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

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

📌 S Forget class distribution for seed 1:
Class 0: 527
Class 1: 527
./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 [256/9494]	Loss: 0.6896	LR: 0.000000
Training Epoch: 1 [512/9494]	Loss: 0.7001	LR: 0.002632
Training Epoch: 1 [768/9494]	Loss: 0.6884	LR: 0.005263
Training Epoch: 1 [1024/9494]	Loss: 0.6921	LR: 0.007895
Training Epoch: 1 [1280/9494]	Loss: 0.7588	LR: 0.010526
Training Epoch: 1 [1536/9494]	Loss: 0.6894	LR: 0.013158
Training Epoch: 1 [1792/9494]	Loss: 0.7516	LR: 0.015789
Training Epoch: 1 [2048/9494]	Loss: 0.6888	LR: 0.018421
Training Epoch: 1 [2304/9494]	Loss: 0.7428	LR: 0.021053
Training Epoch: 1 [2560/9494]	Loss: 0.7007	LR: 0.023684
Training Epoch: 1 [2816/9494]	Loss: 0.6731	LR: 0.026316
Training Epoch: 1 [3072/9494]	Loss: 0.7219	LR: 0.028947
Training Epoch: 1 [3328/9494]	Loss: 1.1655	LR: 0.031579
Training Epoch: 1 [3584/9494]	Loss: 1.1733	LR: 0.034211
Training Epoch: 1 [3840/9494]	Loss: 0.7578	LR: 0.036842
Training Epoch: 1 [4096/9494]	Loss: 0.6758	LR: 0.039474
Training Epoch: 1 [4352/9494]	Loss: 0.7513	LR: 0.042105
Training Epoch: 1 [4608/9494]	Loss: 0.7002	LR: 0.044737
Training Epoch: 1 [4864/9494]	Loss: 0.7137	LR: 0.047368
Training Epoch: 1 [5120/9494]	Loss: 0.7802	LR: 0.050000
Training Epoch: 1 [5376/9494]	Loss: 0.7998	LR: 0.052632
Training Epoch: 1 [5632/9494]	Loss: 0.8339	LR: 0.055263
Training Epoch: 1 [5888/9494]	Loss: 0.7552	LR: 0.057895
Training Epoch: 1 [6144/9494]	Loss: 0.6589	LR: 0.060526
Training Epoch: 1 [6400/9494]	Loss: 0.7496	LR: 0.063158
Training Epoch: 1 [6656/9494]	Loss: 0.6548	LR: 0.065789
Training Epoch: 1 [6912/9494]	Loss: 0.7738	LR: 0.068421
Training Epoch: 1 [7168/9494]	Loss: 0.7135	LR: 0.071053
Training Epoch: 1 [7424/9494]	Loss: 0.9873	LR: 0.073684
Training Epoch: 1 [7680/9494]	Loss: 0.7446	LR: 0.076316
Training Epoch: 1 [7936/9494]	Loss: 0.9624	LR: 0.078947
Training Epoch: 1 [8192/9494]	Loss: 0.8219	LR: 0.081579
Training Epoch: 1 [8448/9494]	Loss: 0.7999	LR: 0.084211
Training Epoch: 1 [8704/9494]	Loss: 0.8890	LR: 0.086842
Training Epoch: 1 [8960/9494]	Loss: 0.6916	LR: 0.089474
Training Epoch: 1 [9216/9494]	Loss: 0.7706	LR: 0.092105
Training Epoch: 1 [9472/9494]	Loss: 0.9696	LR: 0.094737
Training Epoch: 1 [9494/9494]	Loss: 0.6137	LR: 0.097368
Epoch 1 - Average Train Loss: 0.7778, Train Accuracy: 0.5273
Epoch 1 training time consumed: 7445.95s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0371, Accuracy: 0.5550, Time consumed:464.41s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-1-best.pth
Training Epoch: 2 [256/9494]	Loss: 1.1067	LR: 0.100000
Training Epoch: 2 [512/9494]	Loss: 2.0830	LR: 0.100000
Training Epoch: 2 [768/9494]	Loss: 0.9461	LR: 0.100000
Training Epoch: 2 [1024/9494]	Loss: 1.4653	LR: 0.100000
Training Epoch: 2 [1280/9494]	Loss: 0.7363	LR: 0.100000
Training Epoch: 2 [1536/9494]	Loss: 1.2493	LR: 0.100000
Training Epoch: 2 [1792/9494]	Loss: 0.8004	LR: 0.100000
Training Epoch: 2 [2048/9494]	Loss: 0.8744	LR: 0.100000
Training Epoch: 2 [2304/9494]	Loss: 0.7425	LR: 0.100000
Training Epoch: 2 [2560/9494]	Loss: 0.7213	LR: 0.100000
Training Epoch: 2 [2816/9494]	Loss: 0.7191	LR: 0.100000
Training Epoch: 2 [3072/9494]	Loss: 0.7960	LR: 0.100000
Training Epoch: 2 [3328/9494]	Loss: 0.7367	LR: 0.100000
Training Epoch: 2 [3584/9494]	Loss: 0.7227	LR: 0.100000
Training Epoch: 2 [3840/9494]	Loss: 0.7046	LR: 0.100000
Training Epoch: 2 [4096/9494]	Loss: 0.7098	LR: 0.100000
Training Epoch: 2 [4352/9494]	Loss: 0.7079	LR: 0.100000
Training Epoch: 2 [4608/9494]	Loss: 0.7260	LR: 0.100000
Training Epoch: 2 [4864/9494]	Loss: 0.7349	LR: 0.100000
Training Epoch: 2 [5120/9494]	Loss: 0.6911	LR: 0.100000
Training Epoch: 2 [5376/9494]	Loss: 0.7114	LR: 0.100000
Training Epoch: 2 [5632/9494]	Loss: 0.7267	LR: 0.100000
Training Epoch: 2 [5888/9494]	Loss: 0.7567	LR: 0.100000
Training Epoch: 2 [6144/9494]	Loss: 0.6952	LR: 0.100000
Training Epoch: 2 [6400/9494]	Loss: 0.7078	LR: 0.100000
Training Epoch: 2 [6656/9494]	Loss: 0.7315	LR: 0.100000
Training Epoch: 2 [6912/9494]	Loss: 0.7112	LR: 0.100000
Training Epoch: 2 [7168/9494]	Loss: 0.6652	LR: 0.100000
Training Epoch: 2 [7424/9494]	Loss: 0.7521	LR: 0.100000
Training Epoch: 2 [7680/9494]	Loss: 0.6916	LR: 0.100000
Training Epoch: 2 [7936/9494]	Loss: 0.6823	LR: 0.100000
Training Epoch: 2 [8192/9494]	Loss: 0.6731	LR: 0.100000
Training Epoch: 2 [8448/9494]	Loss: 0.7046	LR: 0.100000
Training Epoch: 2 [8704/9494]	Loss: 0.6773	LR: 0.100000
Training Epoch: 2 [8960/9494]	Loss: 0.7220	LR: 0.100000
