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

📌 S Retain class distribution for seed 2:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 2:
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: 0.6998	LR: 0.000000
Training Epoch: 1 [512/10284]	Loss: 0.6880	LR: 0.002439
Training Epoch: 1 [768/10284]	Loss: 0.6964	LR: 0.004878
Training Epoch: 1 [1024/10284]	Loss: 0.6873	LR: 0.007317
Training Epoch: 1 [1280/10284]	Loss: 0.7120	LR: 0.009756
Training Epoch: 1 [1536/10284]	Loss: 0.6859	LR: 0.012195
Training Epoch: 1 [1792/10284]	Loss: 0.7139	LR: 0.014634
Training Epoch: 1 [2048/10284]	Loss: 0.6821	LR: 0.017073
Training Epoch: 1 [2304/10284]	Loss: 0.7829	LR: 0.019512
Training Epoch: 1 [2560/10284]	Loss: 0.8736	LR: 0.021951
Training Epoch: 1 [2816/10284]	Loss: 0.6773	LR: 0.024390
Training Epoch: 1 [3072/10284]	Loss: 0.8305	LR: 0.026829
Training Epoch: 1 [3328/10284]	Loss: 1.0358	LR: 0.029268
Training Epoch: 1 [3584/10284]	Loss: 1.0650	LR: 0.031707
Training Epoch: 1 [3840/10284]	Loss: 1.0153	LR: 0.034146
Training Epoch: 1 [4096/10284]	Loss: 0.7798	LR: 0.036585
Training Epoch: 1 [4352/10284]	Loss: 0.7243	LR: 0.039024
Training Epoch: 1 [4608/10284]	Loss: 0.9681	LR: 0.041463
Training Epoch: 1 [4864/10284]	Loss: 0.9044	LR: 0.043902
Training Epoch: 1 [5120/10284]	Loss: 0.7233	LR: 0.046341
Training Epoch: 1 [5376/10284]	Loss: 0.7414	LR: 0.048780
Training Epoch: 1 [5632/10284]	Loss: 0.7208	LR: 0.051220
Training Epoch: 1 [5888/10284]	Loss: 0.7166	LR: 0.053659
Training Epoch: 1 [6144/10284]	Loss: 0.6907	LR: 0.056098
Training Epoch: 1 [6400/10284]	Loss: 0.7112	LR: 0.058537
Training Epoch: 1 [6656/10284]	Loss: 0.6586	LR: 0.060976
Training Epoch: 1 [6912/10284]	Loss: 0.8089	LR: 0.063415
Training Epoch: 1 [7168/10284]	Loss: 0.6926	LR: 0.065854
Training Epoch: 1 [7424/10284]	Loss: 0.8184	LR: 0.068293
Training Epoch: 1 [7680/10284]	Loss: 0.6836	LR: 0.070732
Training Epoch: 1 [7936/10284]	Loss: 0.8599	LR: 0.073171
Training Epoch: 1 [8192/10284]	Loss: 0.7575	LR: 0.075610
Training Epoch: 1 [8448/10284]	Loss: 0.7512	LR: 0.078049
Training Epoch: 1 [8704/10284]	Loss: 0.7762	LR: 0.080488
Training Epoch: 1 [8960/10284]	Loss: 0.6932	LR: 0.082927
Training Epoch: 1 [9216/10284]	Loss: 0.7265	LR: 0.085366
Training Epoch: 1 [9472/10284]	Loss: 0.7434	LR: 0.087805
Training Epoch: 1 [9728/10284]	Loss: 0.7945	LR: 0.090244
Training Epoch: 1 [9984/10284]	Loss: 0.7305	LR: 0.092683
Training Epoch: 1 [10240/10284]	Loss: 0.7709	LR: 0.095122
Training Epoch: 1 [10284/10284]	Loss: 0.6724	LR: 0.097561
Epoch 1 - Average Train Loss: 0.7694, Train Accuracy: 0.5249
Epoch 1 training time consumed: 321.35s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0048, Accuracy: 0.4450, Time consumed:7.87s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-1-best.pth
Training Epoch: 2 [256/10284]	Loss: 0.7620	LR: 0.100000
Training Epoch: 2 [512/10284]	Loss: 0.7709	LR: 0.100000
Training Epoch: 2 [768/10284]	Loss: 0.7082	LR: 0.100000
Training Epoch: 2 [1024/10284]	Loss: 0.7355	LR: 0.100000
Training Epoch: 2 [1280/10284]	Loss: 0.6813	LR: 0.100000
Training Epoch: 2 [1536/10284]	Loss: 0.7095	LR: 0.100000
Training Epoch: 2 [1792/10284]	Loss: 0.7513	LR: 0.100000
Training Epoch: 2 [2048/10284]	Loss: 0.7387	LR: 0.100000
Training Epoch: 2 [2304/10284]	Loss: 0.7236	LR: 0.100000
Training Epoch: 2 [2560/10284]	Loss: 0.7730	LR: 0.100000
Training Epoch: 2 [2816/10284]	Loss: 0.7359	LR: 0.100000
Training Epoch: 2 [3072/10284]	Loss: 0.6924	LR: 0.100000
Training Epoch: 2 [3328/10284]	Loss: 0.7307	LR: 0.100000
Training Epoch: 2 [3584/10284]	Loss: 0.7625	LR: 0.100000
Training Epoch: 2 [3840/10284]	Loss: 0.7350	LR: 0.100000
Training Epoch: 2 [4096/10284]	Loss: 0.7091	LR: 0.100000
Training Epoch: 2 [4352/10284]	Loss: 0.7020	LR: 0.100000
Training Epoch: 2 [4608/10284]	Loss: 0.6998	LR: 0.100000
Training Epoch: 2 [4864/10284]	Loss: 0.7211	LR: 0.100000
Training Epoch: 2 [5120/10284]	Loss: 0.7009	LR: 0.100000
Training Epoch: 2 [5376/10284]	Loss: 0.6897	LR: 0.100000
Training Epoch: 2 [5632/10284]	Loss: 0.7156	LR: 0.100000
Training Epoch: 2 [5888/10284]	Loss: 0.7284	LR: 0.100000
Training Epoch: 2 [6144/10284]	Loss: 0.6794	LR: 0.100000
Training Epoch: 2 [6400/10284]	Loss: 0.6785	LR: 0.100000
Training Epoch: 2 [6656/10284]	Loss: 0.6860	LR: 0.100000
Training Epoch: 2 [6912/10284]	Loss: 0.7122	LR: 0.100000
Training Epoch: 2 [7168/10284]	Loss: 0.6951	LR: 0.100000
Training Epoch: 2 [7424/10284]	Loss: 0.6981	LR: 0.100000
Training Epoch: 2 [7680/10284]	Loss: 0.6784	LR: 0.100000
Training Epoch: 2 [7936/10284]	Loss: 0.6432	LR: 0.100000
Training Epoch: 2 [8192/10284]	Loss: 0.6879	LR: 0.100000
Training Epoch: 2 [8448/10284]	Loss: 0.7032	LR: 0.100000
Training Epoch: 2 [8704/10284]	Loss: 0.6955	LR: 0.100000
Training Epoch: 2 [8960/10284]	Loss: 0.6744	LR: 0.100000
Training Epoch: 2 [9216/10284]	Loss: 0.6769	LR: 0.100000
Training Epoch: 2 [9472/10284]	Loss: 0.6711	LR: 0.100000
Training Epoch: 2 [9728/10284]	Loss: 0.6924	LR: 0.100000
Training Epoch: 2 [9984/10284]	Loss: 0.6775	LR: 0.100000
Training Epoch: 2 [10240/10284]	Loss: 0.6959	LR: 0.100000
Training Epoch: 2 [10284/10284]	Loss: 0.6440	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7078, Train Accuracy: 0.5475
Epoch 2 training time consumed: 148.10s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0032, Accuracy: 0.5327, Time consumed:7.85s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-2-best.pth
Training Epoch: 3 [256/10284]	Loss: 0.6861	LR: 0.100000
Training Epoch: 3 [512/10284]	Loss: 0.6556	LR: 0.100000
Training Epoch: 3 [768/10284]	Loss: 0.6620	LR: 0.100000
Training Epoch: 3 [1024/10284]	Loss: 0.6725	LR: 0.100000
Training Epoch: 3 [1280/10284]	Loss: 0.6754	LR: 0.100000
Training Epoch: 3 [1536/10284]	Loss: 0.7404	LR: 0.100000
Training Epoch: 3 [1792/10284]	Loss: 0.7039	LR: 0.100000
Training Epoch: 3 [2048/10284]	Loss: 0.7031	LR: 0.100000
Training Epoch: 3 [2304/10284]	Loss: 0.6744	LR: 0.100000
Training Epoch: 3 [2560/10284]	Loss: 0.6848	LR: 0.100000
Training Epoch: 3 [2816/10284]	Loss: 0.6832	LR: 0.100000
Training Epoch: 3 [3072/10284]	Loss: 0.6914	LR: 0.100000
Training Epoch: 3 [3328/10284]	Loss: 0.6746	LR: 0.100000
Training Epoch: 3 [3584/10284]	Loss: 0.6876	LR: 0.100000
Training Epoch: 3 [3840/10284]	Loss: 0.6896	LR: 0.100000
Training Epoch: 3 [4096/10284]	Loss: 0.6961	LR: 0.100000
Training Epoch: 3 [4352/10284]	Loss: 0.6972	LR: 0.100000
Training Epoch: 3 [4608/10284]	Loss: 0.7174	LR: 0.100000
Training Epoch: 3 [4864/10284]	Loss: 0.6813	LR: 0.100000
Training Epoch: 3 [5120/10284]	Loss: 0.6784	LR: 0.100000
Training Epoch: 3 [5376/10284]	Loss: 0.6922	LR: 0.100000
Training Epoch: 3 [5632/10284]	Loss: 0.6889	LR: 0.100000
Training Epoch: 3 [5888/10284]	Loss: 0.7018	LR: 0.100000
Training Epoch: 3 [6144/10284]	Loss: 0.6986	LR: 0.100000
Training Epoch: 3 [6400/10284]	Loss: 0.6959	LR: 0.100000
Training Epoch: 3 [6656/10284]	Loss: 0.6851	LR: 0.100000
Training Epoch: 3 [6912/10284]	Loss: 0.6880	LR: 0.100000
Training Epoch: 3 [7168/10284]	Loss: 0.6798	LR: 0.100000
Training Epoch: 3 [7424/10284]	Loss: 0.6879	LR: 0.100000
Training Epoch: 3 [7680/10284]	Loss: 0.6618	LR: 0.100000
Training Epoch: 3 [7936/10284]	Loss: 0.6714	LR: 0.100000
Training Epoch: 3 [8192/10284]	Loss: 0.6801	LR: 0.100000
Training Epoch: 3 [8448/10284]	Loss: 0.6620	LR: 0.100000
Training Epoch: 3 [8704/10284]	Loss: 0.6844	LR: 0.100000
Training Epoch: 3 [8960/10284]	Loss: 0.6895	LR: 0.100000
Training Epoch: 3 [9216/10284]	Loss: 0.6913	LR: 0.100000
Training Epoch: 3 [9472/10284]	Loss: 0.7017	LR: 0.100000
Training Epoch: 3 [9728/10284]	Loss: 0.6818	LR: 0.100000
Training Epoch: 3 [9984/10284]	Loss: 0.6622	LR: 0.100000
Training Epoch: 3 [10240/10284]	Loss: 0.6589	LR: 0.100000
Training Epoch: 3 [10284/10284]	Loss: 0.7180	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6856, Train Accuracy: 0.5552
Epoch 3 training time consumed: 148.43s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5768, Time consumed:7.85s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-3-best.pth
Training Epoch: 4 [256/10284]	Loss: 0.6727	LR: 0.100000
Training Epoch: 4 [512/10284]	Loss: 0.6942	LR: 0.100000
Training Epoch: 4 [768/10284]	Loss: 0.6724	LR: 0.100000
Training Epoch: 4 [1024/10284]	Loss: 0.6992	LR: 0.100000
Training Epoch: 4 [1280/10284]	Loss: 0.6961	LR: 0.100000
Training Epoch: 4 [1536/10284]	Loss: 0.6740	LR: 0.100000
Training Epoch: 4 [1792/10284]	Loss: 0.6935	LR: 0.100000
Training Epoch: 4 [2048/10284]	Loss: 0.6939	LR: 0.100000
Training Epoch: 4 [2304/10284]	Loss: 0.6747	LR: 0.100000
Training Epoch: 4 [2560/10284]	Loss: 0.6987	LR: 0.100000
Training Epoch: 4 [2816/10284]	Loss: 0.6678	LR: 0.100000
Training Epoch: 4 [3072/10284]	Loss: 0.6822	LR: 0.100000
Training Epoch: 4 [3328/10284]	Loss: 0.6808	LR: 0.100000
Training Epoch: 4 [3584/10284]	Loss: 0.6896	LR: 0.100000
Training Epoch: 4 [3840/10284]	Loss: 0.6553	LR: 0.100000
Training Epoch: 4 [4096/10284]	Loss: 0.6614	LR: 0.100000
Training Epoch: 4 [4352/10284]	Loss: 0.6586	LR: 0.100000
Training Epoch: 4 [4608/10284]	Loss: 0.6885	LR: 0.100000
Training Epoch: 4 [4864/10284]	Loss: 0.6603	LR: 0.100000
Training Epoch: 4 [5120/10284]	Loss: 0.6707	LR: 0.100000
Training Epoch: 4 [5376/10284]	Loss: 0.6520	LR: 0.100000
Training Epoch: 4 [5632/10284]	Loss: 0.6516	LR: 0.100000
Training Epoch: 4 [5888/10284]	Loss: 0.6714	LR: 0.100000
Training Epoch: 4 [6144/10284]	Loss: 0.6875	LR: 0.100000
Training Epoch: 4 [6400/10284]	Loss: 0.6943	LR: 0.100000
Training Epoch: 4 [6656/10284]	Loss: 0.6512	LR: 0.100000
Training Epoch: 4 [6912/10284]	Loss: 0.6425	LR: 0.100000
Training Epoch: 4 [7168/10284]	Loss: 0.6634	LR: 0.100000
Training Epoch: 4 [7424/10284]	Loss: 0.6646	LR: 0.100000
Training Epoch: 4 [7680/10284]	Loss: 0.6572	LR: 0.100000
Training Epoch: 4 [7936/10284]	Loss: 0.6745	LR: 0.100000
Training Epoch: 4 [8192/10284]	Loss: 0.6809	LR: 0.100000
Training Epoch: 4 [8448/10284]	Loss: 0.6730	LR: 0.100000
Training Epoch: 4 [8704/10284]	Loss: 0.6738	LR: 0.100000
Training Epoch: 4 [8960/10284]	Loss: 0.6438	LR: 0.100000
Training Epoch: 4 [9216/10284]	Loss: 0.6718	LR: 0.100000
Training Epoch: 4 [9472/10284]	Loss: 0.6397	LR: 0.100000
Training Epoch: 4 [9728/10284]	Loss: 0.6753	LR: 0.100000
