 [9728/10284]	Loss: 0.5657	LR: 0.020000
Training Epoch: 12 [9984/10284]	Loss: 0.5527	LR: 0.020000
Training Epoch: 12 [10240/10284]	Loss: 0.5743	LR: 0.020000
Training Epoch: 12 [10284/10284]	Loss: 0.6005	LR: 0.020000
Epoch 12 - Average Train Loss: 0.5912, Train Accuracy: 0.6952
Epoch 12 training time consumed: 151.28s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0033, Accuracy: 0.6300, Time consumed:8.17s
Training Epoch: 13 [256/10284]	Loss: 0.4934	LR: 0.020000
Training Epoch: 13 [512/10284]	Loss: 0.5562	LR: 0.020000
Training Epoch: 13 [768/10284]	Loss: 0.5412	LR: 0.020000
Training Epoch: 13 [1024/10284]	Loss: 0.5626	LR: 0.020000
Training Epoch: 13 [1280/10284]	Loss: 0.5536	LR: 0.020000
Training Epoch: 13 [1536/10284]	Loss: 0.5684	LR: 0.020000
Training Epoch: 13 [1792/10284]	Loss: 0.5227	LR: 0.020000
Training Epoch: 13 [2048/10284]	Loss: 0.5472	LR: 0.020000
Training Epoch: 13 [2304/10284]	Loss: 0.5354	LR: 0.020000
Training Epoch: 13 [2560/10284]	Loss: 0.5304	LR: 0.020000
Training Epoch: 13 [2816/10284]	Loss: 0.5857	LR: 0.020000
Training Epoch: 13 [3072/10284]	Loss: 0.5516	LR: 0.020000
Training Epoch: 13 [3328/10284]	Loss: 0.5352	LR: 0.020000
Training Epoch: 13 [3584/10284]	Loss: 0.5651	LR: 0.020000
Training Epoch: 13 [3840/10284]	Loss: 0.5644	LR: 0.020000
Training Epoch: 13 [4096/10284]	Loss: 0.6241	LR: 0.020000
Training Epoch: 13 [4352/10284]	Loss: 0.5204	LR: 0.020000
Training Epoch: 13 [4608/10284]	Loss: 0.5225	LR: 0.020000
Training Epoch: 13 [4864/10284]	Loss: 0.5043	LR: 0.020000
Training Epoch: 13 [5120/10284]	Loss: 0.5112	LR: 0.020000
Training Epoch: 13 [5376/10284]	Loss: 0.4942	LR: 0.020000
Training Epoch: 13 [5632/10284]	Loss: 0.5275	LR: 0.020000
Training Epoch: 13 [5888/10284]	Loss: 0.4878	LR: 0.020000
Training Epoch: 13 [6144/10284]	Loss: 0.5280	LR: 0.020000
Training Epoch: 13 [6400/10284]	Loss: 0.4936	LR: 0.020000
Training Epoch: 13 [6656/10284]	Loss: 0.4922	LR: 0.020000
Training Epoch: 13 [6912/10284]	Loss: 0.5559	LR: 0.020000
Training Epoch: 13 [7168/10284]	Loss: 0.5429	LR: 0.020000
Training Epoch: 13 [7424/10284]	Loss: 0.4901	LR: 0.020000
Training Epoch: 13 [7680/10284]	Loss: 0.5856	LR: 0.020000
Training Epoch: 13 [7936/10284]	Loss: 0.5102	LR: 0.020000
Training Epoch: 13 [8192/10284]	Loss: 0.5072	LR: 0.020000
Training Epoch: 13 [8448/10284]	Loss: 0.4897	LR: 0.020000
Training Epoch: 13 [8704/10284]	Loss: 0.5123	LR: 0.020000
Training Epoch: 13 [8960/10284]	Loss: 0.4734	LR: 0.020000
Training Epoch: 13 [9216/10284]	Loss: 0.4899	LR: 0.020000
Training Epoch: 13 [9472/10284]	Loss: 0.4995	LR: 0.020000
Training Epoch: 13 [9728/10284]	Loss: 0.4810	LR: 0.020000
Training Epoch: 13 [9984/10284]	Loss: 0.4060	LR: 0.020000
Training Epoch: 13 [10240/10284]	Loss: 0.4574	LR: 0.020000
Training Epoch: 13 [10284/10284]	Loss: 0.5730	LR: 0.020000
Epoch 13 - Average Train Loss: 0.5232, Train Accuracy: 0.7457
Epoch 13 training time consumed: 151.58s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0034, Accuracy: 0.6140, Time consumed:8.26s
Training Epoch: 14 [256/10284]	Loss: 0.4725	LR: 0.020000
Training Epoch: 14 [512/10284]	Loss: 0.5352	LR: 0.020000
Training Epoch: 14 [768/10284]	Loss: 0.5057	LR: 0.020000
Training Epoch: 14 [1024/10284]	Loss: 0.4683	LR: 0.020000
Training Epoch: 14 [1280/10284]	Loss: 0.4719	LR: 0.020000
Training Epoch: 14 [1536/10284]	Loss: 0.4730	LR: 0.020000
Training Epoch: 14 [1792/10284]	Loss: 0.4754	LR: 0.020000
Training Epoch: 14 [2048/10284]	Loss: 0.4320	LR: 0.020000
Training Epoch: 14 [2304/10284]	Loss: 0.5292	LR: 0.020000
Training Epoch: 14 [2560/10284]	Loss: 0.4571	LR: 0.020000
Training Epoch: 14 [2816/10284]	Loss: 0.5229	LR: 0.020000
Training Epoch: 14 [3072/10284]	Loss: 0.5029	LR: 0.020000
Training Epoch: 14 [3328/10284]	Loss: 0.4980	LR: 0.020000
Training Epoch: 14 [3584/10284]	Loss: 0.4843	LR: 0.020000
Training Epoch: 14 [3840/10284]	Loss: 0.4758	LR: 0.020000
Training Epoch: 14 [4096/10284]	Loss: 0.4333	LR: 0.020000
Training Epoch: 14 [4352/10284]	Loss: 0.4800	LR: 0.020000
Training Epoch: 14 [4608/10284]	Loss: 0.4468	LR: 0.020000
Training Epoch: 14 [4864/10284]	Loss: 0.4570	LR: 0.020000
Training Epoch: 14 [5120/10284]	Loss: 0.5437	LR: 0.020000
Training Epoch: 14 [5376/10284]	Loss: 0.5110	LR: 0.020000
Training Epoch: 14 [5632/10284]	Loss: 0.4201	LR: 0.020000
Training Epoch: 14 [5888/10284]	Loss: 0.4246	LR: 0.020000
Training Epoch: 14 [6144/10284]	Loss: 0.4109	LR: 0.020000
Training Epoch: 14 [6400/10284]	Loss: 0.4175	LR: 0.020000
Training Epoch: 14 [6656/10284]	Loss: 0.4753	LR: 0.020000
Training Epoch: 14 [6912/10284]	Loss: 0.4140	LR: 0.020000
Training Epoch: 14 [7168/10284]	Loss: 0.4722	LR: 0.020000
Training Epoch: 14 [7424/10284]	Loss: 0.4742	LR: 0.020000
Training Epoch: 14 [7680/10284]	Loss: 0.4498	LR: 0.020000
Training Epoch: 14 [7936/10284]	Loss: 0.4023	LR: 0.020000
Training Epoch: 14 [8192/10284]	Loss: 0.4602	LR: 0.020000
Training Epoch: 14 [8448/10284]	Loss: 0.4302	LR: 0.020000
Training Epoch: 14 [8704/10284]	Loss: 0.3564	LR: 0.020000
Training Epoch: 14 [8960/10284]	Loss: 0.3701	LR: 0.020000
Training Epoch: 14 [9216/10284]	Loss: 0.4017	LR: 0.020000
Training Epoch: 14 [9472/10284]	Loss: 0.3756	LR: 0.020000
Training Epoch: 14 [9728/10284]	Loss: 0.3517	LR: 0.020000
Training Epoch: 14 [9984/10284]	Loss: 0.4206	LR: 0.020000
Training Epoch: 14 [10240/10284]	Loss: 0.3347	LR: 0.020000
Training Epoch: 14 [10284/10284]	Loss: 0.4842	LR: 0.020000
Epoch 14 - Average Train Loss: 0.4511, Train Accuracy: 0.7894
Epoch 14 training time consumed: 151.35s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0033, Accuracy: 0.6930, Time consumed:8.22s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-14-best.pth
Training Epoch: 15 [256/10284]	Loss: 0.4882	LR: 0.020000
Training Epoch: 15 [512/10284]	Loss: 0.3486	LR: 0.020000
Training Epoch: 15 [768/10284]	Loss: 0.4612	LR: 0.020000
Training Epoch: 15 [1024/10284]	Loss: 0.3946	LR: 0.020000
Training Epoch: 15 [1280/10284]	Loss: 0.3708	LR: 0.020000
Training Epoch: 15 [1536/10284]	Loss: 0.3981	LR: 0.020000
Training Epoch: 15 [1792/10284]	Loss: 0.3745	LR: 0.020000
Training Epoch: 15 [2048/10284]	Loss: 0.3768	LR: 0.020000
Training Epoch: 15 [2304/10284]	Loss: 0.3657	LR: 0.020000
Training Epoch: 15 [2560/10284]	Loss: 0.3674	LR: 0.020000
Training Epoch: 15 [2816/10284]	Loss: 0.3404	LR: 0.020000
Training Epoch: 15 [3072/10284]	Loss: 0.3642	LR: 0.020000