Training Epoch: 2 [9216/9494]	Loss: 0.6874	LR: 0.100000
Training Epoch: 2 [9472/9494]	Loss: 0.6761	LR: 0.100000
Training Epoch: 2 [9494/9494]	Loss: 0.7774	LR: 0.100000
Epoch 2 - Average Train Loss: 0.8093, Train Accuracy: 0.5276
Epoch 2 training time consumed: 136.45s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0031, Accuracy: 0.5472, Time consumed:8.00s
Training Epoch: 3 [256/9494]	Loss: 0.6735	LR: 0.100000
Training Epoch: 3 [512/9494]	Loss: 0.6848	LR: 0.100000
Training Epoch: 3 [768/9494]	Loss: 0.7437	LR: 0.100000
Training Epoch: 3 [1024/9494]	Loss: 0.6809	LR: 0.100000
Training Epoch: 3 [1280/9494]	Loss: 0.7487	LR: 0.100000
Training Epoch: 3 [1536/9494]	Loss: 0.6757	LR: 0.100000
Training Epoch: 3 [1792/9494]	Loss: 0.6826	LR: 0.100000
Training Epoch: 3 [2048/9494]	Loss: 0.7119	LR: 0.100000
Training Epoch: 3 [2304/9494]	Loss: 0.7282	LR: 0.100000
Training Epoch: 3 [2560/9494]	Loss: 0.6824	LR: 0.100000
Training Epoch: 3 [2816/9494]	Loss: 0.6580	LR: 0.100000
Training Epoch: 3 [3072/9494]	Loss: 0.6806	LR: 0.100000
Training Epoch: 3 [3328/9494]	Loss: 0.7118	LR: 0.100000
Training Epoch: 3 [3584/9494]	Loss: 0.6763	LR: 0.100000
Training Epoch: 3 [3840/9494]	Loss: 0.6837	LR: 0.100000
Training Epoch: 3 [4096/9494]	Loss: 0.7007	LR: 0.100000
Training Epoch: 3 [4352/9494]	Loss: 0.7095	LR: 0.100000
Training Epoch: 3 [4608/9494]	Loss: 0.7068	LR: 0.100000
Training Epoch: 3 [4864/9494]	Loss: 0.6760	LR: 0.100000
Training Epoch: 3 [5120/9494]	Loss: 0.6972	LR: 0.100000
Training Epoch: 3 [5376/9494]	Loss: 0.7163	LR: 0.100000
Training Epoch: 3 [5632/9494]	Loss: 0.6964	LR: 0.100000
Training Epoch: 3 [5888/9494]	Loss: 0.6832	LR: 0.100000
Training Epoch: 3 [6144/9494]	Loss: 0.6829	LR: 0.100000
Training Epoch: 3 [6400/9494]	Loss: 0.6838	LR: 0.100000
Training Epoch: 3 [6656/9494]	Loss: 0.6924	LR: 0.100000
Training Epoch: 3 [6912/9494]	Loss: 0.7142	LR: 0.100000
Training Epoch: 3 [7168/9494]	Loss: 0.6868	LR: 0.100000
Training Epoch: 3 [7424/9494]	Loss: 0.6650	LR: 0.100000
Training Epoch: 3 [7680/9494]	Loss: 0.6981	LR: 0.100000
Training Epoch: 3 [7936/9494]	Loss: 0.6850	LR: 0.100000
Training Epoch: 3 [8192/9494]	Loss: 0.6638	LR: 0.100000
Training Epoch: 3 [8448/9494]	Loss: 0.6914	LR: 0.100000
Training Epoch: 3 [8704/9494]	Loss: 0.6722	LR: 0.100000
Training Epoch: 3 [8960/9494]	Loss: 0.6769	LR: 0.100000
Training Epoch: 3 [9216/9494]	Loss: 0.6912	LR: 0.100000
Training Epoch: 3 [9472/9494]	Loss: 0.7007	LR: 0.100000
Training Epoch: 3 [9494/9494]	Loss: 0.6323	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6921, Train Accuracy: 0.5553
Epoch 3 training time consumed: 136.32s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0035, Accuracy: 0.5564, Time consumed:8.00s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-3-best.pth
Training Epoch: 4 [256/9494]	Loss: 0.7273	LR: 0.100000
Training Epoch: 4 [512/9494]	Loss: 0.7296	LR: 0.100000
Training Epoch: 4 [768/9494]	Loss: 0.7213	LR: 0.100000
Training Epoch: 4 [1024/9494]	Loss: 0.6498	LR: 0.100000
Training Epoch: 4 [1280/9494]	Loss: 0.6701	LR: 0.100000
Training Epoch: 4 [1536/9494]	Loss: 0.6909	LR: 0.100000
Training Epoch: 4 [1792/9494]	Loss: 0.6981	LR: 0.100000
Training Epoch: 4 [2048/9494]	Loss: 0.7138	LR: 0.100000
Training Epoch: 4 [2304/9494]	Loss: 0.6861	LR: 0.100000
Training Epoch: 4 [2560/9494]	Loss: 0.6885	LR: 0.100000
Training Epoch: 4 [2816/9494]	Loss: 0.6939	LR: 0.100000
Training Epoch: 4 [3072/9494]	Loss: 0.7261	LR: 0.100000
Training Epoch: 4 [3328/9494]	Loss: 0.6968	LR: 0.100000
Training Epoch: 4 [3584/9494]	Loss: 0.6756	LR: 0.100000
Training Epoch: 4 [3840/9494]	Loss: 0.6855	LR: 0.100000
Training Epoch: 4 [4096/9494]	Loss: 0.6767	LR: 0.100000
Training Epoch: 4 [4352/9494]	Loss: 0.7239	LR: 0.100000
Training Epoch: 4 [4608/9494]	Loss: 0.6773	LR: 0.100000
Training Epoch: 4 [4864/9494]	Loss: 0.6754	LR: 0.100000
Training Epoch: 4 [5120/9494]	Loss: 0.6616	LR: 0.100000
Training Epoch: 4 [5376/9494]	Loss: 0.6764	LR: 0.100000
Training Epoch: 4 [5632/9494]	Loss: 0.6972	LR: 0.100000
Training Epoch: 4 [5888/9494]	Loss: 0.7505	LR: 0.100000
Training Epoch: 4 [6144/9494]	Loss: 0.7538	LR: 0.100000
Training Epoch: 4 [6400/9494]	Loss: 0.6936	LR: 0.100000
Training Epoch: 4 [6656/9494]	Loss: 0.6834	LR: 0.100000
Training Epoch: 4 [6912/9494]	Loss: 0.7181	LR: 0.100000
Training Epoch: 4 [7168/9494]	Loss: 0.6719	LR: 0.100000
Training Epoch: 4 [7424/9494]	Loss: 0.6907	LR: 0.100000
Training Epoch: 4 [7680/9494]	Loss: 0.6750	LR: 0.100000
Training Epoch: 4 [7936/9494]	Loss: 0.6654	LR: 0.100000
Training Epoch: 4 [8192/9494]	Loss: 0.6918	LR: 0.100000