Training Epoch: 4 [9984/10284]	Loss: 0.6658	LR: 0.100000
Training Epoch: 4 [10240/10284]	Loss: 0.6628	LR: 0.100000
Training Epoch: 4 [10284/10284]	Loss: 0.7267	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6723, Train Accuracy: 0.5852
Epoch 4 training time consumed: 148.45s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0029, Accuracy: 0.6179, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-4-best.pth
Training Epoch: 5 [256/10284]	Loss: 0.6585	LR: 0.100000
Training Epoch: 5 [512/10284]	Loss: 0.6737	LR: 0.100000
Training Epoch: 5 [768/10284]	Loss: 0.6951	LR: 0.100000
Training Epoch: 5 [1024/10284]	Loss: 0.6640	LR: 0.100000
Training Epoch: 5 [1280/10284]	Loss: 0.6731	LR: 0.100000
Training Epoch: 5 [1536/10284]	Loss: 0.6688	LR: 0.100000
Training Epoch: 5 [1792/10284]	Loss: 0.6800	LR: 0.100000
Training Epoch: 5 [2048/10284]	Loss: 0.6664	LR: 0.100000
Training Epoch: 5 [2304/10284]	Loss: 0.6756	LR: 0.100000
Training Epoch: 5 [2560/10284]	Loss: 0.6615	LR: 0.100000
Training Epoch: 5 [2816/10284]	Loss: 0.6681	LR: 0.100000
Training Epoch: 5 [3072/10284]	Loss: 0.6474	LR: 0.100000
Training Epoch: 5 [3328/10284]	Loss: 0.6667	LR: 0.100000
Training Epoch: 5 [3584/10284]	Loss: 0.6183	LR: 0.100000
Training Epoch: 5 [3840/10284]	Loss: 0.7111	LR: 0.100000
Training Epoch: 5 [4096/10284]	Loss: 0.6584	LR: 0.100000
Training Epoch: 5 [4352/10284]	Loss: 0.6731	LR: 0.100000
Training Epoch: 5 [4608/10284]	Loss: 0.6540	LR: 0.100000
Training Epoch: 5 [4864/10284]	Loss: 0.6429	LR: 0.100000
Training Epoch: 5 [5120/10284]	Loss: 0.6751	LR: 0.100000
Training Epoch: 5 [5376/10284]	Loss: 0.6406	LR: 0.100000
Training Epoch: 5 [5632/10284]	Loss: 0.6579	LR: 0.100000
Training Epoch: 5 [5888/10284]	Loss: 0.6676	LR: 0.100000
Training Epoch: 5 [6144/10284]	Loss: 0.6631	LR: 0.100000
Training Epoch: 5 [6400/10284]	Loss: 0.6806	LR: 0.100000
Training Epoch: 5 [6656/10284]	Loss: 0.6636	LR: 0.100000
Training Epoch: 5 [6912/10284]	Loss: 0.6682	LR: 0.100000
Training Epoch: 5 [7168/10284]	Loss: 0.6615	LR: 0.100000
Training Epoch: 5 [7424/10284]	Loss: 0.6604	LR: 0.100000
Training Epoch: 5 [7680/10284]	Loss: 0.6580	LR: 0.100000
Training Epoch: 5 [7936/10284]	Loss: 0.6470	LR: 0.100000
Training Epoch: 5 [8192/10284]	Loss: 0.6311	LR: 0.100000
Training Epoch: 5 [8448/10284]	Loss: 0.6680	LR: 0.100000
Training Epoch: 5 [8704/10284]	Loss: 0.6555	LR: 0.100000
Training Epoch: 5 [8960/10284]	Loss: 0.6425	LR: 0.100000
Training Epoch: 5 [9216/10284]	Loss: 0.6700	LR: 0.100000
Training Epoch: 5 [9472/10284]	Loss: 0.6754	LR: 0.100000
Training Epoch: 5 [9728/10284]	Loss: 0.6153	LR: 0.100000
Training Epoch: 5 [9984/10284]	Loss: 0.6172	LR: 0.100000
Training Epoch: 5 [10240/10284]	Loss: 0.6620	LR: 0.100000
Training Epoch: 5 [10284/10284]	Loss: 0.6877	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6610, Train Accuracy: 0.6027
Epoch 5 training time consumed: 147.86s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0030, Accuracy: 0.6029, Time consumed:8.08s
Training Epoch: 6 [256/10284]	Loss: 0.6494	LR: 0.100000
Training Epoch: 6 [512/10284]	Loss: 0.6290	LR: 0.100000
Training Epoch: 6 [768/10284]	Loss: 0.6900	LR: 0.100000
Training Epoch: 6 [1024/10284]	Loss: 0.6748	LR: 0.100000
Training Epoch: 6 [1280/10284]	Loss: 0.6430	LR: 0.100000
Training Epoch: 6 [1536/10284]	Loss: 0.6444	LR: 0.100000
Training Epoch: 6 [1792/10284]	Loss: 0.6563	LR: 0.100000
Training Epoch: 6 [2048/10284]	Loss: 0.6326	LR: 0.100000
Training Epoch: 6 [2304/10284]	Loss: 0.6273	LR: 0.100000
Training Epoch: 6 [2560/10284]	Loss: 0.6400	LR: 0.100000
Training Epoch: 6 [2816/10284]	Loss: 0.6335	LR: 0.100000
Training Epoch: 6 [3072/10284]	Loss: 0.6255	LR: 0.100000
Training Epoch: 6 [3328/10284]	Loss: 0.6793	LR: 0.100000
Training Epoch: 6 [3584/10284]	Loss: 0.6088	LR: 0.100000
Training Epoch: 6 [3840/10284]	Loss: 0.6357	LR: 0.100000
Training Epoch: 6 [4096/10284]	Loss: 0.5969	LR: 0.100000
Training Epoch: 6 [4352/10284]	Loss: 0.5855	LR: 0.100000
Training Epoch: 6 [4608/10284]	Loss: 0.6674	LR: 0.100000
Training Epoch: 6 [4864/10284]	Loss: 0.6265	LR: 0.100000
Training Epoch: 6 [5120/10284]	Loss: 0.6065	LR: 0.100000
Training Epoch: 6 [5376/10284]	Loss: 0.6053	LR: 0.100000
Training Epoch: 6 [5632/10284]	Loss: 0.6561	LR: 0.100000
Training Epoch: 6 [5888/10284]	Loss: 0.6047	LR: 0.100000
Training Epoch: 6 [6144/10284]	Loss: 0.5934	LR: 0.100000
Training Epoch: 6 [6400/10284]	Loss: 0.6068	LR: 0.100000
Training Epoch: 6 [6656/10284]	Loss: 0.6671	LR: 0.100000
Training Epoch: 6 [6912/10284]	Loss: 0.6341	LR: 0.100000
Training Epoch: 6 [7168/10284]	Loss: 0.6410	LR: 0.100000
Training Epoch: 6 [7424/10284]	Loss: 0.6032	LR: 0.100000
Training Epoch: 6 [7680/10284]	Loss: 0.6065	LR: 0.100000
Training Epoch: 6 [7936/10284]	Loss: 0.6055	LR: 0.100000
Training Epoch: 6 [8192/10284]	Loss: 0.6174	LR: 0.100000
Training Epoch: 6 [8448/10284]	Loss: 0.5977	LR: 0.100000
Training Epoch: 6 [8704/10284]	Loss: 0.6381	LR: 0.100000
Training Epoch: 6 [8960/10284]	Loss: 0.6318	LR: 0.100000
Training Epoch: 6 [9216/10284]	Loss: 0.6067	LR: 0.100000
Training Epoch: 6 [9472/10284]	Loss: 0.6064	LR: 0.100000
Training Epoch: 6 [9728/10284]	Loss: 0.5707	LR: 0.100000
Training Epoch: 6 [9984/10284]	Loss: 0.5726	LR: 0.100000
Training Epoch: 6 [10240/10284]	Loss: 0.6008	LR: 0.100000
Training Epoch: 6 [10284/10284]	Loss: 0.4970	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6249, Train Accuracy: 0.6508
Epoch 6 training time consumed: 149.91s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0040, Accuracy: 0.5438, Time consumed:8.09s
Training Epoch: 7 [256/10284]	Loss: 0.6169	LR: 0.100000
Training Epoch: 7 [512/10284]	Loss: 0.5896	LR: 0.100000
Training Epoch: 7 [768/10284]	Loss: 0.6814	LR: 0.100000
Training Epoch: 7 [1024/10284]	Loss: 0.6261	LR: 0.100000
Training Epoch: 7 [1280/10284]	Loss: 0.6279	LR: 0.100000
Training Epoch: 7 [1536/10284]	Loss: 0.5881	LR: 0.100000
Training Epoch: 7 [1792/10284]	Loss: 0.6074	LR: 0.100000
Training Epoch: 7 [2048/10284]	Loss: 0.6676	LR: 0.100000
Training Epoch: 7 [2304/10284]	Loss: 0.5450	LR: 0.100000
Training Epoch: 7 [2560/10284]	Loss: 0.6108	LR: 0.100000
Training Epoch: 7 [2816/10284]	Loss: 0.5777	LR: 0.100000
Training Epoch: 7 [3072/10284]	Loss: 0.5917	LR: 0.100000
Training Epoch: 7 [3328/10284]	Loss: 0.6129	LR: 0.100000
Training Epoch: 7 [3584/10284]	Loss: 0.5933	LR: 0.100000
Training Epoch: 7 [3840/10284]	Loss: 0.5747	LR: 0.100000
Training Epoch: 7 [4096/10284]	Loss: 0.5632	LR: 0.100000
Training Epoch: 7 [4352/10284]	Loss: 0.6332	LR: 0.100000
Training Epoch: 7 [4608/10284]	Loss: 0.5590	LR: 0.100000
Training Epoch: 7 [4864/10284]	Loss: 0.5827	LR: 0.100000
Training Epoch: 7 [5120/10284]	Loss: 0.5810	LR: 0.100000
Training Epoch: 7 [5376/10284]	Loss: 0.5754	LR: 0.100000
Training Epoch: 7 [5632/10284]	Loss: 0.5845	LR: 0.100000
Training Epoch: 7 [5888/10284]	Loss: 0.5648	LR: 0.100000
Training Epoch: 7 [6144/10284]	Loss: 0.5891	LR: 0.100000
Training Epoch: 7 [6400/10284]	Loss: 0.5921	LR: 0.100000
Training Epoch: 7 [6656/10284]	Loss: 0.5953	LR: 0.100000
Training Epoch: 7 [6912/10284]	Loss: 0.5476	LR: 0.100000
Training Epoch: 7 [7168/10284]	Loss: 0.5621	LR: 0.100000
Training Epoch: 7 [7424/10284]	Loss: 0.5549	LR: 0.100000
Training Epoch: 7 [7680/10284]	Loss: 0.5499	LR: 0.100000
Training Epoch: 7 [7936/10284]	Loss: 0.5751	LR: 0.100000
Training Epoch: 7 [8192/10284]	Loss: 0.5939	LR: 0.100000
Training Epoch: 7 [8448/10284]	Loss: 0.5488	LR: 0.100000
Training Epoch: 7 [8704/10284]	Loss: 0.5383	LR: 0.100000
Training Epoch: 7 [8960/10284]	Loss: 0.4972	LR: 0.100000
Training Epoch: 7 [9216/10284]	Loss: 0.5750	LR: 0.100000
Training Epoch: 7 [9472/10284]	Loss: 0.4944	LR: 0.100000
Training Epoch: 7 [9728/10284]	Loss: 0.5397	LR: 0.100000
Training Epoch: 7 [9984/10284]	Loss: 0.5683	LR: 0.100000
Training Epoch: 7 [10240/10284]	Loss: 0.5349	LR: 0.100000
Training Epoch: 7 [10284/10284]	Loss: 0.6370	LR: 0.100000
Epoch 7 - Average Train Loss: 0.5805, Train Accuracy: 0.6944
Epoch 7 training time consumed: 148.67s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0049, Accuracy: 0.5506, Time consumed:8.08s
Training Epoch: 8 [256/10284]	Loss: 0.6192	LR: 0.100000
Training Epoch: 8 [512/10284]	Loss: 0.7388	LR: 0.100000
Training Epoch: 8 [768/10284]	Loss: 0.6309	LR: 0.100000
Training Epoch: 8 [1024/10284]	Loss: 0.5818	LR: 0.100000
Training Epoch: 8 [1280/10284]	Loss: 0.6031	LR: 0.100000
Training Epoch: 8 [1536/10284]	Loss: 0.5945	LR: 0.100000
Training Epoch: 8 [1792/10284]	Loss: 0.5748	LR: 0.100000
Training Epoch: 8 [2048/10284]	Loss: 0.5718	LR: 0.100000
Training Epoch: 8 [2304/10284]	Loss: 0.5954	LR: 0.100000
Training Epoch: 8 [2560/10284]	Loss: 0.5336	LR: 0.100000
Training Epoch: 8 [2816/10284]	Loss: 0.5312	LR: 0.100000
Training Epoch: 8 [3072/10284]	Loss: 0.4578	LR: 0.100000
Training Epoch: 8 [3328/10284]	Loss: 0.4889	LR: 0.100000
Training Epoch: 8 [3584/10284]	Loss: 0.5129	LR: 0.100000
Training Epoch: 8 [3840/10284]	Loss: 0.5287	LR: 0.100000
Training Epoch: 8 [4096/10284]	Loss: 0.4277	LR: 0.100000
Training Epoch: 8 [4352/10284]	Loss: 0.6019	LR: 0.100000
Training Epoch: 8 [4608/10284]	Loss: 0.4895	LR: 0.100000
Training Epoch: 8 [4864/10284]	Loss: 0.4800	LR: 0.100000
Training Epoch: 8 [5120/10284]	Loss: 0.4821	LR: 0.100000
Training Epoch: 8 [5376/10284]	Loss: 0.4969	LR: 0.100000
Training Epoch: 8 [5632/10284]	Loss: 0.4360	LR: 0.100000
Training Epoch: 8 [5888/10284]	Loss: 0.4305	LR: 0.100000
Training Epoch: 8 [6144/10284]	Loss: 0.4645	LR: 0.100000
Training Epoch: 8 [6400/10284]	Loss: 0.4427	LR: 0.100000
Training Epoch: 8 [6656/10284]	Loss: 0.4784	LR: 0.100000
Training Epoch: 8 [6912/10284]	Loss: 0.5044	LR: 0.100000
Training Epoch: 8 [7168/10284]	Loss: 0.4825	LR: 0.100000
Training Epoch: 8 [7424/10284]	Loss: 0.5104	LR: 0.100000
Training Epoch: 8 [7680/10284]	Loss: 0.4944	LR: 0.100000
Training Epoch: 8 [7936/10284]	Loss: 0.5288	LR: 0.100000
Training Epoch: 8 [8192/10284]	Loss: 0.4953	LR: 0.100000
Training Epoch: 8 [8448/10284]	Loss: 0.4371	LR: 0.100000
Training Epoch: 8 [8704/10284]	Loss: 0.4704	LR: 0.100000
Training Epoch: 8 [8960/10284]	Loss: 0.5137	LR: 0.100000
Training Epoch: 8 [9216/10284]	Loss: 0.4459	LR: 0.100000
Training Epoch: 8 [9472/10284]	Loss: 0.4708	LR: 0.100000