Training Epoch: 15 [3328/10284]	Loss: 0.3767	LR: 0.020000
Training Epoch: 15 [3584/10284]	Loss: 0.4494	LR: 0.020000
Training Epoch: 15 [3840/10284]	Loss: 0.3771	LR: 0.020000
Training Epoch: 15 [4096/10284]	Loss: 0.4339	LR: 0.020000
Training Epoch: 15 [4352/10284]	Loss: 0.4613	LR: 0.020000
Training Epoch: 15 [4608/10284]	Loss: 0.3799	LR: 0.020000
Training Epoch: 15 [4864/10284]	Loss: 0.4352	LR: 0.020000
Training Epoch: 15 [5120/10284]	Loss: 0.3605	LR: 0.020000
Training Epoch: 15 [5376/10284]	Loss: 0.4236	LR: 0.020000
Training Epoch: 15 [5632/10284]	Loss: 0.4719	LR: 0.020000
Training Epoch: 15 [5888/10284]	Loss: 0.3560	LR: 0.020000
Training Epoch: 15 [6144/10284]	Loss: 0.4613	LR: 0.020000
Training Epoch: 15 [6400/10284]	Loss: 0.3618	LR: 0.020000
Training Epoch: 15 [6656/10284]	Loss: 0.3940	LR: 0.020000
Training Epoch: 15 [6912/10284]	Loss: 0.3636	LR: 0.020000
Training Epoch: 15 [7168/10284]	Loss: 0.3891	LR: 0.020000
Training Epoch: 15 [7424/10284]	Loss: 0.4061	LR: 0.020000
Training Epoch: 15 [7680/10284]	Loss: 0.3842	LR: 0.020000
Training Epoch: 15 [7936/10284]	Loss: 0.3207	LR: 0.020000
Training Epoch: 15 [8192/10284]	Loss: 0.3391	LR: 0.020000
Training Epoch: 15 [8448/10284]	Loss: 0.3469	LR: 0.020000
Training Epoch: 15 [8704/10284]	Loss: 0.4069	LR: 0.020000
Training Epoch: 15 [8960/10284]	Loss: 0.4295	LR: 0.020000
Training Epoch: 15 [9216/10284]	Loss: 0.3557	LR: 0.020000
Training Epoch: 15 [9472/10284]	Loss: 0.3514	LR: 0.020000
Training Epoch: 15 [9728/10284]	Loss: 0.3609	LR: 0.020000
Training Epoch: 15 [9984/10284]	Loss: 0.3088	LR: 0.020000
Training Epoch: 15 [10240/10284]	Loss: 0.2914	LR: 0.020000
Training Epoch: 15 [10284/10284]	Loss: 0.3567	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3861, Train Accuracy: 0.8284
Epoch 15 training time consumed: 151.62s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0013, Accuracy: 0.8722, Time consumed:8.37s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-15-best.pth
Training Epoch: 16 [256/10284]	Loss: 0.3534	LR: 0.020000
Training Epoch: 16 [512/10284]	Loss: 0.3028	LR: 0.020000
Training Epoch: 16 [768/10284]	Loss: 0.2973	LR: 0.020000
Training Epoch: 16 [1024/10284]	Loss: 0.3157	LR: 0.020000
Training Epoch: 16 [1280/10284]	Loss: 0.3209	LR: 0.020000
Training Epoch: 16 [1536/10284]	Loss: 0.3289	LR: 0.020000
Training Epoch: 16 [1792/10284]	Loss: 0.3678	LR: 0.020000
Training Epoch: 16 [2048/10284]	Loss: 0.3013	LR: 0.020000
Training Epoch: 16 [2304/10284]	Loss: 0.3180	LR: 0.020000
Training Epoch: 16 [2560/10284]	Loss: 0.3541	LR: 0.020000
Training Epoch: 16 [2816/10284]	Loss: 0.3158	LR: 0.020000
Training Epoch: 16 [3072/10284]	Loss: 0.4002	LR: 0.020000
Training Epoch: 16 [3328/10284]	Loss: 0.3221	LR: 0.020000
Training Epoch: 16 [3584/10284]	Loss: 0.2864	LR: 0.020000
Training Epoch: 16 [3840/10284]	Loss: 0.2654	LR: 0.020000
Training Epoch: 16 [4096/10284]	Loss: 0.3250	LR: 0.020000
Training Epoch: 16 [4352/10284]	Loss: 0.2726	LR: 0.020000
Training Epoch: 16 [4608/10284]	Loss: 0.3811	LR: 0.020000
Training Epoch: 16 [4864/10284]	Loss: 0.3128	LR: 0.020000
Training Epoch: 16 [5120/10284]	Loss: 0.3295	LR: 0.020000
Training Epoch: 16 [5376/10284]	Loss: 0.3865	LR: 0.020000
Training Epoch: 16 [5632/10284]	Loss: 0.2765	LR: 0.020000
Training Epoch: 16 [5888/10284]	Loss: 0.2903	LR: 0.020000
Training Epoch: 16 [6144/10284]	Loss: 0.3774	LR: 0.020000
Training Epoch: 16 [6400/10284]	Loss: 0.2518	LR: 0.020000
Training Epoch: 16 [6656/10284]	Loss: 0.3006	LR: 0.020000
Training Epoch: 16 [6912/10284]	Loss: 0.3901	LR: 0.020000
Training Epoch: 16 [7168/10284]	Loss: 0.2709	LR: 0.020000
Training Epoch: 16 [7424/10284]	Loss: 0.4106	LR: 0.020000
Training Epoch: 16 [7680/10284]	Loss: 0.2786	LR: 0.020000
Training Epoch: 16 [7936/10284]	Loss: 0.3415	LR: 0.020000
Training Epoch: 16 [8192/10284]	Loss: 0.3042	LR: 0.020000
Training Epoch: 16 [8448/10284]	Loss: 0.3064	LR: 0.020000
Training Epoch: 16 [8704/10284]	Loss: 0.3160	LR: 0.020000
Training Epoch: 16 [8960/10284]	Loss: 0.2693	LR: 0.020000
Training Epoch: 16 [9216/10284]	Loss: 0.2673	LR: 0.020000
Training Epoch: 16 [9472/10284]	Loss: 0.3029	LR: 0.020000
Training Epoch: 16 [9728/10284]	Loss: 0.2666	LR: 0.020000
Training Epoch: 16 [9984/10284]	Loss: 0.3065	LR: 0.020000
Training Epoch: 16 [10240/10284]	Loss: 0.2766	LR: 0.020000
Training Epoch: 16 [10284/10284]	Loss: 0.2820	LR: 0.020000
Epoch 16 - Average Train Loss: 0.3164, Train Accuracy: 0.8655
Epoch 16 training time consumed: 151.21s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0017, Accuracy: 0.8358, Time consumed:8.21s
Training Epoch: 17 [256/10284]	Loss: 0.2671	LR: 0.020000
Training Epoch: 17 [512/10284]	Loss: 0.3177	LR: 0.020000
Training Epoch: 17 [768/10284]	Loss: 0.2818	LR: 0.020000
Training Epoch: 17 [1024/10284]	Loss: 0.3180	LR: 0.020000
Training Epoch: 17 [1280/10284]	Loss: 0.2753	LR: 0.020000
Training Epoch: 17 [1536/10284]	Loss: 0.3002	LR: 0.020000
Training Epoch: 17 [1792/10284]	Loss: 0.2775	LR: 0.020000
Training Epoch: 17 [2048/10284]	Loss: 0.3219	LR: 0.020000
Training Epoch: 17 [2304/10284]	Loss: 0.3242	LR: 0.020000
Training Epoch: 17 [2560/10284]	Loss: 0.3301	LR: 0.020000
Training Epoch: 17 [2816/10284]	Loss: 0.2728	LR: 0.020000
Training Epoch: 17 [3072/10284]	Loss: 0.2460	LR: 0.020000
Training Epoch: 17 [3328/10284]	Loss: 0.2718	LR: 0.020000
Training Epoch: 17 [3584/10284]	Loss: 0.2962	LR: 0.020000
Training Epoch: 17 [3840/10284]	Loss: 0.2842	LR: 0.020000
Training Epoch: 17 [4096/10284]	Loss: 0.2789	LR: 0.020000
Training Epoch: 17 [4352/10284]	Loss: 0.3221	LR: 0.020000
Training Epoch: 17 [4608/10284]	Loss: 0.3208	LR: 0.020000
Training Epoch: 17 [4864/10284]	Loss: 0.2495	LR: 0.020000
Training Epoch: 17 [5120/10284]	Loss: 0.3143	LR: 0.020000
Training Epoch: 17 [5376/10284]	Loss: 0.3617	LR: 0.020000
Training Epoch: 17 [5632/10284]	Loss: 0.3269	LR: 0.020000
Training Epoch: 17 [5888/10284]	Loss: 0.2058	LR: 0.020000
Training Epoch: 17 [6144/10284]	Loss: 0.2999	LR: 0.020000
Training Epoch: 17 [6400/10284]	Loss: 0.3307	LR: 0.020000
Training Epoch: 17 [6656/10284]	Loss: 0.3115	LR: 0.020000
Training Epoch: 17 [6912/10284]	Loss: 0.3072	LR: 0.020000
Training Epoch: 17 [7168/10284]	Loss: 0.2953	LR: 0.020000
Training Epoch: 17 [7424/10284]	Loss: 0.2868	LR: 0.020000
Training Epoch: 17 [7680/10284]	Loss: 0.2855	LR: 0.020000
Training Epoch: 17 [7936/10284]	Loss: 0.2359	LR: 0.020000