Training Epoch: 4 [8448/9494]	Loss: 0.6994	LR: 0.100000
Training Epoch: 4 [8704/9494]	Loss: 0.6702	LR: 0.100000
Training Epoch: 4 [8960/9494]	Loss: 0.6845	LR: 0.100000
Training Epoch: 4 [9216/9494]	Loss: 0.6740	LR: 0.100000
Training Epoch: 4 [9472/9494]	Loss: 0.6691	LR: 0.100000
Training Epoch: 4 [9494/9494]	Loss: 0.5886	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6925, Train Accuracy: 0.5712
Epoch 4 training time consumed: 136.07s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0030, Accuracy: 0.5666, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-4-best.pth
Training Epoch: 5 [256/9494]	Loss: 0.7107	LR: 0.100000
Training Epoch: 5 [512/9494]	Loss: 0.7016	LR: 0.100000
Training Epoch: 5 [768/9494]	Loss: 0.7539	LR: 0.100000
Training Epoch: 5 [1024/9494]	Loss: 0.6781	LR: 0.100000
Training Epoch: 5 [1280/9494]	Loss: 0.6464	LR: 0.100000
Training Epoch: 5 [1536/9494]	Loss: 0.6633	LR: 0.100000
Training Epoch: 5 [1792/9494]	Loss: 0.6794	LR: 0.100000
Training Epoch: 5 [2048/9494]	Loss: 0.7193	LR: 0.100000
Training Epoch: 5 [2304/9494]	Loss: 0.6860	LR: 0.100000
Training Epoch: 5 [2560/9494]	Loss: 0.7095	LR: 0.100000
Training Epoch: 5 [2816/9494]	Loss: 0.6779	LR: 0.100000
Training Epoch: 5 [3072/9494]	Loss: 0.6738	LR: 0.100000
Training Epoch: 5 [3328/9494]	Loss: 0.6960	LR: 0.100000
Training Epoch: 5 [3584/9494]	Loss: 0.6642	LR: 0.100000
Training Epoch: 5 [3840/9494]	Loss: 0.6804	LR: 0.100000
Training Epoch: 5 [4096/9494]	Loss: 0.6582	LR: 0.100000
Training Epoch: 5 [4352/9494]	Loss: 0.6998	LR: 0.100000
Training Epoch: 5 [4608/9494]	Loss: 0.6726	LR: 0.100000
Training Epoch: 5 [4864/9494]	Loss: 0.6786	LR: 0.100000
Training Epoch: 5 [5120/9494]	Loss: 0.6819	LR: 0.100000
Training Epoch: 5 [5376/9494]	Loss: 0.6450	LR: 0.100000
Training Epoch: 5 [5632/9494]	Loss: 0.6872	LR: 0.100000
Training Epoch: 5 [5888/9494]	Loss: 0.6782	LR: 0.100000
Training Epoch: 5 [6144/9494]	Loss: 0.7183	LR: 0.100000
Training Epoch: 5 [6400/9494]	Loss: 0.6555	LR: 0.100000
Training Epoch: 5 [6656/9494]	Loss: 0.6762	LR: 0.100000
Training Epoch: 5 [6912/9494]	Loss: 0.6774	LR: 0.100000
Training Epoch: 5 [7168/9494]	Loss: 0.6606	LR: 0.100000
Training Epoch: 5 [7424/9494]	Loss: 0.7093	LR: 0.100000
Training Epoch: 5 [7680/9494]	Loss: 0.6559	LR: 0.100000
Training Epoch: 5 [7936/9494]	Loss: 0.6630	LR: 0.100000
Training Epoch: 5 [8192/9494]	Loss: 0.6855	LR: 0.100000
Training Epoch: 5 [8448/9494]	Loss: 0.6325	LR: 0.100000
Training Epoch: 5 [8704/9494]	Loss: 0.6554	LR: 0.100000
Training Epoch: 5 [8960/9494]	Loss: 0.6568	LR: 0.100000
Training Epoch: 5 [9216/9494]	Loss: 0.6513	LR: 0.100000
Training Epoch: 5 [9472/9494]	Loss: 0.6779	LR: 0.100000
Training Epoch: 5 [9494/9494]	Loss: 0.7122	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6789, Train Accuracy: 0.5796
Epoch 5 training time consumed: 135.67s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0029, Accuracy: 0.5811, Time consumed:7.88s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-5-best.pth
Training Epoch: 6 [256/9494]	Loss: 0.6626	LR: 0.100000
Training Epoch: 6 [512/9494]	Loss: 0.6705	LR: 0.100000
Training Epoch: 6 [768/9494]	Loss: 0.6833	LR: 0.100000
Training Epoch: 6 [1024/9494]	Loss: 0.6769	LR: 0.100000
Training Epoch: 6 [1280/9494]	Loss: 0.6841	LR: 0.100000
Training Epoch: 6 [1536/9494]	Loss: 0.6599	LR: 0.100000
Training Epoch: 6 [1792/9494]	Loss: 0.6501	LR: 0.100000
Training Epoch: 6 [2048/9494]	Loss: 0.6848	LR: 0.100000
Training Epoch: 6 [2304/9494]	Loss: 0.6577	LR: 0.100000
Training Epoch: 6 [2560/9494]	Loss: 0.6863	LR: 0.100000
Training Epoch: 6 [2816/9494]	Loss: 0.6421	LR: 0.100000
Training Epoch: 6 [3072/9494]	Loss: 0.6592	LR: 0.100000
Training Epoch: 6 [3328/9494]	Loss: 0.7032	LR: 0.100000
Training Epoch: 6 [3584/9494]	Loss: 0.6801	LR: 0.100000
Training Epoch: 6 [3840/9494]	Loss: 0.6679	LR: 0.100000
Training Epoch: 6 [4096/9494]	Loss: 0.6677	LR: 0.100000
Training Epoch: 6 [4352/9494]	Loss: 0.6704	LR: 0.100000
Training Epoch: 6 [4608/9494]	Loss: 0.6889	LR: 0.100000
Training Epoch: 6 [4864/9494]	Loss: 0.6884	LR: 0.100000
Training Epoch: 6 [5120/9494]	Loss: 0.6419	LR: 0.100000
Training Epoch: 6 [5376/9494]	Loss: 0.6800	LR: 0.100000
Training Epoch: 6 [5632/9494]	Loss: 0.6644	LR: 0.100000
Training Epoch: 6 [5888/9494]	Loss: 0.6709	LR: 0.100000
Training Epoch: 6 [6144/9494]	Loss: 0.6726	LR: 0.100000
Training Epoch: 6 [6400/9494]	Loss: 0.6929	LR: 0.100000
Training Epoch: 6 [6656/9494]	Loss: 0.6697	LR: 0.100000
Training Epoch: 6 [6912/9494]	Loss: 0.6522	LR: 0.100000
Training Epoch: 6 [7168/9494]	Loss: 0.6446	LR: 0.100000