Training Epoch: 8 [9728/10284]	Loss: 0.4466	LR: 0.100000
Training Epoch: 8 [9984/10284]	Loss: 0.4427	LR: 0.100000
Training Epoch: 8 [10240/10284]	Loss: 0.4991	LR: 0.100000
Training Epoch: 8 [10284/10284]	Loss: 0.5178	LR: 0.100000
Epoch 8 - Average Train Loss: 0.5134, Train Accuracy: 0.7500
Epoch 8 training time consumed: 148.98s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0035, Accuracy: 0.5467, Time consumed:7.91s
Training Epoch: 9 [256/10284]	Loss: 0.5121	LR: 0.100000
Training Epoch: 9 [512/10284]	Loss: 0.5486	LR: 0.100000
Training Epoch: 9 [768/10284]	Loss: 0.5080	LR: 0.100000
Training Epoch: 9 [1024/10284]	Loss: 0.4347	LR: 0.100000
Training Epoch: 9 [1280/10284]	Loss: 0.4970	LR: 0.100000
Training Epoch: 9 [1536/10284]	Loss: 0.4544	LR: 0.100000
Training Epoch: 9 [1792/10284]	Loss: 0.4512	LR: 0.100000
Training Epoch: 9 [2048/10284]	Loss: 0.5227	LR: 0.100000
Training Epoch: 9 [2304/10284]	Loss: 0.4326	LR: 0.100000
Training Epoch: 9 [2560/10284]	Loss: 0.4289	LR: 0.100000
Training Epoch: 9 [2816/10284]	Loss: 0.4445	LR: 0.100000
Training Epoch: 9 [3072/10284]	Loss: 0.4274	LR: 0.100000
Training Epoch: 9 [3328/10284]	Loss: 0.4824	LR: 0.100000
Training Epoch: 9 [3584/10284]	Loss: 0.4427	LR: 0.100000
Training Epoch: 9 [3840/10284]	Loss: 0.4675	LR: 0.100000
Training Epoch: 9 [4096/10284]	Loss: 0.4338	LR: 0.100000
Training Epoch: 9 [4352/10284]	Loss: 0.4582	LR: 0.100000
Training Epoch: 9 [4608/10284]	Loss: 0.3868	LR: 0.100000
Training Epoch: 9 [4864/10284]	Loss: 0.3573	LR: 0.100000
Training Epoch: 9 [5120/10284]	Loss: 0.3731	LR: 0.100000
Training Epoch: 9 [5376/10284]	Loss: 0.4421	LR: 0.100000
Training Epoch: 9 [5632/10284]	Loss: 0.4856	LR: 0.100000
Training Epoch: 9 [5888/10284]	Loss: 0.4816	LR: 0.100000
Training Epoch: 9 [6144/10284]	Loss: 0.4308	LR: 0.100000
Training Epoch: 9 [6400/10284]	Loss: 0.4330	LR: 0.100000
Training Epoch: 9 [6656/10284]	Loss: 0.4042	LR: 0.100000
Training Epoch: 9 [6912/10284]	Loss: 0.4128	LR: 0.100000
Training Epoch: 9 [7168/10284]	Loss: 0.4567	LR: 0.100000
Training Epoch: 9 [7424/10284]	Loss: 0.4469	LR: 0.100000
Training Epoch: 9 [7680/10284]	Loss: 0.4253	LR: 0.100000
Training Epoch: 9 [7936/10284]	Loss: 0.4277	LR: 0.100000
Training Epoch: 9 [8192/10284]	Loss: 0.4604	LR: 0.100000
Training Epoch: 9 [8448/10284]	Loss: 0.4016	LR: 0.100000
Training Epoch: 9 [8704/10284]	Loss: 0.4241	LR: 0.100000
Training Epoch: 9 [8960/10284]	Loss: 0.3696	LR: 0.100000
Training Epoch: 9 [9216/10284]	Loss: 0.3335	LR: 0.100000
Training Epoch: 9 [9472/10284]	Loss: 0.4313	LR: 0.100000
Training Epoch: 9 [9728/10284]	Loss: 0.3769	LR: 0.100000
Training Epoch: 9 [9984/10284]	Loss: 0.3942	LR: 0.100000
Training Epoch: 9 [10240/10284]	Loss: 0.4682	LR: 0.100000
Training Epoch: 9 [10284/10284]	Loss: 0.4062	LR: 0.100000
Epoch 9 - Average Train Loss: 0.4391, Train Accuracy: 0.8001
Epoch 9 training time consumed: 148.32s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0018, Accuracy: 0.8291, Time consumed:7.94s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-9-best.pth
Training Epoch: 10 [256/10284]	Loss: 0.4624	LR: 0.020000
Training Epoch: 10 [512/10284]	Loss: 0.3471	LR: 0.020000
Training Epoch: 10 [768/10284]	Loss: 0.4206	LR: 0.020000
Training Epoch: 10 [1024/10284]	Loss: 0.3583	LR: 0.020000
Training Epoch: 10 [1280/10284]	Loss: 0.4006	LR: 0.020000
Training Epoch: 10 [1536/10284]	Loss: 0.4250	LR: 0.020000
Training Epoch: 10 [1792/10284]	Loss: 0.3940	LR: 0.020000
Training Epoch: 10 [2048/10284]	Loss: 0.4164	LR: 0.020000
Training Epoch: 10 [2304/10284]	Loss: 0.3495	LR: 0.020000
Training Epoch: 10 [2560/10284]	Loss: 0.3720	LR: 0.020000
Training Epoch: 10 [2816/10284]	Loss: 0.4128	LR: 0.020000
Training Epoch: 10 [3072/10284]	Loss: 0.3301	LR: 0.020000
Training Epoch: 10 [3328/10284]	Loss: 0.3949	LR: 0.020000
Training Epoch: 10 [3584/10284]	Loss: 0.3561	LR: 0.020000
Training Epoch: 10 [3840/10284]	Loss: 0.3650	LR: 0.020000
Training Epoch: 10 [4096/10284]	Loss: 0.3745	LR: 0.020000
Training Epoch: 10 [4352/10284]	Loss: 0.3316	LR: 0.020000
Training Epoch: 10 [4608/10284]	Loss: 0.4067	LR: 0.020000
Training Epoch: 10 [4864/10284]	Loss: 0.3715	LR: 0.020000
Training Epoch: 10 [5120/10284]	Loss: 0.3573	LR: 0.020000
Training Epoch: 10 [5376/10284]	Loss: 0.3221	LR: 0.020000
Training Epoch: 10 [5632/10284]	Loss: 0.3823	LR: 0.020000
Training Epoch: 10 [5888/10284]	Loss: 0.3407	LR: 0.020000
Training Epoch: 10 [6144/10284]	Loss: 0.3603	LR: 0.020000
Training Epoch: 10 [6400/10284]	Loss: 0.3933	LR: 0.020000
Training Epoch: 10 [6656/10284]	Loss: 0.3973	LR: 0.020000
Training Epoch: 10 [6912/10284]	Loss: 0.3717	LR: 0.020000
Training Epoch: 10 [7168/10284]	Loss: 0.3321	LR: 0.020000
Training Epoch: 10 [7424/10284]	Loss: 0.3414	LR: 0.020000
Training Epoch: 10 [7680/10284]	Loss: 0.3296	LR: 0.020000
Training Epoch: 10 [7936/10284]	Loss: 0.3156	LR: 0.020000
Training Epoch: 10 [8192/10284]	Loss: 0.3559	LR: 0.020000
Training Epoch: 10 [8448/10284]	Loss: 0.3726	LR: 0.020000
Training Epoch: 10 [8704/10284]	Loss: 0.2914	LR: 0.020000
Training Epoch: 10 [8960/10284]	Loss: 0.3404	LR: 0.020000
Training Epoch: 10 [9216/10284]	Loss: 0.3415	LR: 0.020000
Training Epoch: 10 [9472/10284]	Loss: 0.3222	LR: 0.020000
Training Epoch: 10 [9728/10284]	Loss: 0.3059	LR: 0.020000
Training Epoch: 10 [9984/10284]	Loss: 0.3530	LR: 0.020000
Training Epoch: 10 [10240/10284]	Loss: 0.3254	LR: 0.020000
Training Epoch: 10 [10284/10284]	Loss: 0.3555	LR: 0.020000
Epoch 10 - Average Train Loss: 0.3635, Train Accuracy: 0.8397
Epoch 10 training time consumed: 148.26s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0014, Accuracy: 0.8688, Time consumed:7.88s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-10-best.pth
Training Epoch: 11 [256/10284]	Loss: 0.3276	LR: 0.020000
Training Epoch: 11 [512/10284]	Loss: 0.4080	LR: 0.020000
Training Epoch: 11 [768/10284]	Loss: 0.3119	LR: 0.020000
Training Epoch: 11 [1024/10284]	Loss: 0.3326	LR: 0.020000
Training Epoch: 11 [1280/10284]	Loss: 0.3237	LR: 0.020000
Training Epoch: 11 [1536/10284]	Loss: 0.3743	LR: 0.020000
Training Epoch: 11 [1792/10284]	Loss: 0.3586	LR: 0.020000
Training Epoch: 11 [2048/10284]	Loss: 0.3701	LR: 0.020000
Training Epoch: 11 [2304/10284]	Loss: 0.3199	LR: 0.020000
Training Epoch: 11 [2560/10284]	Loss: 0.3196	LR: 0.020000
Training Epoch: 11 [2816/10284]	Loss: 0.3538	LR: 0.020000
Training Epoch: 11 [3072/10284]	Loss: 0.2932	LR: 0.020000
Training Epoch: 11 [3328/10284]	Loss: 0.3217	LR: 0.020000
Training Epoch: 11 [3584/10284]	Loss: 0.3106	LR: 0.020000
Training Epoch: 11 [3840/10284]	Loss: 0.3132	LR: 0.020000
Training Epoch: 11 [4096/10284]	Loss: 0.3446	LR: 0.020000
Training Epoch: 11 [4352/10284]	Loss: 0.3604	LR: 0.020000
Training Epoch: 11 [4608/10284]	Loss: 0.2965	LR: 0.020000
Training Epoch: 11 [4864/10284]	Loss: 0.3999	LR: 0.020000
Training Epoch: 11 [5120/10284]	Loss: 0.2839	LR: 0.020000
Training Epoch: 11 [5376/10284]	Loss: 0.3457	LR: 0.020000
Training Epoch: 11 [5632/10284]	Loss: 0.3581	LR: 0.020000
Training Epoch: 11 [5888/10284]	Loss: 0.3458	LR: 0.020000
Training Epoch: 11 [6144/10284]	Loss: 0.3079	LR: 0.020000
Training Epoch: 11 [6400/10284]	Loss: 0.3028	LR: 0.020000
Training Epoch: 11 [6656/10284]	Loss: 0.4378	LR: 0.020000
Training Epoch: 11 [6912/10284]	Loss: 0.2838	LR: 0.020000
Training Epoch: 11 [7168/10284]	Loss: 0.2896	LR: 0.020000
Training Epoch: 11 [7424/10284]	Loss: 0.2893	LR: 0.020000
Training Epoch: 11 [7680/10284]	Loss: 0.3132	LR: 0.020000
Training Epoch: 11 [7936/10284]	Loss: 0.2806	LR: 0.020000
Training Epoch: 11 [8192/10284]	Loss: 0.3149	LR: 0.020000
Training Epoch: 11 [8448/10284]	Loss: 0.3519	LR: 0.020000
Training Epoch: 11 [8704/10284]	Loss: 0.2661	LR: 0.020000
Training Epoch: 11 [8960/10284]	Loss: 0.2669	LR: 0.020000
Training Epoch: 11 [9216/10284]	Loss: 0.3146	LR: 0.020000
Training Epoch: 11 [9472/10284]	Loss: 0.2717	LR: 0.020000
Training Epoch: 11 [9728/10284]	Loss: 0.2992	LR: 0.020000
Training Epoch: 11 [9984/10284]	Loss: 0.3136	LR: 0.020000
Training Epoch: 11 [10240/10284]	Loss: 0.3157	LR: 0.020000
Training Epoch: 11 [10284/10284]	Loss: 0.2764	LR: 0.020000
Epoch 11 - Average Train Loss: 0.3246, Train Accuracy: 0.8610
Epoch 11 training time consumed: 149.35s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0014, Accuracy: 0.8668, Time consumed:7.93s
Training Epoch: 12 [256/10284]	Loss: 0.2982	LR: 0.020000
Training Epoch: 12 [512/10284]	Loss: 0.3415	LR: 0.020000
Training Epoch: 12 [768/10284]	Loss: 0.3126	LR: 0.020000
Training Epoch: 12 [1024/10284]	Loss: 0.3070	LR: 0.020000
Training Epoch: 12 [1280/10284]	Loss: 0.3412	LR: 0.020000
Training Epoch: 12 [1536/10284]	Loss: 0.3160	LR: 0.020000
Training Epoch: 12 [1792/10284]	Loss: 0.3130	LR: 0.020000
Training Epoch: 12 [2048/10284]	Loss: 0.3001	LR: 0.020000
Training Epoch: 12 [2304/10284]	Loss: 0.2698	LR: 0.020000
Training Epoch: 12 [2560/10284]	Loss: 0.3231	LR: 0.020000
Training Epoch: 12 [2816/10284]	Loss: 0.3008	LR: 0.020000
Training Epoch: 12 [3072/10284]	Loss: 0.2995	LR: 0.020000
Training Epoch: 12 [3328/10284]	Loss: 0.3146	LR: 0.020000
Training Epoch: 12 [3584/10284]	Loss: 0.3193	LR: 0.020000
Training Epoch: 12 [3840/10284]	Loss: 0.2435	LR: 0.020000
Training Epoch: 12 [4096/10284]	Loss: 0.2280	LR: 0.020000
Training Epoch: 12 [4352/10284]	Loss: 0.2807	LR: 0.020000
Training Epoch: 12 [4608/10284]	Loss: 0.2249	LR: 0.020000
Training Epoch: 12 [4864/10284]	Loss: 0.2744	LR: 0.020000
Training Epoch: 12 [5120/10284]	Loss: 0.2869	LR: 0.020000
Training Epoch: 12 [5376/10284]	Loss: 0.2547	LR: 0.020000
Training Epoch: 12 [5632/10284]	Loss: 0.2488	LR: 0.020000
Training Epoch: 12 [5888/10284]	Loss: 0.3364	LR: 0.020000
Training Epoch: 12 [6144/10284]	Loss: 0.3108	LR: 0.020000
Training Epoch: 12 [6400/10284]	Loss: 0.2063	LR: 0.020000
Training Epoch: 12 [6656/10284]	Loss: 0.2583	LR: 0.020000
Training Epoch: 12 [6912/10284]	Loss: 0.2208	LR: 0.020000
Training Epoch: 12 [7168/10284]	Loss: 0.3535	LR: 0.020000
Training Epoch: 12 [7424/10284]	Loss: 0.2408	LR: 0.020000
Training Epoch: 12 [7680/10284]	Loss: 0.2296	LR: 0.020000
Training Epoch: 12 [7936/10284]	Loss: 0.2361	LR: 0.020000
Training Epoch: 12 [8192/10284]	Loss: 0.3677	LR: 0.020000
Training Epoch: 12 [8448/10284]	Loss: 0.2915	LR: 0.020000