Training Epoch: 17 [8192/10284]	Loss: 0.2698	LR: 0.020000
Training Epoch: 17 [8448/10284]	Loss: 0.2396	LR: 0.020000
Training Epoch: 17 [8704/10284]	Loss: 0.2379	LR: 0.020000
Training Epoch: 17 [8960/10284]	Loss: 0.2439	LR: 0.020000
Training Epoch: 17 [9216/10284]	Loss: 0.2120	LR: 0.020000
Training Epoch: 17 [9472/10284]	Loss: 0.2482	LR: 0.020000
Training Epoch: 17 [9728/10284]	Loss: 0.2913	LR: 0.020000
Training Epoch: 17 [9984/10284]	Loss: 0.2773	LR: 0.020000
Training Epoch: 17 [10240/10284]	Loss: 0.3352	LR: 0.020000
Training Epoch: 17 [10284/10284]	Loss: 0.1676	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2863, Train Accuracy: 0.8801
Epoch 17 training time consumed: 151.35s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0013, Accuracy: 0.8809, Time consumed:8.16s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-17-best.pth
Training Epoch: 18 [256/10284]	Loss: 0.2807	LR: 0.020000
Training Epoch: 18 [512/10284]	Loss: 0.2844	LR: 0.020000
Training Epoch: 18 [768/10284]	Loss: 0.3471	LR: 0.020000
Training Epoch: 18 [1024/10284]	Loss: 0.2058	LR: 0.020000
Training Epoch: 18 [1280/10284]	Loss: 0.3115	LR: 0.020000
Training Epoch: 18 [1536/10284]	Loss: 0.2157	LR: 0.020000
Training Epoch: 18 [1792/10284]	Loss: 0.2478	LR: 0.020000
Training Epoch: 18 [2048/10284]	Loss: 0.2711	LR: 0.020000
Training Epoch: 18 [2304/10284]	Loss: 0.2866	LR: 0.020000
Training Epoch: 18 [2560/10284]	Loss: 0.2303	LR: 0.020000
Training Epoch: 18 [2816/10284]	Loss: 0.2754	LR: 0.020000
Training Epoch: 18 [3072/10284]	Loss: 0.2843	LR: 0.020000
Training Epoch: 18 [3328/10284]	Loss: 0.2723	LR: 0.020000
Training Epoch: 18 [3584/10284]	Loss: 0.2209	LR: 0.020000
Training Epoch: 18 [3840/10284]	Loss: 0.2689	LR: 0.020000
Training Epoch: 18 [4096/10284]	Loss: 0.2446	LR: 0.020000
Training Epoch: 18 [4352/10284]	Loss: 0.2160	LR: 0.020000
Training Epoch: 18 [4608/10284]	Loss: 0.2404	LR: 0.020000
Training Epoch: 18 [4864/10284]	Loss: 0.2622	LR: 0.020000
Training Epoch: 18 [5120/10284]	Loss: 0.3707	LR: 0.020000
Training Epoch: 18 [5376/10284]	Loss: 0.2915	LR: 0.020000
Training Epoch: 18 [5632/10284]	Loss: 0.2248	LR: 0.020000
Training Epoch: 18 [5888/10284]	Loss: 0.1999	LR: 0.020000
Training Epoch: 18 [6144/10284]	Loss: 0.3306	LR: 0.020000
Training Epoch: 18 [6400/10284]	Loss: 0.2896	LR: 0.020000
Training Epoch: 18 [6656/10284]	Loss: 0.2327	LR: 0.020000
Training Epoch: 18 [6912/10284]	Loss: 0.2013	LR: 0.020000
Training Epoch: 18 [7168/10284]	Loss: 0.2127	LR: 0.020000
Training Epoch: 18 [7424/10284]	Loss: 0.2627	LR: 0.020000
Training Epoch: 18 [7680/10284]	Loss: 0.1719	LR: 0.020000
Training Epoch: 18 [7936/10284]	Loss: 0.1991	LR: 0.020000
Training Epoch: 18 [8192/10284]	Loss: 0.2441	LR: 0.020000
Training Epoch: 18 [8448/10284]	Loss: 0.1781	LR: 0.020000
Training Epoch: 18 [8704/10284]	Loss: 0.1997	LR: 0.020000
Training Epoch: 18 [8960/10284]	Loss: 0.1671	LR: 0.020000
Training Epoch: 18 [9216/10284]	Loss: 0.2718	LR: 0.020000
Training Epoch: 18 [9472/10284]	Loss: 0.2406	LR: 0.020000
Training Epoch: 18 [9728/10284]	Loss: 0.1748	LR: 0.020000
Training Epoch: 18 [9984/10284]	Loss: 0.2713	LR: 0.020000
Training Epoch: 18 [10240/10284]	Loss: 0.2313	LR: 0.020000
Training Epoch: 18 [10284/10284]	Loss: 0.2272	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2482, Train Accuracy: 0.8967
Epoch 18 training time consumed: 150.77s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0019, Accuracy: 0.8262, Time consumed:8.12s
Training Epoch: 19 [256/10284]	Loss: 0.2308	LR: 0.020000
Training Epoch: 19 [512/10284]	Loss: 0.2366	LR: 0.020000
Training Epoch: 19 [768/10284]	Loss: 0.2198	LR: 0.020000
Training Epoch: 19 [1024/10284]	Loss: 0.2538	LR: 0.020000
Training Epoch: 19 [1280/10284]	Loss: 0.2464	LR: 0.020000
Training Epoch: 19 [1536/10284]	Loss: 0.2332	LR: 0.020000
Training Epoch: 19 [1792/10284]	Loss: 0.2101	LR: 0.020000
Training Epoch: 19 [2048/10284]	Loss: 0.2653	LR: 0.020000
Training Epoch: 19 [2304/10284]	Loss: 0.2000	LR: 0.020000
Training Epoch: 19 [2560/10284]	Loss: 0.2186	LR: 0.020000
Training Epoch: 19 [2816/10284]	Loss: 0.2124	LR: 0.020000
Training Epoch: 19 [3072/10284]	Loss: 0.2615	LR: 0.020000
Training Epoch: 19 [3328/10284]	Loss: 0.2370	LR: 0.020000
Training Epoch: 19 [3584/10284]	Loss: 0.2969	LR: 0.020000
Training Epoch: 19 [3840/10284]	Loss: 0.1821	LR: 0.020000
Training Epoch: 19 [4096/10284]	Loss: 0.3350	LR: 0.020000
Training Epoch: 19 [4352/10284]	Loss: 0.2845	LR: 0.020000
Training Epoch: 19 [4608/10284]	Loss: 0.2072	LR: 0.020000
Training Epoch: 19 [4864/10284]	Loss: 0.2611	LR: 0.020000
Training Epoch: 19 [5120/10284]	Loss: 0.1873	LR: 0.020000
Training Epoch: 19 [5376/10284]	Loss: 0.1827	LR: 0.020000
Training Epoch: 19 [5632/10284]	Loss: 0.2274	LR: 0.020000
Training Epoch: 19 [5888/10284]	Loss: 0.2678	LR: 0.020000
Training Epoch: 19 [6144/10284]	Loss: 0.1431	LR: 0.020000
Training Epoch: 19 [6400/10284]	Loss: 0.1494	LR: 0.020000
Training Epoch: 19 [6656/10284]	Loss: 0.2232	LR: 0.020000
Training Epoch: 19 [6912/10284]	Loss: 0.2925	LR: 0.020000
Training Epoch: 19 [7168/10284]	Loss: 0.2147	LR: 0.020000
Training Epoch: 19 [7424/10284]	Loss: 0.2386	LR: 0.020000
Training Epoch: 19 [7680/10284]	Loss: 0.2410	LR: 0.020000
Training Epoch: 19 [7936/10284]	Loss: 0.2470	LR: 0.020000
Training Epoch: 19 [8192/10284]	Loss: 0.1972	LR: 0.020000
Training Epoch: 19 [8448/10284]	Loss: 0.2675	LR: 0.020000
Training Epoch: 19 [8704/10284]	Loss: 0.2249	LR: 0.020000
Training Epoch: 19 [8960/10284]	Loss: 0.2501	LR: 0.020000
Training Epoch: 19 [9216/10284]	Loss: 0.1871	LR: 0.020000
Training Epoch: 19 [9472/10284]	Loss: 0.1993	LR: 0.020000
Training Epoch: 19 [9728/10284]	Loss: 0.1875	LR: 0.020000
Training Epoch: 19 [9984/10284]	Loss: 0.2095	LR: 0.020000
Training Epoch: 19 [10240/10284]	Loss: 0.2554	LR: 0.020000
Training Epoch: 19 [10284/10284]	Loss: 0.4010	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2304, Train Accuracy: 0.9084
Epoch 19 training time consumed: 151.11s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0011, Accuracy: 0.8935, Time consumed:8.09s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-19-best.pth
Training Epoch: 20 [256/10284]	Loss: 0.1942	LR: 0.004000
Training Epoch: 20 [512/10284]	Loss: 0.2701	LR: 0.004000
Training Epoch: 20 [768/10284]	Loss: 0.1858	LR: 0.004000
Training Epoch: 20 [1024/10284]	Loss: 0.2147	LR: 0.004000
Training Epoch: 20 [1280/10284]	Loss: 0.2299	LR: 0.004000