Training Epoch: 6 [7424/9494]	Loss: 0.6462	LR: 0.100000
Training Epoch: 6 [7680/9494]	Loss: 0.6454	LR: 0.100000
Training Epoch: 6 [7936/9494]	Loss: 0.6572	LR: 0.100000
Training Epoch: 6 [8192/9494]	Loss: 0.6529	LR: 0.100000
Training Epoch: 6 [8448/9494]	Loss: 0.6571	LR: 0.100000
Training Epoch: 6 [8704/9494]	Loss: 0.6744	LR: 0.100000
Training Epoch: 6 [8960/9494]	Loss: 0.6564	LR: 0.100000
Training Epoch: 6 [9216/9494]	Loss: 0.6509	LR: 0.100000
Training Epoch: 6 [9472/9494]	Loss: 0.6512	LR: 0.100000
Training Epoch: 6 [9494/9494]	Loss: 0.6700	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6666, Train Accuracy: 0.6040
Epoch 6 training time consumed: 135.73s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0029, Accuracy: 0.6397, Time consumed:7.80s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-6-best.pth
Training Epoch: 7 [256/9494]	Loss: 0.6611	LR: 0.100000
Training Epoch: 7 [512/9494]	Loss: 0.6206	LR: 0.100000
Training Epoch: 7 [768/9494]	Loss: 0.6811	LR: 0.100000
Training Epoch: 7 [1024/9494]	Loss: 0.7019	LR: 0.100000
Training Epoch: 7 [1280/9494]	Loss: 0.6632	LR: 0.100000
Training Epoch: 7 [1536/9494]	Loss: 0.6978	LR: 0.100000
Training Epoch: 7 [1792/9494]	Loss: 0.6604	LR: 0.100000
Training Epoch: 7 [2048/9494]	Loss: 0.6426	LR: 0.100000
Training Epoch: 7 [2304/9494]	Loss: 0.6539	LR: 0.100000
Training Epoch: 7 [2560/9494]	Loss: 0.7025	LR: 0.100000
Training Epoch: 7 [2816/9494]	Loss: 0.6774	LR: 0.100000
Training Epoch: 7 [3072/9494]	Loss: 0.6578	LR: 0.100000
Training Epoch: 7 [3328/9494]	Loss: 0.6652	LR: 0.100000
Training Epoch: 7 [3584/9494]	Loss: 0.6760	LR: 0.100000
Training Epoch: 7 [3840/9494]	Loss: 0.6693	LR: 0.100000
Training Epoch: 7 [4096/9494]	Loss: 0.6055	LR: 0.100000
Training Epoch: 7 [4352/9494]	Loss: 0.6582	LR: 0.100000
Training Epoch: 7 [4608/9494]	Loss: 0.6563	LR: 0.100000
Training Epoch: 7 [4864/9494]	Loss: 0.6993	LR: 0.100000
Training Epoch: 7 [5120/9494]	Loss: 0.6707	LR: 0.100000
Training Epoch: 7 [5376/9494]	Loss: 0.6291	LR: 0.100000
Training Epoch: 7 [5632/9494]	Loss: 0.6209	LR: 0.100000
Training Epoch: 7 [5888/9494]	Loss: 0.6100	LR: 0.100000
Training Epoch: 7 [6144/9494]	Loss: 0.6625	LR: 0.100000
Training Epoch: 7 [6400/9494]	Loss: 0.6028	LR: 0.100000
Training Epoch: 7 [6656/9494]	Loss: 0.6521	LR: 0.100000
Training Epoch: 7 [6912/9494]	Loss: 0.6198	LR: 0.100000
Training Epoch: 7 [7168/9494]	Loss: 0.6611	LR: 0.100000
Training Epoch: 7 [7424/9494]	Loss: 0.6293	LR: 0.100000
Training Epoch: 7 [7680/9494]	Loss: 0.6487	LR: 0.100000
Training Epoch: 7 [7936/9494]	Loss: 0.6594	LR: 0.100000
Training Epoch: 7 [8192/9494]	Loss: 0.6107	LR: 0.100000
Training Epoch: 7 [8448/9494]	Loss: 0.6503	LR: 0.100000
Training Epoch: 7 [8704/9494]	Loss: 0.6579	LR: 0.100000
Training Epoch: 7 [8960/9494]	Loss: 0.6310	LR: 0.100000
Training Epoch: 7 [9216/9494]	Loss: 0.6361	LR: 0.100000
Training Epoch: 7 [9472/9494]	Loss: 0.5707	LR: 0.100000
Training Epoch: 7 [9494/9494]	Loss: 0.6037	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6505, Train Accuracy: 0.6326
Epoch 7 training time consumed: 135.83s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0027, Accuracy: 0.6683, Time consumed:7.92s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-7-best.pth
Training Epoch: 8 [256/9494]	Loss: 0.6396	LR: 0.100000
Training Epoch: 8 [512/9494]	Loss: 0.7081	LR: 0.100000
Training Epoch: 8 [768/9494]	Loss: 0.7432	LR: 0.100000
Training Epoch: 8 [1024/9494]	Loss: 0.6664	LR: 0.100000
Training Epoch: 8 [1280/9494]	Loss: 0.7052	LR: 0.100000
Training Epoch: 8 [1536/9494]	Loss: 0.6115	LR: 0.100000
Training Epoch: 8 [1792/9494]	Loss: 0.6352	LR: 0.100000
Training Epoch: 8 [2048/9494]	Loss: 0.6414	LR: 0.100000
Training Epoch: 8 [2304/9494]	Loss: 0.6127	LR: 0.100000
Training Epoch: 8 [2560/9494]	Loss: 0.6358	LR: 0.100000
Training Epoch: 8 [2816/9494]	Loss: 0.6868	LR: 0.100000
Training Epoch: 8 [3072/9494]	Loss: 0.6268	LR: 0.100000
Training Epoch: 8 [3328/9494]	Loss: 0.6326	LR: 0.100000
Training Epoch: 8 [3584/9494]	Loss: 0.6421	LR: 0.100000
Training Epoch: 8 [3840/9494]	Loss: 0.5986	LR: 0.100000
Training Epoch: 8 [4096/9494]	Loss: 0.6123	LR: 0.100000
Training Epoch: 8 [4352/9494]	Loss: 0.6321	LR: 0.100000
Training Epoch: 8 [4608/9494]	Loss: 0.6352	LR: 0.100000
Training Epoch: 8 [4864/9494]	Loss: 0.6858	LR: 0.100000
Training Epoch: 8 [5120/9494]	Loss: 0.6818	LR: 0.100000
Training Epoch: 8 [5376/9494]	Loss: 0.6803	LR: 0.100000
Training Epoch: 8 [5632/9494]	Loss: 0.6636	LR: 0.100000
Training Epoch: 8 [5888/9494]	Loss: 0.6572	LR: 0.100000
Training Epoch: 8 [6144/9494]	Loss: 0.6077	LR: 0.100000