Training Epoch: 12 [8704/10284]	Loss: 0.2800	LR: 0.020000
Training Epoch: 12 [8960/10284]	Loss: 0.2863	LR: 0.020000
Training Epoch: 12 [9216/10284]	Loss: 0.1971	LR: 0.020000
Training Epoch: 12 [9472/10284]	Loss: 0.2896	LR: 0.020000
Training Epoch: 12 [9728/10284]	Loss: 0.2334	LR: 0.020000
Training Epoch: 12 [9984/10284]	Loss: 0.2661	LR: 0.020000
Training Epoch: 12 [10240/10284]	Loss: 0.3192	LR: 0.020000
Training Epoch: 12 [10284/10284]	Loss: 0.4606	LR: 0.020000
Epoch 12 - Average Train Loss: 0.2838, Train Accuracy: 0.8792
Epoch 12 training time consumed: 147.82s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0013, Accuracy: 0.8847, Time consumed:8.11s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-12-best.pth
Training Epoch: 13 [256/10284]	Loss: 0.2513	LR: 0.020000
Training Epoch: 13 [512/10284]	Loss: 0.2639	LR: 0.020000
Training Epoch: 13 [768/10284]	Loss: 0.2872	LR: 0.020000
Training Epoch: 13 [1024/10284]	Loss: 0.2820	LR: 0.020000
Training Epoch: 13 [1280/10284]	Loss: 0.2996	LR: 0.020000
Training Epoch: 13 [1536/10284]	Loss: 0.3019	LR: 0.020000
Training Epoch: 13 [1792/10284]	Loss: 0.3325	LR: 0.020000
Training Epoch: 13 [2048/10284]	Loss: 0.2745	LR: 0.020000
Training Epoch: 13 [2304/10284]	Loss: 0.3303	LR: 0.020000
Training Epoch: 13 [2560/10284]	Loss: 0.3201	LR: 0.020000
Training Epoch: 13 [2816/10284]	Loss: 0.2386	LR: 0.020000
Training Epoch: 13 [3072/10284]	Loss: 0.2535	LR: 0.020000
Training Epoch: 13 [3328/10284]	Loss: 0.3402	LR: 0.020000
Training Epoch: 13 [3584/10284]	Loss: 0.2721	LR: 0.020000
Training Epoch: 13 [3840/10284]	Loss: 0.2551	LR: 0.020000
Training Epoch: 13 [4096/10284]	Loss: 0.2337	LR: 0.020000
Training Epoch: 13 [4352/10284]	Loss: 0.2280	LR: 0.020000
Training Epoch: 13 [4608/10284]	Loss: 0.3038	LR: 0.020000
Training Epoch: 13 [4864/10284]	Loss: 0.2658	LR: 0.020000
Training Epoch: 13 [5120/10284]	Loss: 0.2775	LR: 0.020000
Training Epoch: 13 [5376/10284]	Loss: 0.3092	LR: 0.020000
Training Epoch: 13 [5632/10284]	Loss: 0.2594	LR: 0.020000
Training Epoch: 13 [5888/10284]	Loss: 0.2187	LR: 0.020000
Training Epoch: 13 [6144/10284]	Loss: 0.2787	LR: 0.020000
Training Epoch: 13 [6400/10284]	Loss: 0.2327	LR: 0.020000
Training Epoch: 13 [6656/10284]	Loss: 0.2422	LR: 0.020000
Training Epoch: 13 [6912/10284]	Loss: 0.2828	LR: 0.020000
Training Epoch: 13 [7168/10284]	Loss: 0.2468	LR: 0.020000
Training Epoch: 13 [7424/10284]	Loss: 0.1986	LR: 0.020000
Training Epoch: 13 [7680/10284]	Loss: 0.2887	LR: 0.020000
Training Epoch: 13 [7936/10284]	Loss: 0.2099	LR: 0.020000
Training Epoch: 13 [8192/10284]	Loss: 0.2419	LR: 0.020000
Training Epoch: 13 [8448/10284]	Loss: 0.2458	LR: 0.020000
Training Epoch: 13 [8704/10284]	Loss: 0.2498	LR: 0.020000
Training Epoch: 13 [8960/10284]	Loss: 0.2714	LR: 0.020000
Training Epoch: 13 [9216/10284]	Loss: 0.1755	LR: 0.020000
Training Epoch: 13 [9472/10284]	Loss: 0.2176	LR: 0.020000
Training Epoch: 13 [9728/10284]	Loss: 0.1917	LR: 0.020000
Training Epoch: 13 [9984/10284]	Loss: 0.2017	LR: 0.020000
Training Epoch: 13 [10240/10284]	Loss: 0.1895	LR: 0.020000
Training Epoch: 13 [10284/10284]	Loss: 0.1392	LR: 0.020000
Epoch 13 - Average Train Loss: 0.2586, Train Accuracy: 0.8908
Epoch 13 training time consumed: 148.29s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0009, Accuracy: 0.9201, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-13-best.pth
Training Epoch: 14 [256/10284]	Loss: 0.2132	LR: 0.020000
Training Epoch: 14 [512/10284]	Loss: 0.2688	LR: 0.020000
Training Epoch: 14 [768/10284]	Loss: 0.2018	LR: 0.020000
Training Epoch: 14 [1024/10284]	Loss: 0.2410	LR: 0.020000
Training Epoch: 14 [1280/10284]	Loss: 0.2054	LR: 0.020000
Training Epoch: 14 [1536/10284]	Loss: 0.3204	LR: 0.020000
Training Epoch: 14 [1792/10284]	Loss: 0.2444	LR: 0.020000
Training Epoch: 14 [2048/10284]	Loss: 0.2196	LR: 0.020000
Training Epoch: 14 [2304/10284]	Loss: 0.1810	LR: 0.020000
Training Epoch: 14 [2560/10284]	Loss: 0.2387	LR: 0.020000
Training Epoch: 14 [2816/10284]	Loss: 0.3066	LR: 0.020000
Training Epoch: 14 [3072/10284]	Loss: 0.2224	LR: 0.020000
Training Epoch: 14 [3328/10284]	Loss: 0.2596	LR: 0.020000
Training Epoch: 14 [3584/10284]	Loss: 0.2190	LR: 0.020000
Training Epoch: 14 [3840/10284]	Loss: 0.2415	LR: 0.020000
Training Epoch: 14 [4096/10284]	Loss: 0.2472	LR: 0.020000
Training Epoch: 14 [4352/10284]	Loss: 0.2209	LR: 0.020000
Training Epoch: 14 [4608/10284]	Loss: 0.1896	LR: 0.020000
Training Epoch: 14 [4864/10284]	Loss: 0.1852	LR: 0.020000
Training Epoch: 14 [5120/10284]	Loss: 0.2487	LR: 0.020000
Training Epoch: 14 [5376/10284]	Loss: 0.2792	LR: 0.020000
Training Epoch: 14 [5632/10284]	Loss: 0.1676	LR: 0.020000
Training Epoch: 14 [5888/10284]	Loss: 0.2303	LR: 0.020000
Training Epoch: 14 [6144/10284]	Loss: 0.2895	LR: 0.020000
Training Epoch: 14 [6400/10284]	Loss: 0.2086	LR: 0.020000
Training Epoch: 14 [6656/10284]	Loss: 0.1962	LR: 0.020000
Training Epoch: 14 [6912/10284]	Loss: 0.2556	LR: 0.020000
Training Epoch: 14 [7168/10284]	Loss: 0.2736	LR: 0.020000
Training Epoch: 14 [7424/10284]	Loss: 0.2189	LR: 0.020000
Training Epoch: 14 [7680/10284]	Loss: 0.2427	LR: 0.020000
Training Epoch: 14 [7936/10284]	Loss: 0.2017	LR: 0.020000
Training Epoch: 14 [8192/10284]	Loss: 0.2251	LR: 0.020000
Training Epoch: 14 [8448/10284]	Loss: 0.3243	LR: 0.020000
Training Epoch: 14 [8704/10284]	Loss: 0.2418	LR: 0.020000
Training Epoch: 14 [8960/10284]	Loss: 0.2338	LR: 0.020000
Training Epoch: 14 [9216/10284]	Loss: 0.2677	LR: 0.020000
Training Epoch: 14 [9472/10284]	Loss: 0.2318	LR: 0.020000
Training Epoch: 14 [9728/10284]	Loss: 0.2359	LR: 0.020000
Training Epoch: 14 [9984/10284]	Loss: 0.1870	LR: 0.020000
Training Epoch: 14 [10240/10284]	Loss: 0.2582	LR: 0.020000
Training Epoch: 14 [10284/10284]	Loss: 0.1138	LR: 0.020000
Epoch 14 - Average Train Loss: 0.2356, Train Accuracy: 0.9027
Epoch 14 training time consumed: 148.41s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0009, Accuracy: 0.9114, Time consumed:8.19s
Training Epoch: 15 [256/10284]	Loss: 0.1747	LR: 0.020000
Training Epoch: 15 [512/10284]	Loss: 0.2169	LR: 0.020000
Training Epoch: 15 [768/10284]	Loss: 0.2563	LR: 0.020000
Training Epoch: 15 [1024/10284]	Loss: 0.2624	LR: 0.020000
Training Epoch: 15 [1280/10284]	Loss: 0.2020	LR: 0.020000
Training Epoch: 15 [1536/10284]	Loss: 0.2529	LR: 0.020000
Training Epoch: 15 [1792/10284]	Loss: 0.2163	LR: 0.020000
Training Epoch: 15 [2048/10284]	Loss: 0.2213	LR: 0.020000
Training Epoch: 15 [2304/10284]	Loss: 0.2288	LR: 0.020000
Training Epoch: 15 [2560/10284]	Loss: 0.2115	LR: 0.020000
Training Epoch: 15 [2816/10284]	Loss: 0.2272	LR: 0.020000
Training Epoch: 15 [3072/10284]	Loss: 0.1540	LR: 0.020000
Training Epoch: 15 [3328/10284]	Loss: 0.2005	LR: 0.020000
Training Epoch: 15 [3584/10284]	Loss: 0.2353	LR: 0.020000
Training Epoch: 15 [3840/10284]	Loss: 0.1881	LR: 0.020000
Training Epoch: 15 [4096/10284]	Loss: 0.2046	LR: 0.020000
Training Epoch: 15 [4352/10284]	Loss: 0.2206	LR: 0.020000
Training Epoch: 15 [4608/10284]	Loss: 0.1941	LR: 0.020000
Training Epoch: 15 [4864/10284]	Loss: 0.2499	LR: 0.020000
Training Epoch: 15 [5120/10284]	Loss: 0.2035	LR: 0.020000
Training Epoch: 15 [5376/10284]	Loss: 0.1951	LR: 0.020000
Training Epoch: 15 [5632/10284]	Loss: 0.2017	LR: 0.020000
Training Epoch: 15 [5888/10284]	Loss: 0.1704	LR: 0.020000
Training Epoch: 15 [6144/10284]	Loss: 0.1770	LR: 0.020000
Training Epoch: 15 [6400/10284]	Loss: 0.1944	LR: 0.020000
Training Epoch: 15 [6656/10284]	Loss: 0.2184	LR: 0.020000
Training Epoch: 15 [6912/10284]	Loss: 0.1670	LR: 0.020000
Training Epoch: 15 [7168/10284]	Loss: 0.1736	LR: 0.020000
Training Epoch: 15 [7424/10284]	Loss: 0.2137	LR: 0.020000
Training Epoch: 15 [7680/10284]	Loss: 0.1814	LR: 0.020000
Training Epoch: 15 [7936/10284]	Loss: 0.2804	LR: 0.020000
Training Epoch: 15 [8192/10284]	Loss: 0.1729	LR: 0.020000
Training Epoch: 15 [8448/10284]	Loss: 0.1830	LR: 0.020000
Training Epoch: 15 [8704/10284]	Loss: 0.1997	LR: 0.020000
Training Epoch: 15 [8960/10284]	Loss: 0.2676	LR: 0.020000
Training Epoch: 15 [9216/10284]	Loss: 0.1938	LR: 0.020000
Training Epoch: 15 [9472/10284]	Loss: 0.1661	LR: 0.020000
Training Epoch: 15 [9728/10284]	Loss: 0.2576	LR: 0.020000
Training Epoch: 15 [9984/10284]	Loss: 0.2531	LR: 0.020000
Training Epoch: 15 [10240/10284]	Loss: 0.1857	LR: 0.020000
Training Epoch: 15 [10284/10284]	Loss: 0.3053	LR: 0.020000
Epoch 15 - Average Train Loss: 0.2097, Train Accuracy: 0.9137
Epoch 15 training time consumed: 148.36s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0008, Accuracy: 0.9143, Time consumed:7.94s
Training Epoch: 16 [256/10284]	Loss: 0.1719	LR: 0.020000
Training Epoch: 16 [512/10284]	Loss: 0.1725	LR: 0.020000
Training Epoch: 16 [768/10284]	Loss: 0.2055	LR: 0.020000
Training Epoch: 16 [1024/10284]	Loss: 0.1570	LR: 0.020000
Training Epoch: 16 [1280/10284]	Loss: 0.2317	LR: 0.020000
Training Epoch: 16 [1536/10284]	Loss: 0.2328	LR: 0.020000
Training Epoch: 16 [1792/10284]	Loss: 0.2193	LR: 0.020000
Training Epoch: 16 [2048/10284]	Loss: 0.2601	LR: 0.020000
Training Epoch: 16 [2304/10284]	Loss: 0.1758	LR: 0.020000
Training Epoch: 16 [2560/10284]	Loss: 0.1984	LR: 0.020000
Training Epoch: 16 [2816/10284]	Loss: 0.2279	LR: 0.020000
Training Epoch: 16 [3072/10284]	Loss: 0.2469	LR: 0.020000
Training Epoch: 16 [3328/10284]	Loss: 0.1946	LR: 0.020000
Training Epoch: 16 [3584/10284]	Loss: 0.1786	LR: 0.020000
Training Epoch: 16 [3840/10284]	Loss: 0.2608	LR: 0.020000
Training Epoch: 16 [4096/10284]	Loss: 0.1828	LR: 0.020000
Training Epoch: 16 [4352/10284]	Loss: 0.2604	LR: 0.020000
Training Epoch: 16 [4608/10284]	Loss: 0.1813	LR: 0.020000
Training Epoch: 16 [4864/10284]	Loss: 0.1900	LR: 0.020000
Training Epoch: 16 [5120/10284]	Loss: 0.2199	LR: 0.020000
Training Epoch: 16 [5376/10284]	Loss: 0.1765	LR: 0.020000
Training Epoch: 16 [5632/10284]	Loss: 0.2058	LR: 0.020000
Training Epoch: 16 [5888/10284]	Loss: 0.1985	LR: 0.020000
Training Epoch: 16 [6144/10284]	Loss: 0.1807	LR: 0.020000
Training Epoch: 16 [6400/10284]	Loss: 0.2143	LR: 0.020000
Training Epoch: 16 [6656/10284]	Loss: 0.1916	LR: 0.020000
Training Epoch: 16 [6912/10284]	Loss: 0.2429	LR: 0.020000
Training Epoch: 16 [7168/10284]	Loss: 0.2023	LR: 0.020000