Training Epoch: 20 [1536/10284]	Loss: 0.2661	LR: 0.004000
Training Epoch: 20 [1792/10284]	Loss: 0.2882	LR: 0.004000
Training Epoch: 20 [2048/10284]	Loss: 0.1917	LR: 0.004000
Training Epoch: 20 [2304/10284]	Loss: 0.2331	LR: 0.004000
Training Epoch: 20 [2560/10284]	Loss: 0.2335	LR: 0.004000
Training Epoch: 20 [2816/10284]	Loss: 0.1977	LR: 0.004000
Training Epoch: 20 [3072/10284]	Loss: 0.1644	LR: 0.004000
Training Epoch: 20 [3328/10284]	Loss: 0.2246	LR: 0.004000
Training Epoch: 20 [3584/10284]	Loss: 0.1997	LR: 0.004000
Training Epoch: 20 [3840/10284]	Loss: 0.2118	LR: 0.004000
Training Epoch: 20 [4096/10284]	Loss: 0.1747	LR: 0.004000
Training Epoch: 20 [4352/10284]	Loss: 0.2051	LR: 0.004000
Training Epoch: 20 [4608/10284]	Loss: 0.1978	LR: 0.004000
Training Epoch: 20 [4864/10284]	Loss: 0.2326	LR: 0.004000
Training Epoch: 20 [5120/10284]	Loss: 0.2238	LR: 0.004000
Training Epoch: 20 [5376/10284]	Loss: 0.1796	LR: 0.004000
Training Epoch: 20 [5632/10284]	Loss: 0.2374	LR: 0.004000
Training Epoch: 20 [5888/10284]	Loss: 0.2063	LR: 0.004000
Training Epoch: 20 [6144/10284]	Loss: 0.1474	LR: 0.004000
Training Epoch: 20 [6400/10284]	Loss: 0.1896	LR: 0.004000
Training Epoch: 20 [6656/10284]	Loss: 0.2096	LR: 0.004000
Training Epoch: 20 [6912/10284]	Loss: 0.1817	LR: 0.004000
Training Epoch: 20 [7168/10284]	Loss: 0.1416	LR: 0.004000
Training Epoch: 20 [7424/10284]	Loss: 0.1937	LR: 0.004000
Training Epoch: 20 [7680/10284]	Loss: 0.2158	LR: 0.004000
Training Epoch: 20 [7936/10284]	Loss: 0.1655	LR: 0.004000
Training Epoch: 20 [8192/10284]	Loss: 0.1823	LR: 0.004000
Training Epoch: 20 [8448/10284]	Loss: 0.1976	LR: 0.004000
Training Epoch: 20 [8704/10284]	Loss: 0.1402	LR: 0.004000
Training Epoch: 20 [8960/10284]	Loss: 0.1614	LR: 0.004000
Training Epoch: 20 [9216/10284]	Loss: 0.1677	LR: 0.004000
Training Epoch: 20 [9472/10284]	Loss: 0.1646	LR: 0.004000
Training Epoch: 20 [9728/10284]	Loss: 0.1368	LR: 0.004000
Training Epoch: 20 [9984/10284]	Loss: 0.2653	LR: 0.004000
Training Epoch: 20 [10240/10284]	Loss: 0.2132	LR: 0.004000
Training Epoch: 20 [10284/10284]	Loss: 0.2815	LR: 0.004000
Epoch 20 - Average Train Loss: 0.2013, Train Accuracy: 0.9161
Epoch 20 training time consumed: 151.34s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0007, Accuracy: 0.9370, Time consumed:8.15s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-20-best.pth
Training Epoch: 21 [256/10284]	Loss: 0.1476	LR: 0.004000
Training Epoch: 21 [512/10284]	Loss: 0.1484	LR: 0.004000
Training Epoch: 21 [768/10284]	Loss: 0.1671	LR: 0.004000
Training Epoch: 21 [1024/10284]	Loss: 0.1811	LR: 0.004000
Training Epoch: 21 [1280/10284]	Loss: 0.3144	LR: 0.004000
Training Epoch: 21 [1536/10284]	Loss: 0.1659	LR: 0.004000
Training Epoch: 21 [1792/10284]	Loss: 0.1614	LR: 0.004000
Training Epoch: 21 [2048/10284]	Loss: 0.1606	LR: 0.004000
Training Epoch: 21 [2304/10284]	Loss: 0.1783	LR: 0.004000
Training Epoch: 21 [2560/10284]	Loss: 0.1688	LR: 0.004000
Training Epoch: 21 [2816/10284]	Loss: 0.1949	LR: 0.004000
Training Epoch: 21 [3072/10284]	Loss: 0.1700	LR: 0.004000
Training Epoch: 21 [3328/10284]	Loss: 0.1930	LR: 0.004000
Training Epoch: 21 [3584/10284]	Loss: 0.1770	LR: 0.004000
Training Epoch: 21 [3840/10284]	Loss: 0.1821	LR: 0.004000
Training Epoch: 21 [4096/10284]	Loss: 0.1954	LR: 0.004000
Training Epoch: 21 [4352/10284]	Loss: 0.2742	LR: 0.004000
Training Epoch: 21 [4608/10284]	Loss: 0.2072	LR: 0.004000
Training Epoch: 21 [4864/10284]	Loss: 0.1372	LR: 0.004000
Training Epoch: 21 [5120/10284]	Loss: 0.1825	LR: 0.004000
Training Epoch: 21 [5376/10284]	Loss: 0.1685	LR: 0.004000
Training Epoch: 21 [5632/10284]	Loss: 0.1700	LR: 0.004000
Training Epoch: 21 [5888/10284]	Loss: 0.1509	LR: 0.004000
Training Epoch: 21 [6144/10284]	Loss: 0.1463	LR: 0.004000
Training Epoch: 21 [6400/10284]	Loss: 0.1575	LR: 0.004000
Training Epoch: 21 [6656/10284]	Loss: 0.1680	LR: 0.004000
Training Epoch: 21 [6912/10284]	Loss: 0.1493	LR: 0.004000
Training Epoch: 21 [7168/10284]	Loss: 0.2394	LR: 0.004000
Training Epoch: 21 [7424/10284]	Loss: 0.1459	LR: 0.004000
Training Epoch: 21 [7680/10284]	Loss: 0.2199	LR: 0.004000
Training Epoch: 21 [7936/10284]	Loss: 0.2042	LR: 0.004000
Training Epoch: 21 [8192/10284]	Loss: 0.1884	LR: 0.004000
Training Epoch: 21 [8448/10284]	Loss: 0.1632	LR: 0.004000
Training Epoch: 21 [8704/10284]	Loss: 0.1662	LR: 0.004000
Training Epoch: 21 [8960/10284]	Loss: 0.2027	LR: 0.004000
Training Epoch: 21 [9216/10284]	Loss: 0.1544	LR: 0.004000
Training Epoch: 21 [9472/10284]	Loss: 0.2312	LR: 0.004000
Training Epoch: 21 [9728/10284]	Loss: 0.2153	LR: 0.004000
Training Epoch: 21 [9984/10284]	Loss: 0.1439	LR: 0.004000
Training Epoch: 21 [10240/10284]	Loss: 0.2110	LR: 0.004000
Training Epoch: 21 [10284/10284]	Loss: 0.2850	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1830, Train Accuracy: 0.9238
Epoch 21 training time consumed: 151.70s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0008, Accuracy: 0.9269, Time consumed:8.06s
Training Epoch: 22 [256/10284]	Loss: 0.2105	LR: 0.004000
Training Epoch: 22 [512/10284]	Loss: 0.1951	LR: 0.004000
Training Epoch: 22 [768/10284]	Loss: 0.2539	LR: 0.004000
Training Epoch: 22 [1024/10284]	Loss: 0.1399	LR: 0.004000
Training Epoch: 22 [1280/10284]	Loss: 0.1718	LR: 0.004000
Training Epoch: 22 [1536/10284]	Loss: 0.2139	LR: 0.004000
Training Epoch: 22 [1792/10284]	Loss: 0.1544	LR: 0.004000
Training Epoch: 22 [2048/10284]	Loss: 0.1668	LR: 0.004000
Training Epoch: 22 [2304/10284]	Loss: 0.1814	LR: 0.004000
Training Epoch: 22 [2560/10284]	Loss: 0.1431	LR: 0.004000
Training Epoch: 22 [2816/10284]	Loss: 0.1543	LR: 0.004000
Training Epoch: 22 [3072/10284]	Loss: 0.1888	LR: 0.004000
Training Epoch: 22 [3328/10284]	Loss: 0.1757	LR: 0.004000
Training Epoch: 22 [3584/10284]	Loss: 0.1282	LR: 0.004000
Training Epoch: 22 [3840/10284]	Loss: 0.1934	LR: 0.004000
Training Epoch: 22 [4096/10284]	Loss: 0.2048	LR: 0.004000
Training Epoch: 22 [4352/10284]	Loss: 0.1543	LR: 0.004000
Training Epoch: 22 [4608/10284]	Loss: 0.1979	LR: 0.004000
Training Epoch: 22 [4864/10284]	Loss: 0.1913	LR: 0.004000
Training Epoch: 22 [5120/10284]	Loss: 0.1773	LR: 0.004000
Training Epoch: 22 [5376/10284]	Loss: 0.1366	LR: 0.004000
Training Epoch: 22 [5632/10284]	Loss: 0.2002	LR: 0.004000
Training Epoch: 22 [5888/10284]	Loss: 0.1321	LR: 0.004000
Training Epoch: 22 [6144/10284]	Loss: 0.1555	LR: 0.004000