Training Epoch: 8 [6400/9494]	Loss: 0.6707	LR: 0.100000
Training Epoch: 8 [6656/9494]	Loss: 0.6209	LR: 0.100000
Training Epoch: 8 [6912/9494]	Loss: 0.5959	LR: 0.100000
Training Epoch: 8 [7168/9494]	Loss: 0.6706	LR: 0.100000
Training Epoch: 8 [7424/9494]	Loss: 0.6322	LR: 0.100000
Training Epoch: 8 [7680/9494]	Loss: 0.6158	LR: 0.100000
Training Epoch: 8 [7936/9494]	Loss: 0.6164	LR: 0.100000
Training Epoch: 8 [8192/9494]	Loss: 0.6044	LR: 0.100000
Training Epoch: 8 [8448/9494]	Loss: 0.6444	LR: 0.100000
Training Epoch: 8 [8704/9494]	Loss: 0.6379	LR: 0.100000
Training Epoch: 8 [8960/9494]	Loss: 0.5750	LR: 0.100000
Training Epoch: 8 [9216/9494]	Loss: 0.5800	LR: 0.100000
Training Epoch: 8 [9472/9494]	Loss: 0.5833	LR: 0.100000
Training Epoch: 8 [9494/9494]	Loss: 0.7444	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6405, Train Accuracy: 0.6486
Epoch 8 training time consumed: 135.70s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0027, Accuracy: 0.6804, Time consumed:7.94s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-8-best.pth
Training Epoch: 9 [256/9494]	Loss: 0.5793	LR: 0.100000
Training Epoch: 9 [512/9494]	Loss: 0.6435	LR: 0.100000
Training Epoch: 9 [768/9494]	Loss: 0.6108	LR: 0.100000
Training Epoch: 9 [1024/9494]	Loss: 0.6351	LR: 0.100000
Training Epoch: 9 [1280/9494]	Loss: 0.6003	LR: 0.100000
Training Epoch: 9 [1536/9494]	Loss: 0.6167	LR: 0.100000
Training Epoch: 9 [1792/9494]	Loss: 0.5752	LR: 0.100000
Training Epoch: 9 [2048/9494]	Loss: 0.6482	LR: 0.100000
Training Epoch: 9 [2304/9494]	Loss: 0.6500	LR: 0.100000
Training Epoch: 9 [2560/9494]	Loss: 0.6241	LR: 0.100000
Training Epoch: 9 [2816/9494]	Loss: 0.6290	LR: 0.100000
Training Epoch: 9 [3072/9494]	Loss: 0.6063	LR: 0.100000
Training Epoch: 9 [3328/9494]	Loss: 0.5953	LR: 0.100000
Training Epoch: 9 [3584/9494]	Loss: 0.6192	LR: 0.100000
Training Epoch: 9 [3840/9494]	Loss: 0.6134	LR: 0.100000
Training Epoch: 9 [4096/9494]	Loss: 0.5656	LR: 0.100000
Training Epoch: 9 [4352/9494]	Loss: 0.5574	LR: 0.100000
Training Epoch: 9 [4608/9494]	Loss: 0.5911	LR: 0.100000
Training Epoch: 9 [4864/9494]	Loss: 0.6166	LR: 0.100000
Training Epoch: 9 [5120/9494]	Loss: 0.6156	LR: 0.100000
Training Epoch: 9 [5376/9494]	Loss: 0.5807	LR: 0.100000
Training Epoch: 9 [5632/9494]	Loss: 0.6204	LR: 0.100000
Training Epoch: 9 [5888/9494]	Loss: 0.6522	LR: 0.100000
Training Epoch: 9 [6144/9494]	Loss: 0.5435	LR: 0.100000
Training Epoch: 9 [6400/9494]	Loss: 0.5675	LR: 0.100000
Training Epoch: 9 [6656/9494]	Loss: 0.5787	LR: 0.100000
Training Epoch: 9 [6912/9494]	Loss: 0.5819	LR: 0.100000
Training Epoch: 9 [7168/9494]	Loss: 0.5960	LR: 0.100000
Training Epoch: 9 [7424/9494]	Loss: 0.5150	LR: 0.100000
Training Epoch: 9 [7680/9494]	Loss: 0.6259	LR: 0.100000
Training Epoch: 9 [7936/9494]	Loss: 0.6226	LR: 0.100000
Training Epoch: 9 [8192/9494]	Loss: 0.5684	LR: 0.100000
Training Epoch: 9 [8448/9494]	Loss: 0.5527	LR: 0.100000
Training Epoch: 9 [8704/9494]	Loss: 0.5973	LR: 0.100000
Training Epoch: 9 [8960/9494]	Loss: 0.5456	LR: 0.100000
Training Epoch: 9 [9216/9494]	Loss: 0.5475	LR: 0.100000
Training Epoch: 9 [9472/9494]	Loss: 0.5909	LR: 0.100000
Training Epoch: 9 [9494/9494]	Loss: 0.5707	LR: 0.100000
Epoch 9 - Average Train Loss: 0.5967, Train Accuracy: 0.6807
Epoch 9 training time consumed: 135.64s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0027, Accuracy: 0.6596, Time consumed:8.10s
Training Epoch: 10 [256/9494]	Loss: 0.5534	LR: 0.020000
Training Epoch: 10 [512/9494]	Loss: 0.6445	LR: 0.020000
Training Epoch: 10 [768/9494]	Loss: 0.6162	LR: 0.020000
Training Epoch: 10 [1024/9494]	Loss: 0.6063	LR: 0.020000
Training Epoch: 10 [1280/9494]	Loss: 0.5200	LR: 0.020000
Training Epoch: 10 [1536/9494]	Loss: 0.5979	LR: 0.020000
Training Epoch: 10 [1792/9494]	Loss: 0.6280	LR: 0.020000
Training Epoch: 10 [2048/9494]	Loss: 0.5871	LR: 0.020000
Training Epoch: 10 [2304/9494]	Loss: 0.5965	LR: 0.020000
Training Epoch: 10 [2560/9494]	Loss: 0.5790	LR: 0.020000
Training Epoch: 10 [2816/9494]	Loss: 0.5230	LR: 0.020000
Training Epoch: 10 [3072/9494]	Loss: 0.6042	LR: 0.020000
Training Epoch: 10 [3328/9494]	Loss: 0.5638	LR: 0.020000
Training Epoch: 10 [3584/9494]	Loss: 0.5348	LR: 0.020000
Training Epoch: 10 [3840/9494]	Loss: 0.5346	LR: 0.020000
Training Epoch: 10 [4096/9494]	Loss: 0.5270	LR: 0.020000
Training Epoch: 10 [4352/9494]	Loss: 0.5819	LR: 0.020000
Training Epoch: 10 [4608/9494]	Loss: 0.5750	LR: 0.020000
Training Epoch: 10 [4864/9494]	Loss: 0.5604	LR: 0.020000
Training Epoch: 10 [5120/9494]	Loss: 0.5657	LR: 0.020000