Training Epoch: 16 [7424/10284]	Loss: 0.1987	LR: 0.020000
Training Epoch: 16 [7680/10284]	Loss: 0.2536	LR: 0.020000
Training Epoch: 16 [7936/10284]	Loss: 0.1559	LR: 0.020000
Training Epoch: 16 [8192/10284]	Loss: 0.1557	LR: 0.020000
Training Epoch: 16 [8448/10284]	Loss: 0.2056	LR: 0.020000
Training Epoch: 16 [8704/10284]	Loss: 0.1466	LR: 0.020000
Training Epoch: 16 [8960/10284]	Loss: 0.1719	LR: 0.020000
Training Epoch: 16 [9216/10284]	Loss: 0.2032	LR: 0.020000
Training Epoch: 16 [9472/10284]	Loss: 0.1898	LR: 0.020000
Training Epoch: 16 [9728/10284]	Loss: 0.1549	LR: 0.020000
Training Epoch: 16 [9984/10284]	Loss: 0.1757	LR: 0.020000
Training Epoch: 16 [10240/10284]	Loss: 0.2291	LR: 0.020000
Training Epoch: 16 [10284/10284]	Loss: 0.1312	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2002, Train Accuracy: 0.9142
Epoch 16 training time consumed: 148.78s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0016, Accuracy: 0.8634, Time consumed:7.84s
Training Epoch: 17 [256/10284]	Loss: 0.1536	LR: 0.020000
Training Epoch: 17 [512/10284]	Loss: 0.1946	LR: 0.020000
Training Epoch: 17 [768/10284]	Loss: 0.2183	LR: 0.020000
Training Epoch: 17 [1024/10284]	Loss: 0.2126	LR: 0.020000
Training Epoch: 17 [1280/10284]	Loss: 0.2090	LR: 0.020000
Training Epoch: 17 [1536/10284]	Loss: 0.1581	LR: 0.020000
Training Epoch: 17 [1792/10284]	Loss: 0.1732	LR: 0.020000
Training Epoch: 17 [2048/10284]	Loss: 0.1810	LR: 0.020000
Training Epoch: 17 [2304/10284]	Loss: 0.1794	LR: 0.020000
Training Epoch: 17 [2560/10284]	Loss: 0.2213	LR: 0.020000
Training Epoch: 17 [2816/10284]	Loss: 0.2353	LR: 0.020000
Training Epoch: 17 [3072/10284]	Loss: 0.2360	LR: 0.020000
Training Epoch: 17 [3328/10284]	Loss: 0.2289	LR: 0.020000
Training Epoch: 17 [3584/10284]	Loss: 0.1931	LR: 0.020000
Training Epoch: 17 [3840/10284]	Loss: 0.1814	LR: 0.020000
Training Epoch: 17 [4096/10284]	Loss: 0.1757	LR: 0.020000
Training Epoch: 17 [4352/10284]	Loss: 0.2031	LR: 0.020000
Training Epoch: 17 [4608/10284]	Loss: 0.1804	LR: 0.020000
Training Epoch: 17 [4864/10284]	Loss: 0.1507	LR: 0.020000
Training Epoch: 17 [5120/10284]	Loss: 0.1452	LR: 0.020000
Training Epoch: 17 [5376/10284]	Loss: 0.2997	LR: 0.020000
Training Epoch: 17 [5632/10284]	Loss: 0.1604	LR: 0.020000
Training Epoch: 17 [5888/10284]	Loss: 0.1571	LR: 0.020000
Training Epoch: 17 [6144/10284]	Loss: 0.2020	LR: 0.020000
Training Epoch: 17 [6400/10284]	Loss: 0.2072	LR: 0.020000
Training Epoch: 17 [6656/10284]	Loss: 0.2054	LR: 0.020000
Training Epoch: 17 [6912/10284]	Loss: 0.2055	LR: 0.020000
Training Epoch: 17 [7168/10284]	Loss: 0.2185	LR: 0.020000
Training Epoch: 17 [7424/10284]	Loss: 0.2119	LR: 0.020000
Training Epoch: 17 [7680/10284]	Loss: 0.2132	LR: 0.020000
Training Epoch: 17 [7936/10284]	Loss: 0.2026	LR: 0.020000
Training Epoch: 17 [8192/10284]	Loss: 0.1946	LR: 0.020000
Training Epoch: 17 [8448/10284]	Loss: 0.1483	LR: 0.020000
Training Epoch: 17 [8704/10284]	Loss: 0.2330	LR: 0.020000
Training Epoch: 17 [8960/10284]	Loss: 0.1547	LR: 0.020000
Training Epoch: 17 [9216/10284]	Loss: 0.1596	LR: 0.020000
Training Epoch: 17 [9472/10284]	Loss: 0.2219	LR: 0.020000
Training Epoch: 17 [9728/10284]	Loss: 0.2592	LR: 0.020000
Training Epoch: 17 [9984/10284]	Loss: 0.2203	LR: 0.020000
Training Epoch: 17 [10240/10284]	Loss: 0.1603	LR: 0.020000
Training Epoch: 17 [10284/10284]	Loss: 0.1863	LR: 0.020000
Epoch 17 - Average Train Loss: 0.1966, Train Accuracy: 0.9188
Epoch 17 training time consumed: 148.33s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0019, Accuracy: 0.8504, Time consumed:7.93s
Training Epoch: 18 [256/10284]	Loss: 0.2064	LR: 0.020000
Training Epoch: 18 [512/10284]	Loss: 0.1466	LR: 0.020000
Training Epoch: 18 [768/10284]	Loss: 0.1577	LR: 0.020000
Training Epoch: 18 [1024/10284]	Loss: 0.2014	LR: 0.020000
Training Epoch: 18 [1280/10284]	Loss: 0.1952	LR: 0.020000
Training Epoch: 18 [1536/10284]	Loss: 0.1992	LR: 0.020000
Training Epoch: 18 [1792/10284]	Loss: 0.1502	LR: 0.020000
Training Epoch: 18 [2048/10284]	Loss: 0.1676	LR: 0.020000
Training Epoch: 18 [2304/10284]	Loss: 0.2136	LR: 0.020000
Training Epoch: 18 [2560/10284]	Loss: 0.1709	LR: 0.020000
Training Epoch: 18 [2816/10284]	Loss: 0.1653	LR: 0.020000
Training Epoch: 18 [3072/10284]	Loss: 0.1959	LR: 0.020000
Training Epoch: 18 [3328/10284]	Loss: 0.2341	LR: 0.020000
Training Epoch: 18 [3584/10284]	Loss: 0.1790	LR: 0.020000
Training Epoch: 18 [3840/10284]	Loss: 0.1620	LR: 0.020000
Training Epoch: 18 [4096/10284]	Loss: 0.1956	LR: 0.020000
Training Epoch: 18 [4352/10284]	Loss: 0.2276	LR: 0.020000
Training Epoch: 18 [4608/10284]	Loss: 0.1838	LR: 0.020000
Training Epoch: 18 [4864/10284]	Loss: 0.1109	LR: 0.020000
Training Epoch: 18 [5120/10284]	Loss: 0.2447	LR: 0.020000
Training Epoch: 18 [5376/10284]	Loss: 0.2011	LR: 0.020000
Training Epoch: 18 [5632/10284]	Loss: 0.1671	LR: 0.020000
Training Epoch: 18 [5888/10284]	Loss: 0.1213	LR: 0.020000
Training Epoch: 18 [6144/10284]	Loss: 0.1718	LR: 0.020000
Training Epoch: 18 [6400/10284]	Loss: 0.1717	LR: 0.020000
Training Epoch: 18 [6656/10284]	Loss: 0.1882	LR: 0.020000
Training Epoch: 18 [6912/10284]	Loss: 0.1171	LR: 0.020000
Training Epoch: 18 [7168/10284]	Loss: 0.1957	LR: 0.020000
Training Epoch: 18 [7424/10284]	Loss: 0.1763	LR: 0.020000
Training Epoch: 18 [7680/10284]	Loss: 0.1791	LR: 0.020000
Training Epoch: 18 [7936/10284]	Loss: 0.2511	LR: 0.020000
Training Epoch: 18 [8192/10284]	Loss: 0.1701	LR: 0.020000
Training Epoch: 18 [8448/10284]	Loss: 0.2137	LR: 0.020000
Training Epoch: 18 [8704/10284]	Loss: 0.1575	LR: 0.020000
Training Epoch: 18 [8960/10284]	Loss: 0.1473	LR: 0.020000
Training Epoch: 18 [9216/10284]	Loss: 0.1849	LR: 0.020000
Training Epoch: 18 [9472/10284]	Loss: 0.1728	LR: 0.020000
Training Epoch: 18 [9728/10284]	Loss: 0.2661	LR: 0.020000
Training Epoch: 18 [9984/10284]	Loss: 0.1072	LR: 0.020000
Training Epoch: 18 [10240/10284]	Loss: 0.1587	LR: 0.020000
Training Epoch: 18 [10284/10284]	Loss: 0.1061	LR: 0.020000
Epoch 18 - Average Train Loss: 0.1803, Train Accuracy: 0.9302
Epoch 18 training time consumed: 148.35s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0007, Accuracy: 0.9317, Time consumed:8.27s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-18-best.pth
Training Epoch: 19 [256/10284]	Loss: 0.1877	LR: 0.020000
Training Epoch: 19 [512/10284]	Loss: 0.1805	LR: 0.020000
Training Epoch: 19 [768/10284]	Loss: 0.1429	LR: 0.020000
Training Epoch: 19 [1024/10284]	Loss: 0.1341	LR: 0.020000
Training Epoch: 19 [1280/10284]	Loss: 0.1780	LR: 0.020000
Training Epoch: 19 [1536/10284]	Loss: 0.1699	LR: 0.020000
Training Epoch: 19 [1792/10284]	Loss: 0.1909	LR: 0.020000
Training Epoch: 19 [2048/10284]	Loss: 0.1512	LR: 0.020000
Training Epoch: 19 [2304/10284]	Loss: 0.1553	LR: 0.020000
Training Epoch: 19 [2560/10284]	Loss: 0.2004	LR: 0.020000
Training Epoch: 19 [2816/10284]	Loss: 0.1642	LR: 0.020000
Training Epoch: 19 [3072/10284]	Loss: 0.2090	LR: 0.020000
Training Epoch: 19 [3328/10284]	Loss: 0.1713	LR: 0.020000
Training Epoch: 19 [3584/10284]	Loss: 0.1411	LR: 0.020000
Training Epoch: 19 [3840/10284]	Loss: 0.1881	LR: 0.020000
Training Epoch: 19 [4096/10284]	Loss: 0.2322	LR: 0.020000
Training Epoch: 19 [4352/10284]	Loss: 0.1988	LR: 0.020000
Training Epoch: 19 [4608/10284]	Loss: 0.1745	LR: 0.020000
Training Epoch: 19 [4864/10284]	Loss: 0.1951	LR: 0.020000
Training Epoch: 19 [5120/10284]	Loss: 0.1631	LR: 0.020000
Training Epoch: 19 [5376/10284]	Loss: 0.1646	LR: 0.020000
Training Epoch: 19 [5632/10284]	Loss: 0.1269	LR: 0.020000
Training Epoch: 19 [5888/10284]	Loss: 0.2121	LR: 0.020000
Training Epoch: 19 [6144/10284]	Loss: 0.2013	LR: 0.020000
Training Epoch: 19 [6400/10284]	Loss: 0.1660	LR: 0.020000
Training Epoch: 19 [6656/10284]	Loss: 0.1291	LR: 0.020000
Training Epoch: 19 [6912/10284]	Loss: 0.1866	LR: 0.020000
Training Epoch: 19 [7168/10284]	Loss: 0.2259	LR: 0.020000
Training Epoch: 19 [7424/10284]	Loss: 0.2245	LR: 0.020000
Training Epoch: 19 [7680/10284]	Loss: 0.1675	LR: 0.020000
Training Epoch: 19 [7936/10284]	Loss: 0.1435	LR: 0.020000
Training Epoch: 19 [8192/10284]	Loss: 0.1514	LR: 0.020000
Training Epoch: 19 [8448/10284]	Loss: 0.1684	LR: 0.020000
Training Epoch: 19 [8704/10284]	Loss: 0.1487	LR: 0.020000
Training Epoch: 19 [8960/10284]	Loss: 0.1633	LR: 0.020000
Training Epoch: 19 [9216/10284]	Loss: 0.1408	LR: 0.020000
Training Epoch: 19 [9472/10284]	Loss: 0.1562	LR: 0.020000
Training Epoch: 19 [9728/10284]	Loss: 0.1499	LR: 0.020000
Training Epoch: 19 [9984/10284]	Loss: 0.1743	LR: 0.020000
Training Epoch: 19 [10240/10284]	Loss: 0.1446	LR: 0.020000
Training Epoch: 19 [10284/10284]	Loss: 0.0915	LR: 0.020000
Epoch 19 - Average Train Loss: 0.1715, Train Accuracy: 0.9304
Epoch 19 training time consumed: 148.53s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0007, Accuracy: 0.9356, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-19-best.pth
Training Epoch: 20 [256/10284]	Loss: 0.1448	LR: 0.004000
Training Epoch: 20 [512/10284]	Loss: 0.1375	LR: 0.004000
Training Epoch: 20 [768/10284]	Loss: 0.1693	LR: 0.004000
Training Epoch: 20 [1024/10284]	Loss: 0.1493	LR: 0.004000
Training Epoch: 20 [1280/10284]	Loss: 0.1788	LR: 0.004000
Training Epoch: 20 [1536/10284]	Loss: 0.1402	LR: 0.004000
Training Epoch: 20 [1792/10284]	Loss: 0.1393	LR: 0.004000
Training Epoch: 20 [2048/10284]	Loss: 0.1609	LR: 0.004000
Training Epoch: 20 [2304/10284]	Loss: 0.1103	LR: 0.004000
Training Epoch: 20 [2560/10284]	Loss: 0.1187	LR: 0.004000
Training Epoch: 20 [2816/10284]	Loss: 0.1582	LR: 0.004000
Training Epoch: 20 [3072/10284]	Loss: 0.1478	LR: 0.004000
Training Epoch: 20 [3328/10284]	Loss: 0.1436	LR: 0.004000
Training Epoch: 20 [3584/10284]	Loss: 0.1452	LR: 0.004000
Training Epoch: 20 [3840/10284]	Loss: 0.1602	LR: 0.004000
Training Epoch: 20 [4096/10284]	Loss: 0.1922	LR: 0.004000
Training Epoch: 20 [4352/10284]	Loss: 0.1572	LR: 0.004000
Training Epoch: 20 [4608/10284]	Loss: 0.1191	LR: 0.004000
Training Epoch: 20 [4864/10284]	Loss: 0.1431	LR: 0.004000
Training Epoch: 20 [5120/10284]	Loss: 0.1742	LR: 0.004000
Training Epoch: 20 [5376/10284]	Loss: 0.0986	LR: 0.004000
Training Epoch: 20 [5632/10284]	Loss: 0.1423	LR: 0.004000
Training Epoch: 20 [5888/10284]	Loss: 0.1497	LR: 0.004000
Training Epoch: 20 [6144/10284]	Loss: 0.1511	LR: 0.004000