Training Epoch: 22 [6400/10284]	Loss: 0.1375	LR: 0.004000
Training Epoch: 22 [6656/10284]	Loss: 0.1738	LR: 0.004000
Training Epoch: 22 [6912/10284]	Loss: 0.1481	LR: 0.004000
Training Epoch: 22 [7168/10284]	Loss: 0.1653	LR: 0.004000
Training Epoch: 22 [7424/10284]	Loss: 0.1518	LR: 0.004000
Training Epoch: 22 [7680/10284]	Loss: 0.1473	LR: 0.004000
Training Epoch: 22 [7936/10284]	Loss: 0.1645	LR: 0.004000
Training Epoch: 22 [8192/10284]	Loss: 0.1553	LR: 0.004000
Training Epoch: 22 [8448/10284]	Loss: 0.1600	LR: 0.004000
Training Epoch: 22 [8704/10284]	Loss: 0.1368	LR: 0.004000
Training Epoch: 22 [8960/10284]	Loss: 0.1945	LR: 0.004000
Training Epoch: 22 [9216/10284]	Loss: 0.1765	LR: 0.004000
Training Epoch: 22 [9472/10284]	Loss: 0.1971	LR: 0.004000
Training Epoch: 22 [9728/10284]	Loss: 0.1551	LR: 0.004000
Training Epoch: 22 [9984/10284]	Loss: 0.1584	LR: 0.004000
Training Epoch: 22 [10240/10284]	Loss: 0.1486	LR: 0.004000
Training Epoch: 22 [10284/10284]	Loss: 0.1267	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1696, Train Accuracy: 0.9303
Epoch 22 training time consumed: 151.40s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0006, Accuracy: 0.9395, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_13h_06m_12s/ResNet18-MUCAC-seed3-ret75-22-best.pth
Training Epoch: 23 [256/10284]	Loss: 0.1567	LR: 0.004000
Training Epoch: 23 [512/10284]	Loss: 0.1484	LR: 0.004000
Training Epoch: 23 [768/10284]	Loss: 0.1296	LR: 0.004000
Training Epoch: 23 [1024/10284]	Loss: 0.1863	LR: 0.004000
Training Epoch: 23 [1280/10284]	Loss: 0.1542	LR: 0.004000
Training Epoch: 23 [1536/10284]	Loss: 0.1625	LR: 0.004000
Training Epoch: 23 [1792/10284]	Loss: 0.1136	LR: 0.004000
Training Epoch: 23 [2048/10284]	Loss: 0.1966	LR: 0.004000
Training Epoch: 23 [2304/10284]	Loss: 0.1836	LR: 0.004000
Training Epoch: 23 [2560/10284]	Loss: 0.1831	LR: 0.004000
Training Epoch: 23 [2816/10284]	Loss: 0.2245	LR: 0.004000
Training Epoch: 23 [3072/10284]	Loss: 0.1680	LR: 0.004000
Training Epoch: 23 [3328/10284]	Loss: 0.1269	LR: 0.004000
Training Epoch: 23 [3584/10284]	Loss: 0.1590	LR: 0.004000
Training Epoch: 23 [3840/10284]	Loss: 0.1916	LR: 0.004000
Training Epoch: 23 [4096/10284]	Loss: 0.1165	LR: 0.004000
Training Epoch: 23 [4352/10284]	Loss: 0.2113	LR: 0.004000
Training Epoch: 23 [4608/10284]	Loss: 0.1688	LR: 0.004000
Training Epoch: 23 [4864/10284]	Loss: 0.1731	LR: 0.004000
Training Epoch: 23 [5120/10284]	Loss: 0.1634	LR: 0.004000
Training Epoch: 23 [5376/10284]	Loss: 0.1454	LR: 0.004000
Training Epoch: 23 [5632/10284]	Loss: 0.1767	LR: 0.004000
Training Epoch: 23 [5888/10284]	Loss: 0.1593	LR: 0.004000
Training Epoch: 23 [6144/10284]	Loss: 0.1993	LR: 0.004000
Training Epoch: 23 [6400/10284]	Loss: 0.1508	LR: 0.004000
Training Epoch: 23 [6656/10284]	Loss: 0.1901	LR: 0.004000
Training Epoch: 23 [6912/10284]	Loss: 0.1686	LR: 0.004000
Training Epoch: 23 [7168/10284]	Loss: 0.1507	LR: 0.004000
Training Epoch: 23 [7424/10284]	Loss: 0.1264	LR: 0.004000
Training Epoch: 23 [7680/10284]	Loss: 0.1383	LR: 0.004000
Training Epoch: 23 [7936/10284]	Loss: 0.1400	LR: 0.004000
Training Epoch: 23 [8192/10284]	Loss: 0.1431	LR: 0.004000
Training Epoch: 23 [8448/10284]	Loss: 0.1441	LR: 0.004000
Training Epoch: 23 [8704/10284]	Loss: 0.1466	LR: 0.004000
Training Epoch: 23 [8960/10284]	Loss: 0.1535	LR: 0.004000
Training Epoch: 23 [9216/10284]	Loss: 0.2106	LR: 0.004000
Training Epoch: 23 [9472/10284]	Loss: 0.1833	LR: 0.004000
Training Epoch: 23 [9728/10284]	Loss: 0.2102	LR: 0.004000
Training Epoch: 23 [9984/10284]	Loss: 0.1954	LR: 0.004000
Training Epoch: 23 [10240/10284]	Loss: 0.1747	LR: 0.004000
Training Epoch: 23 [10284/10284]	Loss: 0.3110	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1662, Train Accuracy: 0.9297
Epoch 23 training time consumed: 153.01s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0007, Accuracy: 0.9346, Time consumed:8.32s
Training Epoch: 24 [256/10284]	Loss: 0.1837	LR: 0.004000
Training Epoch: 24 [512/10284]	Loss: 0.1481	LR: 0.004000
Training Epoch: 24 [768/10284]	Loss: 0.1215	LR: 0.004000
Training Epoch: 24 [1024/10284]	Loss: 0.1474	LR: 0.004000
Training Epoch: 24 [1280/10284]	Loss: 0.1789	LR: 0.004000
Training Epoch: 24 [1536/10284]	Loss: 0.1672	LR: 0.004000
Training Epoch: 24 [1792/10284]	Loss: 0.1204	LR: 0.004000
Training Epoch: 24 [2048/10284]	Loss: 0.2035	LR: 0.004000
Training Epoch: 24 [2304/10284]	Loss: 0.1434	LR: 0.004000
Training Epoch: 24 [2560/10284]	Loss: 0.1733	LR: 0.004000
Training Epoch: 24 [2816/10284]	Loss: 0.1517	LR: 0.004000
Training Epoch: 24 [3072/10284]	Loss: 0.1922	LR: 0.004000
Training Epoch: 24 [3328/10284]	Loss: 0.1754	LR: 0.004000
Training Epoch: 24 [3584/10284]	Loss: 0.1720	LR: 0.004000
Training Epoch: 24 [3840/10284]	Loss: 0.1305	LR: 0.004000
Training Epoch: 24 [4096/10284]	Loss: 0.1347	LR: 0.004000
Training Epoch: 24 [4352/10284]	Loss: 0.1503	LR: 0.004000
Training Epoch: 24 [4608/10284]	Loss: 0.1380	LR: 0.004000
Training Epoch: 24 [4864/10284]	Loss: 0.1595	LR: 0.004000
Training Epoch: 24 [5120/10284]	Loss: 0.1524	LR: 0.004000
Training Epoch: 24 [5376/10284]	Loss: 0.1611	LR: 0.004000
Training Epoch: 24 [5632/10284]	Loss: 0.1514	LR: 0.004000
Training Epoch: 24 [5888/10284]	Loss: 0.1732	LR: 0.004000
Training Epoch: 24 [6144/10284]	Loss: 0.1677	LR: 0.004000
Training Epoch: 24 [6400/10284]	Loss: 0.1904	LR: 0.004000
Training Epoch: 24 [6656/10284]	Loss: 0.1604	LR: 0.004000
Training Epoch: 24 [6912/10284]	Loss: 0.1558	LR: 0.004000
Training Epoch: 24 [7168/10284]	Loss: 0.1950	LR: 0.004000
Training Epoch: 24 [7424/10284]	Loss: 0.2151	LR: 0.004000
Training Epoch: 24 [7680/10284]	Loss: 0.2133	LR: 0.004000
Training Epoch: 24 [7936/10284]	Loss: 0.1764	LR: 0.004000
Training Epoch: 24 [8192/10284]	Loss: 0.1423	LR: 0.004000
Training Epoch: 24 [8448/10284]	Loss: 0.1675	LR: 0.004000
Training Epoch: 24 [8704/10284]	Loss: 0.1754	LR: 0.004000
Training Epoch: 24 [8960/10284]	Loss: 0.1376	LR: 0.004000
Training Epoch: 24 [9216/10284]	Loss: 0.1943	LR: 0.004000
Training Epoch: 24 [9472/10284]	Loss: 0.1640	LR: 0.004000
Training Epoch: 24 [9728/10284]	Loss: 0.1329	LR: 0.004000
Training Epoch: 24 [9984/10284]	Loss: 0.1838	LR: 0.004000
Training Epoch: 24 [10240/10284]	Loss: 0.1311	LR: 0.004000
Training Epoch: 24 [10284/10284]	Loss: 0.1304	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1632, Train Accuracy: 0.9336