Training Epoch: 10 [5376/9494]	Loss: 0.5174	LR: 0.020000
Training Epoch: 10 [5632/9494]	Loss: 0.5397	LR: 0.020000
Training Epoch: 10 [5888/9494]	Loss: 0.5441	LR: 0.020000
Training Epoch: 10 [6144/9494]	Loss: 0.5384	LR: 0.020000
Training Epoch: 10 [6400/9494]	Loss: 0.5561	LR: 0.020000
Training Epoch: 10 [6656/9494]	Loss: 0.5068	LR: 0.020000
Training Epoch: 10 [6912/9494]	Loss: 0.5327	LR: 0.020000
Training Epoch: 10 [7168/9494]	Loss: 0.5261	LR: 0.020000
Training Epoch: 10 [7424/9494]	Loss: 0.5186	LR: 0.020000
Training Epoch: 10 [7680/9494]	Loss: 0.5102	LR: 0.020000
Training Epoch: 10 [7936/9494]	Loss: 0.4940	LR: 0.020000
Training Epoch: 10 [8192/9494]	Loss: 0.5442	LR: 0.020000
Training Epoch: 10 [8448/9494]	Loss: 0.5346	LR: 0.020000
Training Epoch: 10 [8704/9494]	Loss: 0.5011	LR: 0.020000
Training Epoch: 10 [8960/9494]	Loss: 0.4818	LR: 0.020000
Training Epoch: 10 [9216/9494]	Loss: 0.5430	LR: 0.020000
Training Epoch: 10 [9472/9494]	Loss: 0.5126	LR: 0.020000
Training Epoch: 10 [9494/9494]	Loss: 0.3581	LR: 0.020000
Epoch 10 - Average Train Loss: 0.5509, Train Accuracy: 0.7242
Epoch 10 training time consumed: 135.29s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0025, Accuracy: 0.7235, Time consumed:7.85s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-10-best.pth
Training Epoch: 11 [256/9494]	Loss: 0.5742	LR: 0.020000
Training Epoch: 11 [512/9494]	Loss: 0.5532	LR: 0.020000
Training Epoch: 11 [768/9494]	Loss: 0.4842	LR: 0.020000
Training Epoch: 11 [1024/9494]	Loss: 0.4481	LR: 0.020000
Training Epoch: 11 [1280/9494]	Loss: 0.4910	LR: 0.020000
Training Epoch: 11 [1536/9494]	Loss: 0.4729	LR: 0.020000
Training Epoch: 11 [1792/9494]	Loss: 0.5290	LR: 0.020000
Training Epoch: 11 [2048/9494]	Loss: 0.4619	LR: 0.020000
Training Epoch: 11 [2304/9494]	Loss: 0.5330	LR: 0.020000
Training Epoch: 11 [2560/9494]	Loss: 0.5337	LR: 0.020000
Training Epoch: 11 [2816/9494]	Loss: 0.4463	LR: 0.020000
Training Epoch: 11 [3072/9494]	Loss: 0.4748	LR: 0.020000
Training Epoch: 11 [3328/9494]	Loss: 0.4780	LR: 0.020000
Training Epoch: 11 [3584/9494]	Loss: 0.5455	LR: 0.020000
Training Epoch: 11 [3840/9494]	Loss: 0.5328	LR: 0.020000
Training Epoch: 11 [4096/9494]	Loss: 0.4895	LR: 0.020000
Training Epoch: 11 [4352/9494]	Loss: 0.4887	LR: 0.020000
Training Epoch: 11 [4608/9494]	Loss: 0.4782	LR: 0.020000
Training Epoch: 11 [4864/9494]	Loss: 0.5007	LR: 0.020000
Training Epoch: 11 [5120/9494]	Loss: 0.5182	LR: 0.020000
Training Epoch: 11 [5376/9494]	Loss: 0.4930	LR: 0.020000
Training Epoch: 11 [5632/9494]	Loss: 0.5138	LR: 0.020000
Training Epoch: 11 [5888/9494]	Loss: 0.4901	LR: 0.020000
Training Epoch: 11 [6144/9494]	Loss: 0.4268	LR: 0.020000
Training Epoch: 11 [6400/9494]	Loss: 0.3972	LR: 0.020000
Training Epoch: 11 [6656/9494]	Loss: 0.4767	LR: 0.020000
Training Epoch: 11 [6912/9494]	Loss: 0.4236	LR: 0.020000
Training Epoch: 11 [7168/9494]	Loss: 0.4271	LR: 0.020000
Training Epoch: 11 [7424/9494]	Loss: 0.4906	LR: 0.020000
Training Epoch: 11 [7680/9494]	Loss: 0.4630	LR: 0.020000
Training Epoch: 11 [7936/9494]	Loss: 0.4387	LR: 0.020000
Training Epoch: 11 [8192/9494]	Loss: 0.5093	LR: 0.020000
Training Epoch: 11 [8448/9494]	Loss: 0.5034	LR: 0.020000
Training Epoch: 11 [8704/9494]	Loss: 0.4130	LR: 0.020000
Training Epoch: 11 [8960/9494]	Loss: 0.4537	LR: 0.020000
Training Epoch: 11 [9216/9494]	Loss: 0.4585	LR: 0.020000
Training Epoch: 11 [9472/9494]	Loss: 0.4777	LR: 0.020000
Training Epoch: 11 [9494/9494]	Loss: 0.4855	LR: 0.020000
Epoch 11 - Average Train Loss: 0.4835, Train Accuracy: 0.7679
Epoch 11 training time consumed: 135.46s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0021, Accuracy: 0.7806, Time consumed:7.98s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-11-best.pth
Training Epoch: 12 [256/9494]	Loss: 0.4502	LR: 0.020000
Training Epoch: 12 [512/9494]	Loss: 0.4991	LR: 0.020000
Training Epoch: 12 [768/9494]	Loss: 0.4682	LR: 0.020000
Training Epoch: 12 [1024/9494]	Loss: 0.4853	LR: 0.020000
Training Epoch: 12 [1280/9494]	Loss: 0.4572	LR: 0.020000
Training Epoch: 12 [1536/9494]	Loss: 0.4593	LR: 0.020000
Training Epoch: 12 [1792/9494]	Loss: 0.4267	LR: 0.020000
Training Epoch: 12 [2048/9494]	Loss: 0.4678	LR: 0.020000
Training Epoch: 12 [2304/9494]	Loss: 0.5242	LR: 0.020000
Training Epoch: 12 [2560/9494]	Loss: 0.4826	LR: 0.020000
Training Epoch: 12 [2816/9494]	Loss: 0.4705	LR: 0.020000
Training Epoch: 12 [3072/9494]	Loss: 0.4840	LR: 0.020000
Training Epoch: 12 [3328/9494]	Loss: 0.4861	LR: 0.020000
Training Epoch: 12 [3584/9494]	Loss: 0.4754	LR: 0.020000
Training Epoch: 12 [3840/9494]	Loss: 0.4679	LR: 0.020000