Training Epoch: 20 [6400/10284]	Loss: 0.2135	LR: 0.004000
Training Epoch: 20 [6656/10284]	Loss: 0.2139	LR: 0.004000
Training Epoch: 20 [6912/10284]	Loss: 0.1117	LR: 0.004000
Training Epoch: 20 [7168/10284]	Loss: 0.1521	LR: 0.004000
Training Epoch: 20 [7424/10284]	Loss: 0.1429	LR: 0.004000
Training Epoch: 20 [7680/10284]	Loss: 0.1215	LR: 0.004000
Training Epoch: 20 [7936/10284]	Loss: 0.1593	LR: 0.004000
Training Epoch: 20 [8192/10284]	Loss: 0.1928	LR: 0.004000
Training Epoch: 20 [8448/10284]	Loss: 0.1096	LR: 0.004000
Training Epoch: 20 [8704/10284]	Loss: 0.1491	LR: 0.004000
Training Epoch: 20 [8960/10284]	Loss: 0.1251	LR: 0.004000
Training Epoch: 20 [9216/10284]	Loss: 0.1376	LR: 0.004000
Training Epoch: 20 [9472/10284]	Loss: 0.1766	LR: 0.004000
Training Epoch: 20 [9728/10284]	Loss: 0.1582	LR: 0.004000
Training Epoch: 20 [9984/10284]	Loss: 0.1711	LR: 0.004000
Training Epoch: 20 [10240/10284]	Loss: 0.1617	LR: 0.004000
Training Epoch: 20 [10284/10284]	Loss: 0.2828	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1513, Train Accuracy: 0.9388
Epoch 20 training time consumed: 148.18s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0006, Accuracy: 0.9419, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-20-best.pth
Training Epoch: 21 [256/10284]	Loss: 0.1225	LR: 0.004000
Training Epoch: 21 [512/10284]	Loss: 0.1357	LR: 0.004000
Training Epoch: 21 [768/10284]	Loss: 0.1410	LR: 0.004000
Training Epoch: 21 [1024/10284]	Loss: 0.1760	LR: 0.004000
Training Epoch: 21 [1280/10284]	Loss: 0.2293	LR: 0.004000
Training Epoch: 21 [1536/10284]	Loss: 0.1699	LR: 0.004000
Training Epoch: 21 [1792/10284]	Loss: 0.1436	LR: 0.004000
Training Epoch: 21 [2048/10284]	Loss: 0.1446	LR: 0.004000
Training Epoch: 21 [2304/10284]	Loss: 0.1241	LR: 0.004000
Training Epoch: 21 [2560/10284]	Loss: 0.1171	LR: 0.004000
Training Epoch: 21 [2816/10284]	Loss: 0.1269	LR: 0.004000
Training Epoch: 21 [3072/10284]	Loss: 0.1805	LR: 0.004000
Training Epoch: 21 [3328/10284]	Loss: 0.1034	LR: 0.004000
Training Epoch: 21 [3584/10284]	Loss: 0.1559	LR: 0.004000
Training Epoch: 21 [3840/10284]	Loss: 0.1610	LR: 0.004000
Training Epoch: 21 [4096/10284]	Loss: 0.1397	LR: 0.004000
Training Epoch: 21 [4352/10284]	Loss: 0.2198	LR: 0.004000
Training Epoch: 21 [4608/10284]	Loss: 0.1693	LR: 0.004000
Training Epoch: 21 [4864/10284]	Loss: 0.1578	LR: 0.004000
Training Epoch: 21 [5120/10284]	Loss: 0.1098	LR: 0.004000
Training Epoch: 21 [5376/10284]	Loss: 0.1652	LR: 0.004000
Training Epoch: 21 [5632/10284]	Loss: 0.1526	LR: 0.004000
Training Epoch: 21 [5888/10284]	Loss: 0.1402	LR: 0.004000
Training Epoch: 21 [6144/10284]	Loss: 0.1186	LR: 0.004000
Training Epoch: 21 [6400/10284]	Loss: 0.1513	LR: 0.004000
Training Epoch: 21 [6656/10284]	Loss: 0.1395	LR: 0.004000
Training Epoch: 21 [6912/10284]	Loss: 0.1222	LR: 0.004000
Training Epoch: 21 [7168/10284]	Loss: 0.1203	LR: 0.004000
Training Epoch: 21 [7424/10284]	Loss: 0.1682	LR: 0.004000
Training Epoch: 21 [7680/10284]	Loss: 0.1018	LR: 0.004000
Training Epoch: 21 [7936/10284]	Loss: 0.1420	LR: 0.004000
Training Epoch: 21 [8192/10284]	Loss: 0.1030	LR: 0.004000
Training Epoch: 21 [8448/10284]	Loss: 0.1608	LR: 0.004000
Training Epoch: 21 [8704/10284]	Loss: 0.1189	LR: 0.004000
Training Epoch: 21 [8960/10284]	Loss: 0.1561	LR: 0.004000
Training Epoch: 21 [9216/10284]	Loss: 0.1488	LR: 0.004000
Training Epoch: 21 [9472/10284]	Loss: 0.1565	LR: 0.004000
Training Epoch: 21 [9728/10284]	Loss: 0.1274	LR: 0.004000
Training Epoch: 21 [9984/10284]	Loss: 0.1078	LR: 0.004000
Training Epoch: 21 [10240/10284]	Loss: 0.1318	LR: 0.004000
Training Epoch: 21 [10284/10284]	Loss: 0.1877	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1442, Train Accuracy: 0.9401
Epoch 21 training time consumed: 148.50s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0006, Accuracy: 0.9433, Time consumed:7.91s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-21-best.pth
Training Epoch: 22 [256/10284]	Loss: 0.1133	LR: 0.004000
Training Epoch: 22 [512/10284]	Loss: 0.1181	LR: 0.004000
Training Epoch: 22 [768/10284]	Loss: 0.1502	LR: 0.004000
Training Epoch: 22 [1024/10284]	Loss: 0.1414	LR: 0.004000
Training Epoch: 22 [1280/10284]	Loss: 0.2040	LR: 0.004000
Training Epoch: 22 [1536/10284]	Loss: 0.1386	LR: 0.004000
Training Epoch: 22 [1792/10284]	Loss: 0.1048	LR: 0.004000
Training Epoch: 22 [2048/10284]	Loss: 0.1355	LR: 0.004000
Training Epoch: 22 [2304/10284]	Loss: 0.1262	LR: 0.004000
Training Epoch: 22 [2560/10284]	Loss: 0.1578	LR: 0.004000
Training Epoch: 22 [2816/10284]	Loss: 0.1183	LR: 0.004000
Training Epoch: 22 [3072/10284]	Loss: 0.1328	LR: 0.004000
Training Epoch: 22 [3328/10284]	Loss: 0.1373	LR: 0.004000
Training Epoch: 22 [3584/10284]	Loss: 0.1134	LR: 0.004000
Training Epoch: 22 [3840/10284]	Loss: 0.1917	LR: 0.004000
Training Epoch: 22 [4096/10284]	Loss: 0.1454	LR: 0.004000
Training Epoch: 22 [4352/10284]	Loss: 0.0856	LR: 0.004000
Training Epoch: 22 [4608/10284]	Loss: 0.1310	LR: 0.004000
Training Epoch: 22 [4864/10284]	Loss: 0.1116	LR: 0.004000
Training Epoch: 22 [5120/10284]	Loss: 0.0998	LR: 0.004000
Training Epoch: 22 [5376/10284]	Loss: 0.1197	LR: 0.004000
Training Epoch: 22 [5632/10284]	Loss: 0.1387	LR: 0.004000
Training Epoch: 22 [5888/10284]	Loss: 0.1044	LR: 0.004000
Training Epoch: 22 [6144/10284]	Loss: 0.1438	LR: 0.004000
Training Epoch: 22 [6400/10284]	Loss: 0.1925	LR: 0.004000
Training Epoch: 22 [6656/10284]	Loss: 0.1839	LR: 0.004000
Training Epoch: 22 [6912/10284]	Loss: 0.1231	LR: 0.004000
Training Epoch: 22 [7168/10284]	Loss: 0.1306	LR: 0.004000
Training Epoch: 22 [7424/10284]	Loss: 0.1358	LR: 0.004000
Training Epoch: 22 [7680/10284]	Loss: 0.1481	LR: 0.004000
Training Epoch: 22 [7936/10284]	Loss: 0.2700	LR: 0.004000
Training Epoch: 22 [8192/10284]	Loss: 0.1782	LR: 0.004000
Training Epoch: 22 [8448/10284]	Loss: 0.1436	LR: 0.004000
Training Epoch: 22 [8704/10284]	Loss: 0.1569	LR: 0.004000
Training Epoch: 22 [8960/10284]	Loss: 0.1437	LR: 0.004000
Training Epoch: 22 [9216/10284]	Loss: 0.1586	LR: 0.004000
Training Epoch: 22 [9472/10284]	Loss: 0.1164	LR: 0.004000
Training Epoch: 22 [9728/10284]	Loss: 0.1549	LR: 0.004000
Training Epoch: 22 [9984/10284]	Loss: 0.1143	LR: 0.004000
Training Epoch: 22 [10240/10284]	Loss: 0.1223	LR: 0.004000
Training Epoch: 22 [10284/10284]	Loss: 0.2348	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1413, Train Accuracy: 0.9411
Epoch 22 training time consumed: 148.90s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0006, Accuracy: 0.9433, Time consumed:7.93s
Training Epoch: 23 [256/10284]	Loss: 0.0986	LR: 0.004000
Training Epoch: 23 [512/10284]	Loss: 0.1028	LR: 0.004000
Training Epoch: 23 [768/10284]	Loss: 0.1338	LR: 0.004000
Training Epoch: 23 [1024/10284]	Loss: 0.1328	LR: 0.004000
Training Epoch: 23 [1280/10284]	Loss: 0.1025	LR: 0.004000
Training Epoch: 23 [1536/10284]	Loss: 0.1654	LR: 0.004000
Training Epoch: 23 [1792/10284]	Loss: 0.1798	LR: 0.004000
Training Epoch: 23 [2048/10284]	Loss: 0.1263	LR: 0.004000
Training Epoch: 23 [2304/10284]	Loss: 0.1321	LR: 0.004000
Training Epoch: 23 [2560/10284]	Loss: 0.1069	LR: 0.004000
Training Epoch: 23 [2816/10284]	Loss: 0.0983	LR: 0.004000
Training Epoch: 23 [3072/10284]	Loss: 0.1407	LR: 0.004000
Training Epoch: 23 [3328/10284]	Loss: 0.1366	LR: 0.004000
Training Epoch: 23 [3584/10284]	Loss: 0.1415	LR: 0.004000
Training Epoch: 23 [3840/10284]	Loss: 0.1410	LR: 0.004000
Training Epoch: 23 [4096/10284]	Loss: 0.1530	LR: 0.004000
Training Epoch: 23 [4352/10284]	Loss: 0.1298	LR: 0.004000
Training Epoch: 23 [4608/10284]	Loss: 0.1626	LR: 0.004000
Training Epoch: 23 [4864/10284]	Loss: 0.1340	LR: 0.004000
Training Epoch: 23 [5120/10284]	Loss: 0.1393	LR: 0.004000
Training Epoch: 23 [5376/10284]	Loss: 0.1195	LR: 0.004000
Training Epoch: 23 [5632/10284]	Loss: 0.1850	LR: 0.004000
Training Epoch: 23 [5888/10284]	Loss: 0.1305	LR: 0.004000
Training Epoch: 23 [6144/10284]	Loss: 0.1476	LR: 0.004000
Training Epoch: 23 [6400/10284]	Loss: 0.1009	LR: 0.004000
Training Epoch: 23 [6656/10284]	Loss: 0.1500	LR: 0.004000
Training Epoch: 23 [6912/10284]	Loss: 0.1238	LR: 0.004000
Training Epoch: 23 [7168/10284]	Loss: 0.1271	LR: 0.004000
Training Epoch: 23 [7424/10284]	Loss: 0.1345	LR: 0.004000
Training Epoch: 23 [7680/10284]	Loss: 0.2127	LR: 0.004000
Training Epoch: 23 [7936/10284]	Loss: 0.1565	LR: 0.004000
Training Epoch: 23 [8192/10284]	Loss: 0.1377	LR: 0.004000
Training Epoch: 23 [8448/10284]	Loss: 0.1220	LR: 0.004000
Training Epoch: 23 [8704/10284]	Loss: 0.0986	LR: 0.004000
Training Epoch: 23 [8960/10284]	Loss: 0.1546	LR: 0.004000
Training Epoch: 23 [9216/10284]	Loss: 0.1495	LR: 0.004000
Training Epoch: 23 [9472/10284]	Loss: 0.1639	LR: 0.004000
Training Epoch: 23 [9728/10284]	Loss: 0.1430	LR: 0.004000
Training Epoch: 23 [9984/10284]	Loss: 0.1397	LR: 0.004000
Training Epoch: 23 [10240/10284]	Loss: 0.1713	LR: 0.004000
Training Epoch: 23 [10284/10284]	Loss: 0.1646	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1383, Train Accuracy: 0.9449
Epoch 23 training time consumed: 148.52s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9453, Time consumed:7.95s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-23-best.pth
Training Epoch: 24 [256/10284]	Loss: 0.1432	LR: 0.004000
Training Epoch: 24 [512/10284]	Loss: 0.1184	LR: 0.004000
Training Epoch: 24 [768/10284]	Loss: 0.1403	LR: 0.004000
Training Epoch: 24 [1024/10284]	Loss: 0.1033	LR: 0.004000
Training Epoch: 24 [1280/10284]	Loss: 0.1074	LR: 0.004000
Training Epoch: 24 [1536/10284]	Loss: 0.1273	LR: 0.004000
Training Epoch: 24 [1792/10284]	Loss: 0.1972	LR: 0.004000
Training Epoch: 24 [2048/10284]	Loss: 0.1244	LR: 0.004000
Training Epoch: 24 [2304/10284]	Loss: 0.1538	LR: 0.004000
Training Epoch: 24 [2560/10284]	Loss: 0.1302	LR: 0.004000
Training Epoch: 24 [2816/10284]	Loss: 0.1066	LR: 0.004000
Training Epoch: 24 [3072/10284]	Loss: 0.1397	LR: 0.004000
Training Epoch: 24 [3328/10284]	Loss: 0.1537	LR: 0.004000
Training Epoch: 24 [3584/10284]	Loss: 0.1039	LR: 0.004000
Training Epoch: 24 [3840/10284]	Loss: 0.0857	LR: 0.004000
Training Epoch: 24 [4096/10284]	Loss: 0.0991	LR: 0.004000
Training Epoch: 24 [4352/10284]	Loss: 0.1002	LR: 0.004000
Training Epoch: 24 [4608/10284]	Loss: 0.1384	LR: 0.004000