Epoch 24 training time consumed: 152.06s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0006, Accuracy: 0.9390, Time consumed:8.28s
Training Epoch: 25 [256/10284]	Loss: 0.1756	LR: 0.004000
Training Epoch: 25 [512/10284]	Loss: 0.1303	LR: 0.004000
Training Epoch: 25 [768/10284]	Loss: 0.1461	LR: 0.004000
Training Epoch: 25 [1024/10284]	Loss: 0.1564	LR: 0.004000
Training Epoch: 25 [1280/10284]	Loss: 0.1647	LR: 0.004000
Training Epoch: 25 [1536/10284]	Loss: 0.1291	LR: 0.004000
Training Epoch: 25 [1792/10284]	Loss: 0.1653	LR: 0.004000
Training Epoch: 25 [2048/10284]	Loss: 0.1525	LR: 0.004000
Training Epoch: 25 [2304/10284]	Loss: 0.1997	LR: 0.004000
Training Epoch: 25 [2560/10284]	Loss: 0.1665	LR: 0.004000
Training Epoch: 25 [2816/10284]	Loss: 0.1738	LR: 0.004000
Training Epoch: 25 [3072/10284]	Loss: 0.1667	LR: 0.004000
Training Epoch: 25 [3328/10284]	Loss: 0.1837	LR: 0.004000
Training Epoch: 25 [3584/10284]	Loss: 0.1556	LR: 0.004000
Training Epoch: 25 [3840/10284]	Loss: 0.1472	LR: 0.004000
Training Epoch: 25 [4096/10284]	Loss: 0.1426	LR: 0.004000
Training Epoch: 25 [4352/10284]	Loss: 0.1589	LR: 0.004000
Training Epoch: 25 [4608/10284]	Loss: 0.1472	LR: 0.004000
Training Epoch: 25 [4864/10284]	Loss: 0.1905	LR: 0.004000
Training Epoch: 25 [5120/10284]	Loss: 0.1555	LR: 0.004000
Training Epoch: 25 [5376/10284]	Loss: 0.1208	LR: 0.004000
Training Epoch: 25 [5632/10284]	Loss: 0.1458	LR: 0.004000
Training Epoch: 25 [5888/10284]	Loss: 0.1756	LR: 0.004000
Training Epoch: 25 [6144/10284]	Loss: 0.1770	LR: 0.004000
Training Epoch: 25 [6400/10284]	Loss: 0.1182	LR: 0.004000
Training Epoch: 25 [6656/10284]	Loss: 0.1597	LR: 0.004000
Training Epoch: 25 [6912/10284]	Loss: 0.1586	LR: 0.004000
Training Epoch: 25 [7168/10284]	Loss: 0.2245	LR: 0.004000
Training Epoch: 25 [7424/10284]	Loss: 0.1708	LR: 0.004000
Training Epoch: 25 [7680/10284]	Loss: 0.1635	LR: 0.004000
Training Epoch: 25 [7936/10284]	Loss: 0.1834	LR: 0.004000
Training Epoch: 25 [8192/10284]	Loss: 0.1572	LR: 0.004000
Training Epoch: 25 [8448/10284]	Loss: 0.1846	LR: 0.004000
Training Epoch: 25 [8704/10284]	Loss: 0.1069	LR: 0.004000
Training Epoch: 25 [8960/10284]	Loss: 0.1343	LR: 0.004000
Training Epoch: 25 [9216/10284]	Loss: 0.1394	LR: 0.004000
Training Epoch: 25 [9472/10284]	Loss: 0.1608	LR: 0.004000
Training Epoch: 25 [9728/10284]	Loss: 0.1395	LR: 0.004000
Training Epoch: 25 [9984/10284]	Loss: 0.1655	LR: 0.004000
Training Epoch: 25 [10240/10284]	Loss: 0.1601	LR: 0.004000
Training Epoch: 25 [10284/10284]	Loss: 0.3444	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1597, Train Accuracy: 0.9343
Epoch 25 training time consumed: 151.23s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0007, Accuracy: 0.9327, Time consumed:8.31s
Training Epoch: 26 [256/10284]	Loss: 0.1287	LR: 0.004000
Training Epoch: 26 [512/10284]	Loss: 0.1469	LR: 0.004000
Training Epoch: 26 [768/10284]	Loss: 0.1950	LR: 0.004000
Training Epoch: 26 [1024/10284]	Loss: 0.2129	LR: 0.004000
Training Epoch: 26 [1280/10284]	Loss: 0.1227	LR: 0.004000
Training Epoch: 26 [1536/10284]	Loss: 0.1881	LR: 0.004000
Training Epoch: 26 [1792/10284]	Loss: 0.2218	LR: 0.004000
Training Epoch: 26 [2048/10284]	Loss: 0.1632	LR: 0.004000
Training Epoch: 26 [2304/10284]	Loss: 0.2118	LR: 0.004000
Training Epoch: 26 [2560/10284]	Loss: 0.1399	LR: 0.004000
Training Epoch: 26 [2816/10284]	Loss: 0.1553	LR: 0.004000
Training Epoch: 26 [3072/10284]	Loss: 0.1723	LR: 0.004000
Training Epoch: 26 [3328/10284]	Loss: 0.1523	LR: 0.004000
Training Epoch: 26 [3584/10284]	Loss: 0.1670	LR: 0.004000
Training Epoch: 26 [3840/10284]	Loss: 0.1631	LR: 0.004000
Training Epoch: 26 [4096/10284]	Loss: 0.1162	LR: 0.004000
Training Epoch: 26 [4352/10284]	Loss: 0.1671	LR: 0.004000
Training Epoch: 26 [4608/10284]	Loss: 0.1986	LR: 0.004000
Training Epoch: 26 [4864/10284]	Loss: 0.1551	LR: 0.004000
Training Epoch: 26 [5120/10284]	Loss: 0.1912	LR: 0.004000
Training Epoch: 26 [5376/10284]	Loss: 0.1268	LR: 0.004000
Training Epoch: 26 [5632/10284]	Loss: 0.2359	LR: 0.004000
Training Epoch: 26 [5888/10284]	Loss: 0.1391	LR: 0.004000
Training Epoch: 26 [6144/10284]	Loss: 0.1862	LR: 0.004000
Training Epoch: 26 [6400/10284]	Loss: 0.1970	LR: 0.004000
Training Epoch: 26 [6656/10284]	Loss: 0.1235	LR: 0.004000
Training Epoch: 26 [6912/10284]	Loss: 0.1157	LR: 0.004000
Training Epoch: 26 [7168/10284]	Loss: 0.1311	LR: 0.004000
Training Epoch: 26 [7424/10284]	Loss: 0.1183	LR: 0.004000
Training Epoch: 26 [7680/10284]	Loss: 0.1410	LR: 0.004000
Training Epoch: 26 [7936/10284]	Loss: 0.1707	LR: 0.004000
Training Epoch: 26 [8192/10284]	Loss: 0.1625	LR: 0.004000
Training Epoch: 26 [8448/10284]	Loss: 0.1424	LR: 0.004000
Training Epoch: 26 [8704/10284]	Loss: 0.2197	LR: 0.004000
Training Epoch: 26 [8960/10284]	Loss: 0.1898	LR: 0.004000
Training Epoch: 26 [9216/10284]	Loss: 0.1696	LR: 0.004000
Training Epoch: 26 [9472/10284]	Loss: 0.1962	LR: 0.004000
Training Epoch: 26 [9728/10284]	Loss: 0.1376	LR: 0.004000
Training Epoch: 26 [9984/10284]	Loss: 0.2055	LR: 0.004000
Training Epoch: 26 [10240/10284]	Loss: 0.2010	LR: 0.004000
Training Epoch: 26 [10284/10284]	Loss: 0.1484	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1669, Train Accuracy: 0.9308
Epoch 26 training time consumed: 151.07s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9356, Time consumed:8.28s
Training Epoch: 27 [256/10284]	Loss: 0.1767	LR: 0.004000
Training Epoch: 27 [512/10284]	Loss: 0.1496	LR: 0.004000
Training Epoch: 27 [768/10284]	Loss: 0.0920	LR: 0.004000
Training Epoch: 27 [1024/10284]	Loss: 0.1361	LR: 0.004000
Training Epoch: 27 [1280/10284]	Loss: 0.1801	LR: 0.004000
Training Epoch: 27 [1536/10284]	Loss: 0.1513	LR: 0.004000
Training Epoch: 27 [1792/10284]	Loss: 0.1535	LR: 0.004000
Training Epoch: 27 [2048/10284]	Loss: 0.2176	LR: 0.004000
Training Epoch: 27 [2304/10284]	Loss: 0.1458	LR: 0.004000
Training Epoch: 27 [2560/10284]	Loss: 0.1943	LR: 0.004000
Training Epoch: 27 [2816/10284]	Loss: 0.1732	LR: 0.004000
Training Epoch: 27 [3072/10284]	Loss: 0.1579	LR: 0.004000
Training Epoch: 27 [3328/10284]	Loss: 0.1368	LR: 0.004000
Training Epoch: 27 [3584/10284]	Loss: 0.1820	LR: 0.004000
Training Epoch: 27 [3840/10284]	Loss: 0.1954	LR: 0.004000
Training Epoch: 27 [4096/10284]	Loss: 0.1324	LR: 0.004000
Training Epoch: 27 [4352/10284]	Loss: 0.1423	LR: 0.004000
Training Epoch: 27 [4608/10284]	Loss: 0.1740	LR: 0.004000
Training Epoch: 27 [4864/10284]	Loss: 0.1650	LR: 0.004000