Training Epoch: 12 [4096/9494]	Loss: 0.4291	LR: 0.020000
Training Epoch: 12 [4352/9494]	Loss: 0.4432	LR: 0.020000
Training Epoch: 12 [4608/9494]	Loss: 0.4717	LR: 0.020000
Training Epoch: 12 [4864/9494]	Loss: 0.4364	LR: 0.020000
Training Epoch: 12 [5120/9494]	Loss: 0.4655	LR: 0.020000
Training Epoch: 12 [5376/9494]	Loss: 0.4903	LR: 0.020000
Training Epoch: 12 [5632/9494]	Loss: 0.4490	LR: 0.020000
Training Epoch: 12 [5888/9494]	Loss: 0.4171	LR: 0.020000
Training Epoch: 12 [6144/9494]	Loss: 0.4398	LR: 0.020000
Training Epoch: 12 [6400/9494]	Loss: 0.4406	LR: 0.020000
Training Epoch: 12 [6656/9494]	Loss: 0.4148	LR: 0.020000
Training Epoch: 12 [6912/9494]	Loss: 0.3764	LR: 0.020000
Training Epoch: 12 [7168/9494]	Loss: 0.5319	LR: 0.020000
Training Epoch: 12 [7424/9494]	Loss: 0.4341	LR: 0.020000
Training Epoch: 12 [7680/9494]	Loss: 0.4797	LR: 0.020000
Training Epoch: 12 [7936/9494]	Loss: 0.5023	LR: 0.020000
Training Epoch: 12 [8192/9494]	Loss: 0.5008	LR: 0.020000
Training Epoch: 12 [8448/9494]	Loss: 0.3890	LR: 0.020000
Training Epoch: 12 [8704/9494]	Loss: 0.4184	LR: 0.020000
Training Epoch: 12 [8960/9494]	Loss: 0.3979	LR: 0.020000
Training Epoch: 12 [9216/9494]	Loss: 0.4789	LR: 0.020000
Training Epoch: 12 [9472/9494]	Loss: 0.3664	LR: 0.020000
Training Epoch: 12 [9494/9494]	Loss: 0.5117	LR: 0.020000
Epoch 12 - Average Train Loss: 0.4563, Train Accuracy: 0.7877
Epoch 12 training time consumed: 135.73s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0019, Accuracy: 0.8136, Time consumed:7.70s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-12-best.pth
Training Epoch: 13 [256/9494]	Loss: 0.4356	LR: 0.020000
Training Epoch: 13 [512/9494]	Loss: 0.4576	LR: 0.020000
Training Epoch: 13 [768/9494]	Loss: 0.4847	LR: 0.020000
Training Epoch: 13 [1024/9494]	Loss: 0.4375	LR: 0.020000
Training Epoch: 13 [1280/9494]	Loss: 0.4276	LR: 0.020000
Training Epoch: 13 [1536/9494]	Loss: 0.3926	LR: 0.020000
Training Epoch: 13 [1792/9494]	Loss: 0.4157	LR: 0.020000
Training Epoch: 13 [2048/9494]	Loss: 0.4338	LR: 0.020000
Training Epoch: 13 [2304/9494]	Loss: 0.4028	LR: 0.020000
Training Epoch: 13 [2560/9494]	Loss: 0.4172	LR: 0.020000
Training Epoch: 13 [2816/9494]	Loss: 0.4266	LR: 0.020000
Training Epoch: 13 [3072/9494]	Loss: 0.4114	LR: 0.020000
Training Epoch: 13 [3328/9494]	Loss: 0.4424	LR: 0.020000
Training Epoch: 13 [3584/9494]	Loss: 0.4316	LR: 0.020000
Training Epoch: 13 [3840/9494]	Loss: 0.3834	LR: 0.020000
Training Epoch: 13 [4096/9494]	Loss: 0.4256	LR: 0.020000
Training Epoch: 13 [4352/9494]	Loss: 0.4709	LR: 0.020000
Training Epoch: 13 [4608/9494]	Loss: 0.4227	LR: 0.020000
Training Epoch: 13 [4864/9494]	Loss: 0.3748	LR: 0.020000
Training Epoch: 13 [5120/9494]	Loss: 0.4378	LR: 0.020000
Training Epoch: 13 [5376/9494]	Loss: 0.4334	LR: 0.020000
Training Epoch: 13 [5632/9494]	Loss: 0.3844	LR: 0.020000
Training Epoch: 13 [5888/9494]	Loss: 0.3631	LR: 0.020000
Training Epoch: 13 [6144/9494]	Loss: 0.4184	LR: 0.020000
Training Epoch: 13 [6400/9494]	Loss: 0.4226	LR: 0.020000
Training Epoch: 13 [6656/9494]	Loss: 0.3898	LR: 0.020000
Training Epoch: 13 [6912/9494]	Loss: 0.3424	LR: 0.020000
Training Epoch: 13 [7168/9494]	Loss: 0.4304	LR: 0.020000
Training Epoch: 13 [7424/9494]	Loss: 0.4689	LR: 0.020000
Training Epoch: 13 [7680/9494]	Loss: 0.3856	LR: 0.020000
Training Epoch: 13 [7936/9494]	Loss: 0.4236	LR: 0.020000
Training Epoch: 13 [8192/9494]	Loss: 0.4244	LR: 0.020000
Training Epoch: 13 [8448/9494]	Loss: 0.4099	LR: 0.020000
Training Epoch: 13 [8704/9494]	Loss: 0.3925	LR: 0.020000
Training Epoch: 13 [8960/9494]	Loss: 0.4208	LR: 0.020000
Training Epoch: 13 [9216/9494]	Loss: 0.3750	LR: 0.020000
Training Epoch: 13 [9472/9494]	Loss: 0.3846	LR: 0.020000
Training Epoch: 13 [9494/9494]	Loss: 0.2467	LR: 0.020000
Epoch 13 - Average Train Loss: 0.4159, Train Accuracy: 0.8105
Epoch 13 training time consumed: 136.41s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0021, Accuracy: 0.7855, Time consumed:7.96s
Training Epoch: 14 [256/9494]	Loss: 0.4100	LR: 0.020000
Training Epoch: 14 [512/9494]	Loss: 0.4536	LR: 0.020000
Training Epoch: 14 [768/9494]	Loss: 0.4454	LR: 0.020000
Training Epoch: 14 [1024/9494]	Loss: 0.4252	LR: 0.020000
Training Epoch: 14 [1280/9494]	Loss: 0.4604	LR: 0.020000
Training Epoch: 14 [1536/9494]	Loss: 0.4365	LR: 0.020000
Training Epoch: 14 [1792/9494]	Loss: 0.4304	LR: 0.020000
Training Epoch: 14 [2048/9494]	Loss: 0.3777	LR: 0.020000
Training Epoch: 14 [2304/9494]	Loss: 0.3463	LR: 0.020000
Training Epoch: 14 [2560/9494]	Loss: 0.4328	LR: 0.020000
Training Epoch: 14 [2816/9494]	Loss: 0.3611	LR: 0.020000