Training Epoch: 24 [4864/10284]	Loss: 0.1424	LR: 0.004000
Training Epoch: 24 [5120/10284]	Loss: 0.1664	LR: 0.004000
Training Epoch: 24 [5376/10284]	Loss: 0.1697	LR: 0.004000
Training Epoch: 24 [5632/10284]	Loss: 0.1256	LR: 0.004000
Training Epoch: 24 [5888/10284]	Loss: 0.1278	LR: 0.004000
Training Epoch: 24 [6144/10284]	Loss: 0.1247	LR: 0.004000
Training Epoch: 24 [6400/10284]	Loss: 0.2285	LR: 0.004000
Training Epoch: 24 [6656/10284]	Loss: 0.1579	LR: 0.004000
Training Epoch: 24 [6912/10284]	Loss: 0.1436	LR: 0.004000
Training Epoch: 24 [7168/10284]	Loss: 0.1335	LR: 0.004000
Training Epoch: 24 [7424/10284]	Loss: 0.1222	LR: 0.004000
Training Epoch: 24 [7680/10284]	Loss: 0.1147	LR: 0.004000
Training Epoch: 24 [7936/10284]	Loss: 0.1129	LR: 0.004000
Training Epoch: 24 [8192/10284]	Loss: 0.1095	LR: 0.004000
Training Epoch: 24 [8448/10284]	Loss: 0.1237	LR: 0.004000
Training Epoch: 24 [8704/10284]	Loss: 0.1281	LR: 0.004000
Training Epoch: 24 [8960/10284]	Loss: 0.1427	LR: 0.004000
Training Epoch: 24 [9216/10284]	Loss: 0.1352	LR: 0.004000
Training Epoch: 24 [9472/10284]	Loss: 0.1732	LR: 0.004000
Training Epoch: 24 [9728/10284]	Loss: 0.1583	LR: 0.004000
Training Epoch: 24 [9984/10284]	Loss: 0.1360	LR: 0.004000
Training Epoch: 24 [10240/10284]	Loss: 0.1039	LR: 0.004000
Training Epoch: 24 [10284/10284]	Loss: 0.1939	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1341, Train Accuracy: 0.9444
Epoch 24 training time consumed: 148.22s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0007, Accuracy: 0.9337, Time consumed:7.91s
Training Epoch: 25 [256/10284]	Loss: 0.1181	LR: 0.004000
Training Epoch: 25 [512/10284]	Loss: 0.1158	LR: 0.004000
Training Epoch: 25 [768/10284]	Loss: 0.1168	LR: 0.004000
Training Epoch: 25 [1024/10284]	Loss: 0.1747	LR: 0.004000
Training Epoch: 25 [1280/10284]	Loss: 0.0996	LR: 0.004000
Training Epoch: 25 [1536/10284]	Loss: 0.1230	LR: 0.004000
Training Epoch: 25 [1792/10284]	Loss: 0.0854	LR: 0.004000
Training Epoch: 25 [2048/10284]	Loss: 0.1117	LR: 0.004000
Training Epoch: 25 [2304/10284]	Loss: 0.1277	LR: 0.004000
Training Epoch: 25 [2560/10284]	Loss: 0.1465	LR: 0.004000
Training Epoch: 25 [2816/10284]	Loss: 0.0737	LR: 0.004000
Training Epoch: 25 [3072/10284]	Loss: 0.1563	LR: 0.004000
Training Epoch: 25 [3328/10284]	Loss: 0.1313	LR: 0.004000
Training Epoch: 25 [3584/10284]	Loss: 0.1646	LR: 0.004000
Training Epoch: 25 [3840/10284]	Loss: 0.1222	LR: 0.004000
Training Epoch: 25 [4096/10284]	Loss: 0.1236	LR: 0.004000
Training Epoch: 25 [4352/10284]	Loss: 0.1274	LR: 0.004000
Training Epoch: 25 [4608/10284]	Loss: 0.1189	LR: 0.004000
Training Epoch: 25 [4864/10284]	Loss: 0.2060	LR: 0.004000
Training Epoch: 25 [5120/10284]	Loss: 0.1193	LR: 0.004000
Training Epoch: 25 [5376/10284]	Loss: 0.1269	LR: 0.004000
Training Epoch: 25 [5632/10284]	Loss: 0.1631	LR: 0.004000
Training Epoch: 25 [5888/10284]	Loss: 0.1265	LR: 0.004000
Training Epoch: 25 [6144/10284]	Loss: 0.0950	LR: 0.004000
Training Epoch: 25 [6400/10284]	Loss: 0.1138	LR: 0.004000
Training Epoch: 25 [6656/10284]	Loss: 0.1448	LR: 0.004000
Training Epoch: 25 [6912/10284]	Loss: 0.1184	LR: 0.004000
Training Epoch: 25 [7168/10284]	Loss: 0.1237	LR: 0.004000
Training Epoch: 25 [7424/10284]	Loss: 0.0957	LR: 0.004000
Training Epoch: 25 [7680/10284]	Loss: 0.1659	LR: 0.004000
Training Epoch: 25 [7936/10284]	Loss: 0.1482	LR: 0.004000
Training Epoch: 25 [8192/10284]	Loss: 0.1059	LR: 0.004000
Training Epoch: 25 [8448/10284]	Loss: 0.1066	LR: 0.004000
Training Epoch: 25 [8704/10284]	Loss: 0.1106	LR: 0.004000
Training Epoch: 25 [8960/10284]	Loss: 0.1132	LR: 0.004000
Training Epoch: 25 [9216/10284]	Loss: 0.1427	LR: 0.004000
Training Epoch: 25 [9472/10284]	Loss: 0.0978	LR: 0.004000
Training Epoch: 25 [9728/10284]	Loss: 0.1408	LR: 0.004000
Training Epoch: 25 [9984/10284]	Loss: 0.1552	LR: 0.004000
Training Epoch: 25 [10240/10284]	Loss: 0.1014	LR: 0.004000
Training Epoch: 25 [10284/10284]	Loss: 0.0492	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1261, Train Accuracy: 0.9478
Epoch 25 training time consumed: 148.18s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9438, Time consumed:7.99s
Training Epoch: 26 [256/10284]	Loss: 0.1200	LR: 0.004000
Training Epoch: 26 [512/10284]	Loss: 0.1301	LR: 0.004000
Training Epoch: 26 [768/10284]	Loss: 0.0993	LR: 0.004000
Training Epoch: 26 [1024/10284]	Loss: 0.1432	LR: 0.004000
Training Epoch: 26 [1280/10284]	Loss: 0.1027	LR: 0.004000
Training Epoch: 26 [1536/10284]	Loss: 0.1742	LR: 0.004000
Training Epoch: 26 [1792/10284]	Loss: 0.1410	LR: 0.004000
Training Epoch: 26 [2048/10284]	Loss: 0.1108	LR: 0.004000
Training Epoch: 26 [2304/10284]	Loss: 0.1740	LR: 0.004000
Training Epoch: 26 [2560/10284]	Loss: 0.1147	LR: 0.004000
Training Epoch: 26 [2816/10284]	Loss: 0.1152	LR: 0.004000
Training Epoch: 26 [3072/10284]	Loss: 0.0819	LR: 0.004000
Training Epoch: 26 [3328/10284]	Loss: 0.1290	LR: 0.004000
Training Epoch: 26 [3584/10284]	Loss: 0.1341	LR: 0.004000
Training Epoch: 26 [3840/10284]	Loss: 0.1438	LR: 0.004000
Training Epoch: 26 [4096/10284]	Loss: 0.1444	LR: 0.004000
Training Epoch: 26 [4352/10284]	Loss: 0.1584	LR: 0.004000
Training Epoch: 26 [4608/10284]	Loss: 0.0922	LR: 0.004000
Training Epoch: 26 [4864/10284]	Loss: 0.1372	LR: 0.004000
Training Epoch: 26 [5120/10284]	Loss: 0.1426	LR: 0.004000
Training Epoch: 26 [5376/10284]	Loss: 0.0986	LR: 0.004000
Training Epoch: 26 [5632/10284]	Loss: 0.1170	LR: 0.004000
Training Epoch: 26 [5888/10284]	Loss: 0.0734	LR: 0.004000
Training Epoch: 26 [6144/10284]	Loss: 0.1387	LR: 0.004000
Training Epoch: 26 [6400/10284]	Loss: 0.1664	LR: 0.004000
Training Epoch: 26 [6656/10284]	Loss: 0.1284	LR: 0.004000
Training Epoch: 26 [6912/10284]	Loss: 0.0687	LR: 0.004000
Training Epoch: 26 [7168/10284]	Loss: 0.1316	LR: 0.004000
Training Epoch: 26 [7424/10284]	Loss: 0.1219	LR: 0.004000
Training Epoch: 26 [7680/10284]	Loss: 0.1187	LR: 0.004000
Training Epoch: 26 [7936/10284]	Loss: 0.1808	LR: 0.004000
Training Epoch: 26 [8192/10284]	Loss: 0.1238	LR: 0.004000
Training Epoch: 26 [8448/10284]	Loss: 0.1493	LR: 0.004000
Training Epoch: 26 [8704/10284]	Loss: 0.1372	LR: 0.004000
Training Epoch: 26 [8960/10284]	Loss: 0.1380	LR: 0.004000
Training Epoch: 26 [9216/10284]	Loss: 0.1437	LR: 0.004000
Training Epoch: 26 [9472/10284]	Loss: 0.1623	LR: 0.004000
Training Epoch: 26 [9728/10284]	Loss: 0.1108	LR: 0.004000
Training Epoch: 26 [9984/10284]	Loss: 0.1095	LR: 0.004000
Training Epoch: 26 [10240/10284]	Loss: 0.1347	LR: 0.004000
Training Epoch: 26 [10284/10284]	Loss: 0.2515	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1291, Train Accuracy: 0.9478
Epoch 26 training time consumed: 148.07s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9448, Time consumed:8.04s
Training Epoch: 27 [256/10284]	Loss: 0.1194	LR: 0.004000
Training Epoch: 27 [512/10284]	Loss: 0.1275	LR: 0.004000
Training Epoch: 27 [768/10284]	Loss: 0.1215	LR: 0.004000
Training Epoch: 27 [1024/10284]	Loss: 0.1366	LR: 0.004000
Training Epoch: 27 [1280/10284]	Loss: 0.1272	LR: 0.004000
Training Epoch: 27 [1536/10284]	Loss: 0.0925	LR: 0.004000
Training Epoch: 27 [1792/10284]	Loss: 0.1104	LR: 0.004000
Training Epoch: 27 [2048/10284]	Loss: 0.1550	LR: 0.004000
Training Epoch: 27 [2304/10284]	Loss: 0.1381	LR: 0.004000
Training Epoch: 27 [2560/10284]	Loss: 0.2096	LR: 0.004000
Training Epoch: 27 [2816/10284]	Loss: 0.1927	LR: 0.004000
Training Epoch: 27 [3072/10284]	Loss: 0.1115	LR: 0.004000
Training Epoch: 27 [3328/10284]	Loss: 0.1301	LR: 0.004000
Training Epoch: 27 [3584/10284]	Loss: 0.1519	LR: 0.004000
Training Epoch: 27 [3840/10284]	Loss: 0.1255	LR: 0.004000
Training Epoch: 27 [4096/10284]	Loss: 0.1108	LR: 0.004000
Training Epoch: 27 [4352/10284]	Loss: 0.1080	LR: 0.004000
Training Epoch: 27 [4608/10284]	Loss: 0.1469	LR: 0.004000
Training Epoch: 27 [4864/10284]	Loss: 0.1411	LR: 0.004000
Training Epoch: 27 [5120/10284]	Loss: 0.0938	LR: 0.004000
Training Epoch: 27 [5376/10284]	Loss: 0.1390	LR: 0.004000
Training Epoch: 27 [5632/10284]	Loss: 0.1435	LR: 0.004000
Training Epoch: 27 [5888/10284]	Loss: 0.0819	LR: 0.004000
Training Epoch: 27 [6144/10284]	Loss: 0.1322	LR: 0.004000
Training Epoch: 27 [6400/10284]	Loss: 0.1091	LR: 0.004000
Training Epoch: 27 [6656/10284]	Loss: 0.1974	LR: 0.004000
Training Epoch: 27 [6912/10284]	Loss: 0.1392	LR: 0.004000
Training Epoch: 27 [7168/10284]	Loss: 0.1302	LR: 0.004000
Training Epoch: 27 [7424/10284]	Loss: 0.0978	LR: 0.004000
Training Epoch: 27 [7680/10284]	Loss: 0.1470	LR: 0.004000
Training Epoch: 27 [7936/10284]	Loss: 0.0895	LR: 0.004000
Training Epoch: 27 [8192/10284]	Loss: 0.1282	LR: 0.004000
Training Epoch: 27 [8448/10284]	Loss: 0.1028	LR: 0.004000
Training Epoch: 27 [8704/10284]	Loss: 0.1454	LR: 0.004000
Training Epoch: 27 [8960/10284]	Loss: 0.1578	LR: 0.004000
Training Epoch: 27 [9216/10284]	Loss: 0.1188	LR: 0.004000
Training Epoch: 27 [9472/10284]	Loss: 0.1092	LR: 0.004000
Training Epoch: 27 [9728/10284]	Loss: 0.1473	LR: 0.004000
Training Epoch: 27 [9984/10284]	Loss: 0.1286	LR: 0.004000
Training Epoch: 27 [10240/10284]	Loss: 0.1075	LR: 0.004000
Training Epoch: 27 [10284/10284]	Loss: 0.1369	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1301, Train Accuracy: 0.9462
Epoch 27 training time consumed: 148.19s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9458, Time consumed:8.11s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-27-best.pth
Training Epoch: 28 [256/10284]	Loss: 0.1268	LR: 0.004000
Training Epoch: 28 [512/10284]	Loss: 0.1257	LR: 0.004000
Training Epoch: 28 [768/10284]	Loss: 0.1150	LR: 0.004000
Training Epoch: 28 [1024/10284]	Loss: 0.0954	LR: 0.004000
Training Epoch: 28 [1280/10284]	Loss: 0.0995	LR: 0.004000
Training Epoch: 28 [1536/10284]	Loss: 0.1374	LR: 0.004000
Training Epoch: 28 [1792/10284]	Loss: 0.0947	LR: 0.004000
Training Epoch: 28 [2048/10284]	Loss: 0.1554	LR: 0.004000
Training Epoch: 28 [2304/10284]	Loss: 0.1709	LR: 0.004000
Training Epoch: 28 [2560/10284]	Loss: 0.1232	LR: 0.004000
Training Epoch: 28 [2816/10284]	Loss: 0.1324	LR: 0.004000
Training Epoch: 28 [3072/10284]	Loss: 0.1245	LR: 0.004000
Training Epoch: 28 [3328/10284]	Loss: 0.1189	LR: 0.004000
Training Epoch: 28 [3584/10284]	Loss: 0.0970	LR: 0.004000