Training Epoch: 27 [5120/10284]	Loss: 0.1193	LR: 0.004000
Training Epoch: 27 [5376/10284]	Loss: 0.1450	LR: 0.004000
Training Epoch: 27 [5632/10284]	Loss: 0.1377	LR: 0.004000
Training Epoch: 27 [5888/10284]	Loss: 0.1843	LR: 0.004000
Training Epoch: 27 [6144/10284]	Loss: 0.1392	LR: 0.004000
Training Epoch: 27 [6400/10284]	Loss: 0.1760	LR: 0.004000
Training Epoch: 27 [6656/10284]	Loss: 0.1612	LR: 0.004000
Training Epoch: 27 [6912/10284]	Loss: 0.1497	LR: 0.004000
Training Epoch: 27 [7168/10284]	Loss: 0.1709	LR: 0.004000
Training Epoch: 27 [7424/10284]	Loss: 0.1864	LR: 0.004000
Training Epoch: 27 [7680/10284]	Loss: 0.2189	LR: 0.004000
Training Epoch: 27 [7936/10284]	Loss: 0.1759	LR: 0.004000
Training Epoch: 27 [8192/10284]	Loss: 0.1567	LR: 0.004000
Training Epoch: 27 [8448/10284]	Loss: 0.1843	LR: 0.004000
Training Epoch: 27 [8704/10284]	Loss: 0.1269	LR: 0.004000
Training Epoch: 27 [8960/10284]	Loss: 0.1745	LR: 0.004000
Training Epoch: 27 [9216/10284]	Loss: 0.1591	LR: 0.004000
Training Epoch: 27 [9472/10284]	Loss: 0.1213	LR: 0.004000
Training Epoch: 27 [9728/10284]	Loss: 0.1537	LR: 0.004000
Training Epoch: 27 [9984/10284]	Loss: 0.1387	LR: 0.004000
Training Epoch: 27 [10240/10284]	Loss: 0.1070	LR: 0.004000
Training Epoch: 27 [10284/10284]	Loss: 0.2000	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1587, Train Accuracy: 0.9340
Epoch 27 training time consumed: 149.27s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9366, Time consumed:8.19s
Training Epoch: 28 [256/10284]	Loss: 0.1588	LR: 0.004000
Training Epoch: 28 [512/10284]	Loss: 0.2085	LR: 0.004000
Training Epoch: 28 [768/10284]	Loss: 0.1227	LR: 0.004000
Training Epoch: 28 [1024/10284]	Loss: 0.2020	LR: 0.004000
Training Epoch: 28 [1280/10284]	Loss: 0.1447	LR: 0.004000
Training Epoch: 28 [1536/10284]	Loss: 0.1323	LR: 0.004000
Training Epoch: 28 [1792/10284]	Loss: 0.1600	LR: 0.004000
Training Epoch: 28 [2048/10284]	Loss: 0.1642	LR: 0.004000
Training Epoch: 28 [2304/10284]	Loss: 0.1332	LR: 0.004000
Training Epoch: 28 [2560/10284]	Loss: 0.0985	LR: 0.004000
Training Epoch: 28 [2816/10284]	Loss: 0.1414	LR: 0.004000
Training Epoch: 28 [3072/10284]	Loss: 0.1482	LR: 0.004000
Training Epoch: 28 [3328/10284]	Loss: 0.1457	LR: 0.004000
Training Epoch: 28 [3584/10284]	Loss: 0.1369	LR: 0.004000
Training Epoch: 28 [3840/10284]	Loss: 0.1878	LR: 0.004000
Training Epoch: 28 [4096/10284]	Loss: 0.1900	LR: 0.004000
Training Epoch: 28 [4352/10284]	Loss: 0.1581	LR: 0.004000
Training Epoch: 28 [4608/10284]	Loss: 0.1675	LR: 0.004000
Training Epoch: 28 [4864/10284]	Loss: 0.1700	LR: 0.004000
Training Epoch: 28 [5120/10284]	Loss: 0.1382	LR: 0.004000
Training Epoch: 28 [5376/10284]	Loss: 0.1388	LR: 0.004000
Training Epoch: 28 [5632/10284]	Loss: 0.1703	LR: 0.004000
Training Epoch: 28 [5888/10284]	Loss: 0.1414	LR: 0.004000
Training Epoch: 28 [6144/10284]	Loss: 0.1731	LR: 0.004000
Training Epoch: 28 [6400/10284]	Loss: 0.1390	LR: 0.004000
Training Epoch: 28 [6656/10284]	Loss: 0.1314	LR: 0.004000
Training Epoch: 28 [6912/10284]	Loss: 0.1444	LR: 0.004000
Training Epoch: 28 [7168/10284]	Loss: 0.1693	LR: 0.004000
Training Epoch: 28 [7424/10284]	Loss: 0.1861	LR: 0.004000
Training Epoch: 28 [7680/10284]	Loss: 0.2100	LR: 0.004000
Training Epoch: 28 [7936/10284]	Loss: 0.1657	LR: 0.004000
Training Epoch: 28 [8192/10284]	Loss: 0.1834	LR: 0.004000
Training Epoch: 28 [8448/10284]	Loss: 0.1829	LR: 0.004000
Training Epoch: 28 [8704/10284]	Loss: 0.1203	LR: 0.004000
Training Epoch: 28 [8960/10284]	Loss: 0.1403	LR: 0.004000
Training Epoch: 28 [9216/10284]	Loss: 0.1245	LR: 0.004000
Training Epoch: 28 [9472/10284]	Loss: 0.1729	LR: 0.004000
Training Epoch: 28 [9728/10284]	Loss: 0.1575	LR: 0.004000
Training Epoch: 28 [9984/10284]	Loss: 0.1450	LR: 0.004000
Training Epoch: 28 [10240/10284]	Loss: 0.1542	LR: 0.004000
Training Epoch: 28 [10284/10284]	Loss: 0.2286	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1568, Train Accuracy: 0.9345
Epoch 28 training time consumed: 148.87s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0006, Accuracy: 0.9361, Time consumed:8.09s
Training Epoch: 29 [256/10284]	Loss: 0.1663	LR: 0.004000
Training Epoch: 29 [512/10284]	Loss: 0.1249	LR: 0.004000
Training Epoch: 29 [768/10284]	Loss: 0.1138	LR: 0.004000
Training Epoch: 29 [1024/10284]	Loss: 0.1323	LR: 0.004000
Training Epoch: 29 [1280/10284]	Loss: 0.1837	LR: 0.004000
Training Epoch: 29 [1536/10284]	Loss: 0.1926	LR: 0.004000
Training Epoch: 29 [1792/10284]	Loss: 0.1448	LR: 0.004000
Training Epoch: 29 [2048/10284]	Loss: 0.0831	LR: 0.004000
Training Epoch: 29 [2304/10284]	Loss: 0.1629	LR: 0.004000
Training Epoch: 29 [2560/10284]	Loss: 0.1565	LR: 0.004000
Training Epoch: 29 [2816/10284]	Loss: 0.1599	LR: 0.004000
Training Epoch: 29 [3072/10284]	Loss: 0.1407	LR: 0.004000
Training Epoch: 29 [3328/10284]	Loss: 0.1581	LR: 0.004000
Training Epoch: 29 [3584/10284]	Loss: 0.0967	LR: 0.004000
Training Epoch: 29 [3840/10284]	Loss: 0.2146	LR: 0.004000
Training Epoch: 29 [4096/10284]	Loss: 0.1369	LR: 0.004000
Training Epoch: 29 [4352/10284]	Loss: 0.1073	LR: 0.004000
Training Epoch: 29 [4608/10284]	Loss: 0.1303	LR: 0.004000
Training Epoch: 29 [4864/10284]	Loss: 0.1419	LR: 0.004000
Training Epoch: 29 [5120/10284]	Loss: 0.1431	LR: 0.004000
Training Epoch: 29 [5376/10284]	Loss: 0.1335	LR: 0.004000
Training Epoch: 29 [5632/10284]	Loss: 0.2185	LR: 0.004000
Training Epoch: 29 [5888/10284]	Loss: 0.1147	LR: 0.004000
Training Epoch: 29 [6144/10284]	Loss: 0.1420	LR: 0.004000
Training Epoch: 29 [6400/10284]	Loss: 0.1697	LR: 0.004000
Training Epoch: 29 [6656/10284]	Loss: 0.1305	LR: 0.004000
Training Epoch: 29 [6912/10284]	Loss: 0.1260	LR: 0.004000
Training Epoch: 29 [7168/10284]	Loss: 0.1805	LR: 0.004000
Training Epoch: 29 [7424/10284]	Loss: 0.1704	LR: 0.004000
Training Epoch: 29 [7680/10284]	Loss: 0.1395	LR: 0.004000
Training Epoch: 29 [7936/10284]	Loss: 0.1064	LR: 0.004000
Training Epoch: 29 [8192/10284]	Loss: 0.1270	LR: 0.004000
Training Epoch: 29 [8448/10284]	Loss: 0.1822	LR: 0.004000
Training Epoch: 29 [8704/10284]	Loss: 0.1649	LR: 0.004000
Training Epoch: 29 [8960/10284]	Loss: 0.1480	LR: 0.004000
Training Epoch: 29 [9216/10284]	Loss: 0.1562	LR: 0.004000
Training Epoch: 29 [9472/10284]	Loss: 0.1416	LR: 0.004000
Training Epoch: 29 [9728/10284]	Loss: 0.1529	LR: 0.004000
Training Epoch: 29 [9984/10284]	Loss: 0.1613	LR: 0.004000