Training Epoch: 28 [3840/10284]	Loss: 0.1316	LR: 0.004000
Training Epoch: 28 [4096/10284]	Loss: 0.1171	LR: 0.004000
Training Epoch: 28 [4352/10284]	Loss: 0.1229	LR: 0.004000
Training Epoch: 28 [4608/10284]	Loss: 0.1166	LR: 0.004000
Training Epoch: 28 [4864/10284]	Loss: 0.2033	LR: 0.004000
Training Epoch: 28 [5120/10284]	Loss: 0.1161	LR: 0.004000
Training Epoch: 28 [5376/10284]	Loss: 0.1323	LR: 0.004000
Training Epoch: 28 [5632/10284]	Loss: 0.1948	LR: 0.004000
Training Epoch: 28 [5888/10284]	Loss: 0.1173	LR: 0.004000
Training Epoch: 28 [6144/10284]	Loss: 0.1271	LR: 0.004000
Training Epoch: 28 [6400/10284]	Loss: 0.1154	LR: 0.004000
Training Epoch: 28 [6656/10284]	Loss: 0.1509	LR: 0.004000
Training Epoch: 28 [6912/10284]	Loss: 0.1487	LR: 0.004000
Training Epoch: 28 [7168/10284]	Loss: 0.1088	LR: 0.004000
Training Epoch: 28 [7424/10284]	Loss: 0.1163	LR: 0.004000
Training Epoch: 28 [7680/10284]	Loss: 0.1473	LR: 0.004000
Training Epoch: 28 [7936/10284]	Loss: 0.1334	LR: 0.004000
Training Epoch: 28 [8192/10284]	Loss: 0.1121	LR: 0.004000
Training Epoch: 28 [8448/10284]	Loss: 0.1097	LR: 0.004000
Training Epoch: 28 [8704/10284]	Loss: 0.1449	LR: 0.004000
Training Epoch: 28 [8960/10284]	Loss: 0.1173	LR: 0.004000
Training Epoch: 28 [9216/10284]	Loss: 0.1019	LR: 0.004000
Training Epoch: 28 [9472/10284]	Loss: 0.0837	LR: 0.004000
Training Epoch: 28 [9728/10284]	Loss: 0.1545	LR: 0.004000
Training Epoch: 28 [9984/10284]	Loss: 0.1157	LR: 0.004000
Training Epoch: 28 [10240/10284]	Loss: 0.1353	LR: 0.004000
Training Epoch: 28 [10284/10284]	Loss: 0.0962	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1272, Train Accuracy: 0.9488
Epoch 28 training time consumed: 148.19s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0006, Accuracy: 0.9433, Time consumed:7.91s
Training Epoch: 29 [256/10284]	Loss: 0.1325	LR: 0.004000
Training Epoch: 29 [512/10284]	Loss: 0.1190	LR: 0.004000
Training Epoch: 29 [768/10284]	Loss: 0.1640	LR: 0.004000
Training Epoch: 29 [1024/10284]	Loss: 0.1127	LR: 0.004000
Training Epoch: 29 [1280/10284]	Loss: 0.1104	LR: 0.004000
Training Epoch: 29 [1536/10284]	Loss: 0.1155	LR: 0.004000
Training Epoch: 29 [1792/10284]	Loss: 0.1381	LR: 0.004000
Training Epoch: 29 [2048/10284]	Loss: 0.1263	LR: 0.004000
Training Epoch: 29 [2304/10284]	Loss: 0.1198	LR: 0.004000
Training Epoch: 29 [2560/10284]	Loss: 0.0767	LR: 0.004000
Training Epoch: 29 [2816/10284]	Loss: 0.1002	LR: 0.004000
Training Epoch: 29 [3072/10284]	Loss: 0.1332	LR: 0.004000
Training Epoch: 29 [3328/10284]	Loss: 0.0713	LR: 0.004000
Training Epoch: 29 [3584/10284]	Loss: 0.1622	LR: 0.004000
Training Epoch: 29 [3840/10284]	Loss: 0.1390	LR: 0.004000
Training Epoch: 29 [4096/10284]	Loss: 0.1223	LR: 0.004000
Training Epoch: 29 [4352/10284]	Loss: 0.0929	LR: 0.004000
Training Epoch: 29 [4608/10284]	Loss: 0.1138	LR: 0.004000
Training Epoch: 29 [4864/10284]	Loss: 0.1419	LR: 0.004000
Training Epoch: 29 [5120/10284]	Loss: 0.1526	LR: 0.004000
Training Epoch: 29 [5376/10284]	Loss: 0.1019	LR: 0.004000
Training Epoch: 29 [5632/10284]	Loss: 0.1251	LR: 0.004000
Training Epoch: 29 [5888/10284]	Loss: 0.1482	LR: 0.004000
Training Epoch: 29 [6144/10284]	Loss: 0.2089	LR: 0.004000
Training Epoch: 29 [6400/10284]	Loss: 0.1476	LR: 0.004000
Training Epoch: 29 [6656/10284]	Loss: 0.0924	LR: 0.004000
Training Epoch: 29 [6912/10284]	Loss: 0.1170	LR: 0.004000
Training Epoch: 29 [7168/10284]	Loss: 0.1173	LR: 0.004000
Training Epoch: 29 [7424/10284]	Loss: 0.0726	LR: 0.004000
Training Epoch: 29 [7680/10284]	Loss: 0.2156	LR: 0.004000
Training Epoch: 29 [7936/10284]	Loss: 0.1391	LR: 0.004000
Training Epoch: 29 [8192/10284]	Loss: 0.1235	LR: 0.004000
Training Epoch: 29 [8448/10284]	Loss: 0.1570	LR: 0.004000
Training Epoch: 29 [8704/10284]	Loss: 0.1105	LR: 0.004000
Training Epoch: 29 [8960/10284]	Loss: 0.1220	LR: 0.004000
Training Epoch: 29 [9216/10284]	Loss: 0.1069	LR: 0.004000
Training Epoch: 29 [9472/10284]	Loss: 0.1337	LR: 0.004000
Training Epoch: 29 [9728/10284]	Loss: 0.1737	LR: 0.004000
Training Epoch: 29 [9984/10284]	Loss: 0.1289	LR: 0.004000
Training Epoch: 29 [10240/10284]	Loss: 0.1263	LR: 0.004000
Training Epoch: 29 [10284/10284]	Loss: 0.1702	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1280, Train Accuracy: 0.9485
Epoch 29 training time consumed: 148.52s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0007, Accuracy: 0.9312, Time consumed:7.87s
Training Epoch: 30 [256/10284]	Loss: 0.1446	LR: 0.004000
Training Epoch: 30 [512/10284]	Loss: 0.1054	LR: 0.004000
Training Epoch: 30 [768/10284]	Loss: 0.1425	LR: 0.004000
Training Epoch: 30 [1024/10284]	Loss: 0.1409	LR: 0.004000
Training Epoch: 30 [1280/10284]	Loss: 0.1418	LR: 0.004000
Training Epoch: 30 [1536/10284]	Loss: 0.1277	LR: 0.004000
Training Epoch: 30 [1792/10284]	Loss: 0.1332	LR: 0.004000
Training Epoch: 30 [2048/10284]	Loss: 0.1219	LR: 0.004000
Training Epoch: 30 [2304/10284]	Loss: 0.1164	LR: 0.004000
Training Epoch: 30 [2560/10284]	Loss: 0.0970	LR: 0.004000
Training Epoch: 30 [2816/10284]	Loss: 0.1284	LR: 0.004000
Training Epoch: 30 [3072/10284]	Loss: 0.1347	LR: 0.004000
Training Epoch: 30 [3328/10284]	Loss: 0.0962	LR: 0.004000
Training Epoch: 30 [3584/10284]	Loss: 0.1120	LR: 0.004000
Training Epoch: 30 [3840/10284]	Loss: 0.1208	LR: 0.004000
Training Epoch: 30 [4096/10284]	Loss: 0.0831	LR: 0.004000
Training Epoch: 30 [4352/10284]	Loss: 0.1066	LR: 0.004000
Training Epoch: 30 [4608/10284]	Loss: 0.1188	LR: 0.004000
Training Epoch: 30 [4864/10284]	Loss: 0.1605	LR: 0.004000
Training Epoch: 30 [5120/10284]	Loss: 0.1042	LR: 0.004000
Training Epoch: 30 [5376/10284]	Loss: 0.1116	LR: 0.004000
Training Epoch: 30 [5632/10284]	Loss: 0.1550	LR: 0.004000
Training Epoch: 30 [5888/10284]	Loss: 0.1057	LR: 0.004000
Training Epoch: 30 [6144/10284]	Loss: 0.1631	LR: 0.004000
Training Epoch: 30 [6400/10284]	Loss: 0.1495	LR: 0.004000
Training Epoch: 30 [6656/10284]	Loss: 0.1572	LR: 0.004000
Training Epoch: 30 [6912/10284]	Loss: 0.1253	LR: 0.004000
Training Epoch: 30 [7168/10284]	Loss: 0.1147	LR: 0.004000
Training Epoch: 30 [7424/10284]	Loss: 0.1076	LR: 0.004000
Training Epoch: 30 [7680/10284]	Loss: 0.1305	LR: 0.004000
Training Epoch: 30 [7936/10284]	Loss: 0.1564	LR: 0.004000
Training Epoch: 30 [8192/10284]	Loss: 0.1474	LR: 0.004000
Training Epoch: 30 [8448/10284]	Loss: 0.1523	LR: 0.004000
Training Epoch: 30 [8704/10284]	Loss: 0.1453	LR: 0.004000
Training Epoch: 30 [8960/10284]	Loss: 0.1236	LR: 0.004000
Training Epoch: 30 [9216/10284]	Loss: 0.1018	LR: 0.004000
Training Epoch: 30 [9472/10284]	Loss: 0.1643	LR: 0.004000
Training Epoch: 30 [9728/10284]	Loss: 0.1183	LR: 0.004000
Training Epoch: 30 [9984/10284]	Loss: 0.1221	LR: 0.004000
Training Epoch: 30 [10240/10284]	Loss: 0.1159	LR: 0.004000
Training Epoch: 30 [10284/10284]	Loss: 0.2166	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1280, Train Accuracy: 0.9454
Epoch 30 training time consumed: 148.28s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0005, Accuracy: 0.9467, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_02m_00s/ResNet18-MUCAC-seed2-ret75-30-best.pth
Training Epoch: 31 [256/10284]	Loss: 0.1211	LR: 0.004000
Training Epoch: 31 [512/10284]	Loss: 0.1155	LR: 0.004000
Training Epoch: 31 [768/10284]	Loss: 0.1038	LR: 0.004000
Training Epoch: 31 [1024/10284]	Loss: 0.0997	LR: 0.004000
Training Epoch: 31 [1280/10284]	Loss: 0.1156	LR: 0.004000
Training Epoch: 31 [1536/10284]	Loss: 0.1242	LR: 0.004000
Training Epoch: 31 [1792/10284]	Loss: 0.1003	LR: 0.004000
Training Epoch: 31 [2048/10284]	Loss: 0.1235	LR: 0.004000
Training Epoch: 31 [2304/10284]	Loss: 0.1311	LR: 0.004000
Training Epoch: 31 [2560/10284]	Loss: 0.1225	LR: 0.004000
Training Epoch: 31 [2816/10284]	Loss: 0.1262	LR: 0.004000
Training Epoch: 31 [3072/10284]	Loss: 0.1441	LR: 0.004000
Training Epoch: 31 [3328/10284]	Loss: 0.0979	LR: 0.004000
Training Epoch: 31 [3584/10284]	Loss: 0.1217	LR: 0.004000
Training Epoch: 31 [3840/10284]	Loss: 0.1016	LR: 0.004000
Training Epoch: 31 [4096/10284]	Loss: 0.1378	LR: 0.004000
Training Epoch: 31 [4352/10284]	Loss: 0.1395	LR: 0.004000
Training Epoch: 31 [4608/10284]	Loss: 0.1395	LR: 0.004000
Training Epoch: 31 [4864/10284]	Loss: 0.0850	LR: 0.004000
Training Epoch: 31 [5120/10284]	Loss: 0.1664	LR: 0.004000
Training Epoch: 31 [5376/10284]	Loss: 0.1265	LR: 0.004000
Training Epoch: 31 [5632/10284]	Loss: 0.1649	LR: 0.004000
Training Epoch: 31 [5888/10284]	Loss: 0.1123	LR: 0.004000
Training Epoch: 31 [6144/10284]	Loss: 0.1318	LR: 0.004000
Training Epoch: 31 [6400/10284]	Loss: 0.1197	LR: 0.004000
Training Epoch: 31 [6656/10284]	Loss: 0.1753	LR: 0.004000
Training Epoch: 31 [6912/10284]	Loss: 0.1269	LR: 0.004000
Training Epoch: 31 [7168/10284]	Loss: 0.1032	LR: 0.004000
Training Epoch: 31 [7424/10284]	Loss: 0.1009	LR: 0.004000
Training Epoch: 31 [7680/10284]	Loss: 0.1270	LR: 0.004000
Training Epoch: 31 [7936/10284]	Loss: 0.1237	LR: 0.004000
Training Epoch: 31 [8192/10284]	Loss: 0.1139	LR: 0.004000
Training Epoch: 31 [8448/10284]	Loss: 0.1019	LR: 0.004000
Training Epoch: 31 [8704/10284]	Loss: 0.0769	LR: 0.004000
Training Epoch: 31 [8960/10284]	Loss: 0.1291	LR: 0.004000
Training Epoch: 31 [9216/10284]	Loss: 0.1306	LR: 0.004000
Training Epoch: 31 [9472/10284]	Loss: 0.1246	LR: 0.004000
Training Epoch: 31 [9728/10284]	Loss: 0.0897	LR: 0.004000
Training Epoch: 31 [9984/10284]	Loss: 0.1024	LR: 0.004000
Training Epoch: 31 [10240/10284]	Loss: 0.1137	LR: 0.004000
Training Epoch: 31 [10284/10284]	Loss: 0.1595	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1205, Train Accuracy: 0.9497
Epoch 31 training time consumed: 148.28s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9400, Time consumed:8.10s
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: 94.00786590576172
Retain Accuracy: 94.70187377929688
Zero-Retain Forget (ZRF): 0.7694384455680847
Membership Inference Attack (MIA): 0.35984848484848486
Forget vs Retain Membership Inference Attack (MIA): 0.4716981132075472
Forget vs Test Membership Inference Attack (MIA): 0.5283018867924528
Test vs Retain Membership Inference Attack (MIA): 0.5290556900726392
Train vs Test Membership Inference Attack (MIA): 0.5363196125907991
Forget Set Accuracy (Df): 97.65625
Method Execution Time: 5981.18 seconds