Training Epoch: 29 [10240/10284]	Loss: 0.1567	LR: 0.004000
Training Epoch: 29 [10284/10284]	Loss: 0.0853	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1476, Train Accuracy: 0.9388
Epoch 29 training time consumed: 148.75s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0009, Accuracy: 0.9259, Time consumed:8.19s
Training Epoch: 30 [256/10284]	Loss: 0.1433	LR: 0.004000
Training Epoch: 30 [512/10284]	Loss: 0.1209	LR: 0.004000
Training Epoch: 30 [768/10284]	Loss: 0.1433	LR: 0.004000
Training Epoch: 30 [1024/10284]	Loss: 0.1682	LR: 0.004000
Training Epoch: 30 [1280/10284]	Loss: 0.0991	LR: 0.004000
Training Epoch: 30 [1536/10284]	Loss: 0.1835	LR: 0.004000
Training Epoch: 30 [1792/10284]	Loss: 0.1733	LR: 0.004000
Training Epoch: 30 [2048/10284]	Loss: 0.1387	LR: 0.004000
Training Epoch: 30 [2304/10284]	Loss: 0.1366	LR: 0.004000
Training Epoch: 30 [2560/10284]	Loss: 0.0967	LR: 0.004000
Training Epoch: 30 [2816/10284]	Loss: 0.1734	LR: 0.004000
Training Epoch: 30 [3072/10284]	Loss: 0.1901	LR: 0.004000
Training Epoch: 30 [3328/10284]	Loss: 0.1410	LR: 0.004000
Training Epoch: 30 [3584/10284]	Loss: 0.1660	LR: 0.004000
Training Epoch: 30 [3840/10284]	Loss: 0.1669	LR: 0.004000
Training Epoch: 30 [4096/10284]	Loss: 0.1779	LR: 0.004000
Training Epoch: 30 [4352/10284]	Loss: 0.1840	LR: 0.004000
Training Epoch: 30 [4608/10284]	Loss: 0.2035	LR: 0.004000
Training Epoch: 30 [4864/10284]	Loss: 0.1709	LR: 0.004000
Training Epoch: 30 [5120/10284]	Loss: 0.1552	LR: 0.004000
Training Epoch: 30 [5376/10284]	Loss: 0.1570	LR: 0.004000
Training Epoch: 30 [5632/10284]	Loss: 0.0992	LR: 0.004000
Training Epoch: 30 [5888/10284]	Loss: 0.1366	LR: 0.004000
Training Epoch: 30 [6144/10284]	Loss: 0.1104	LR: 0.004000
Training Epoch: 30 [6400/10284]	Loss: 0.1556	LR: 0.004000
Training Epoch: 30 [6656/10284]	Loss: 0.1712	LR: 0.004000
Training Epoch: 30 [6912/10284]	Loss: 0.1476	LR: 0.004000
Training Epoch: 30 [7168/10284]	Loss: 0.1341	LR: 0.004000
Training Epoch: 30 [7424/10284]	Loss: 0.1030	LR: 0.004000
Training Epoch: 30 [7680/10284]	Loss: 0.1278	LR: 0.004000
Training Epoch: 30 [7936/10284]	Loss: 0.1237	LR: 0.004000
Training Epoch: 30 [8192/10284]	Loss: 0.1135	LR: 0.004000
Training Epoch: 30 [8448/10284]	Loss: 0.1215	LR: 0.004000
Training Epoch: 30 [8704/10284]	Loss: 0.1131	LR: 0.004000
Training Epoch: 30 [8960/10284]	Loss: 0.1797	LR: 0.004000
Training Epoch: 30 [9216/10284]	Loss: 0.1507	LR: 0.004000
Training Epoch: 30 [9472/10284]	Loss: 0.1321	LR: 0.004000
Training Epoch: 30 [9728/10284]	Loss: 0.1616	LR: 0.004000
Training Epoch: 30 [9984/10284]	Loss: 0.1550	LR: 0.004000
Training Epoch: 30 [10240/10284]	Loss: 0.0917	LR: 0.004000
Training Epoch: 30 [10284/10284]	Loss: 0.1552	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1455, Train Accuracy: 0.9381
Epoch 30 training time consumed: 149.01s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9327, Time consumed:8.00s
Training Epoch: 31 [256/10284]	Loss: 0.2012	LR: 0.004000
Training Epoch: 31 [512/10284]	Loss: 0.1630	LR: 0.004000
Training Epoch: 31 [768/10284]	Loss: 0.0899	LR: 0.004000
Training Epoch: 31 [1024/10284]	Loss: 0.1390	LR: 0.004000
Training Epoch: 31 [1280/10284]	Loss: 0.1509	LR: 0.004000
Training Epoch: 31 [1536/10284]	Loss: 0.1118	LR: 0.004000
Training Epoch: 31 [1792/10284]	Loss: 0.1229	LR: 0.004000
Training Epoch: 31 [2048/10284]	Loss: 0.1494	LR: 0.004000
Training Epoch: 31 [2304/10284]	Loss: 0.1480	LR: 0.004000
Training Epoch: 31 [2560/10284]	Loss: 0.1511	LR: 0.004000
Training Epoch: 31 [2816/10284]	Loss: 0.1673	LR: 0.004000
Training Epoch: 31 [3072/10284]	Loss: 0.1521	LR: 0.004000
Training Epoch: 31 [3328/10284]	Loss: 0.0998	LR: 0.004000
Training Epoch: 31 [3584/10284]	Loss: 0.1247	LR: 0.004000
Training Epoch: 31 [3840/10284]	Loss: 0.1512	LR: 0.004000
Training Epoch: 31 [4096/10284]	Loss: 0.1376	LR: 0.004000
Training Epoch: 31 [4352/10284]	Loss: 0.1380	LR: 0.004000
Training Epoch: 31 [4608/10284]	Loss: 0.1403	LR: 0.004000
Training Epoch: 31 [4864/10284]	Loss: 0.2123	LR: 0.004000
Training Epoch: 31 [5120/10284]	Loss: 0.1665	LR: 0.004000
Training Epoch: 31 [5376/10284]	Loss: 0.1773	LR: 0.004000
Training Epoch: 31 [5632/10284]	Loss: 0.1267	LR: 0.004000
Training Epoch: 31 [5888/10284]	Loss: 0.1624	LR: 0.004000
Training Epoch: 31 [6144/10284]	Loss: 0.1530	LR: 0.004000
Training Epoch: 31 [6400/10284]	Loss: 0.1112	LR: 0.004000
Training Epoch: 31 [6656/10284]	Loss: 0.1240	LR: 0.004000
Training Epoch: 31 [6912/10284]	Loss: 0.1371	LR: 0.004000
Training Epoch: 31 [7168/10284]	Loss: 0.1373	LR: 0.004000
Training Epoch: 31 [7424/10284]	Loss: 0.1361	LR: 0.004000
Training Epoch: 31 [7680/10284]	Loss: 0.1755	LR: 0.004000
Training Epoch: 31 [7936/10284]	Loss: 0.1157	LR: 0.004000
Training Epoch: 31 [8192/10284]	Loss: 0.1693	LR: 0.004000
Training Epoch: 31 [8448/10284]	Loss: 0.1098	LR: 0.004000
Training Epoch: 31 [8704/10284]	Loss: 0.1116	LR: 0.004000
Training Epoch: 31 [8960/10284]	Loss: 0.1286	LR: 0.004000
Training Epoch: 31 [9216/10284]	Loss: 0.1241	LR: 0.004000
Training Epoch: 31 [9472/10284]	Loss: 0.1769	LR: 0.004000
Training Epoch: 31 [9728/10284]	Loss: 0.1793	LR: 0.004000
Training Epoch: 31 [9984/10284]	Loss: 0.1438	LR: 0.004000
Training Epoch: 31 [10240/10284]	Loss: 0.0900	LR: 0.004000
Training Epoch: 31 [10284/10284]	Loss: 0.1315	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1426, Train Accuracy: 0.9400
Epoch 31 training time consumed: 150.70s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0013, Accuracy: 0.8925, Time consumed:8.00s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  10284
Forget Train Dl:  264
Retain Valid Dl:  10284
Forget Valid Dl:  264
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 264 samples
Set1 Distribution: 264 samples
Set2 Distribution: 264 samples
Set1 Distribution: 264 samples
Set2 Distribution: 264 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 89.14419555664062
Retain Accuracy: 88.41896057128906
Zero-Retain Forget (ZRF): 0.685638427734375
Membership Inference Attack (MIA): 0.3181818181818182
Forget vs Retain Membership Inference Attack (MIA): 0.5377358490566038
Forget vs Test Membership Inference Attack (MIA): 0.4716981132075472
Test vs Retain Membership Inference Attack (MIA): 0.5108958837772397
Train vs Test Membership Inference Attack (MIA): 0.5532687651331719
Forget Set Accuracy (Df): 87.6953125
Method Execution Time: 6085.01 seconds