Training Epoch: 14 [3072/9494]	Loss: 0.4708	LR: 0.020000
Training Epoch: 14 [3328/9494]	Loss: 0.3800	LR: 0.020000
Training Epoch: 14 [3584/9494]	Loss: 0.4093	LR: 0.020000
Training Epoch: 14 [3840/9494]	Loss: 0.3897	LR: 0.020000
Training Epoch: 14 [4096/9494]	Loss: 0.4947	LR: 0.020000
Training Epoch: 14 [4352/9494]	Loss: 0.4508	LR: 0.020000
Training Epoch: 14 [4608/9494]	Loss: 0.4039	LR: 0.020000
Training Epoch: 14 [4864/9494]	Loss: 0.4172	LR: 0.020000
Training Epoch: 14 [5120/9494]	Loss: 0.4064	LR: 0.020000
Training Epoch: 14 [5376/9494]	Loss: 0.3811	LR: 0.020000
Training Epoch: 14 [5632/9494]	Loss: 0.3692	LR: 0.020000
Training Epoch: 14 [5888/9494]	Loss: 0.4225	LR: 0.020000
Training Epoch: 14 [6144/9494]	Loss: 0.3261	LR: 0.020000
Training Epoch: 14 [6400/9494]	Loss: 0.3495	LR: 0.020000
Training Epoch: 14 [6656/9494]	Loss: 0.3825	LR: 0.020000
Training Epoch: 14 [6912/9494]	Loss: 0.3569	LR: 0.020000
Training Epoch: 14 [7168/9494]	Loss: 0.3997	LR: 0.020000
Training Epoch: 14 [7424/9494]	Loss: 0.3450	LR: 0.020000
Training Epoch: 14 [7680/9494]	Loss: 0.3806	LR: 0.020000
Training Epoch: 14 [7936/9494]	Loss: 0.4108	LR: 0.020000
Training Epoch: 14 [8192/9494]	Loss: 0.3683	LR: 0.020000
Training Epoch: 14 [8448/9494]	Loss: 0.3455	LR: 0.020000
Training Epoch: 14 [8704/9494]	Loss: 0.3508	LR: 0.020000
Training Epoch: 14 [8960/9494]	Loss: 0.4342	LR: 0.020000
Training Epoch: 14 [9216/9494]	Loss: 0.3192	LR: 0.020000
Training Epoch: 14 [9472/9494]	Loss: 0.3955	LR: 0.020000
Training Epoch: 14 [9494/9494]	Loss: 0.4110	LR: 0.020000
Epoch 14 - Average Train Loss: 0.3984, Train Accuracy: 0.8212
Epoch 14 training time consumed: 135.88s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0016, Accuracy: 0.8387, Time consumed:7.94s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-14-best.pth
Training Epoch: 15 [256/9494]	Loss: 0.3886	LR: 0.020000
Training Epoch: 15 [512/9494]	Loss: 0.4375	LR: 0.020000
Training Epoch: 15 [768/9494]	Loss: 0.3753	LR: 0.020000
Training Epoch: 15 [1024/9494]	Loss: 0.3913	LR: 0.020000
Training Epoch: 15 [1280/9494]	Loss: 0.3819	LR: 0.020000
Training Epoch: 15 [1536/9494]	Loss: 0.3879	LR: 0.020000
Training Epoch: 15 [1792/9494]	Loss: 0.3596	LR: 0.020000
Training Epoch: 15 [2048/9494]	Loss: 0.4093	LR: 0.020000
Training Epoch: 15 [2304/9494]	Loss: 0.3510	LR: 0.020000
Training Epoch: 15 [2560/9494]	Loss: 0.3567	LR: 0.020000
Training Epoch: 15 [2816/9494]	Loss: 0.3592	LR: 0.020000
Training Epoch: 15 [3072/9494]	Loss: 0.3651	LR: 0.020000
Training Epoch: 15 [3328/9494]	Loss: 0.3831	LR: 0.020000
Training Epoch: 15 [3584/9494]	Loss: 0.3420	LR: 0.020000
Training Epoch: 15 [3840/9494]	Loss: 0.3574	LR: 0.020000
Training Epoch: 15 [4096/9494]	Loss: 0.3322	LR: 0.020000
Training Epoch: 15 [4352/9494]	Loss: 0.3481	LR: 0.020000
Training Epoch: 15 [4608/9494]	Loss: 0.3935	LR: 0.020000
Training Epoch: 15 [4864/9494]	Loss: 0.3726	LR: 0.020000
Training Epoch: 15 [5120/9494]	Loss: 0.3641	LR: 0.020000
Training Epoch: 15 [5376/9494]	Loss: 0.3681	LR: 0.020000
Training Epoch: 15 [5632/9494]	Loss: 0.4428	LR: 0.020000
Training Epoch: 15 [5888/9494]	Loss: 0.4107	LR: 0.020000
Training Epoch: 15 [6144/9494]	Loss: 0.3417	LR: 0.020000
Training Epoch: 15 [6400/9494]	Loss: 0.3115	LR: 0.020000
Training Epoch: 15 [6656/9494]	Loss: 0.3624	LR: 0.020000
Training Epoch: 15 [6912/9494]	Loss: 0.3330	LR: 0.020000
Training Epoch: 15 [7168/9494]	Loss: 0.3605	LR: 0.020000
Training Epoch: 15 [7424/9494]	Loss: 0.3853	LR: 0.020000
Training Epoch: 15 [7680/9494]	Loss: 0.3784	LR: 0.020000
Training Epoch: 15 [7936/9494]	Loss: 0.3628	LR: 0.020000
Training Epoch: 15 [8192/9494]	Loss: 0.3676	LR: 0.020000
Training Epoch: 15 [8448/9494]	Loss: 0.3796	LR: 0.020000
Training Epoch: 15 [8704/9494]	Loss: 0.3192	LR: 0.020000
Training Epoch: 15 [8960/9494]	Loss: 0.3073	LR: 0.020000
Training Epoch: 15 [9216/9494]	Loss: 0.3561	LR: 0.020000
Training Epoch: 15 [9472/9494]	Loss: 0.3946	LR: 0.020000
Training Epoch: 15 [9494/9494]	Loss: 0.3972	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3687, Train Accuracy: 0.8374
Epoch 15 training time consumed: 135.86s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0015, Accuracy: 0.8499, Time consumed:7.89s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-15-best.pth
Training Epoch: 16 [256/9494]	Loss: 0.3559	LR: 0.020000
Training Epoch: 16 [512/9494]	Loss: 0.3957	LR: 0.020000
Training Epoch: 16 [768/9494]	Loss: 0.4241	LR: 0.020000
Training Epoch: 16 [1024/9494]	Loss: 0.3659	LR: 0.020000
Training Epoch: 16 [1280/9494]	Loss: 0.3467	LR: 0.020000
Training Epoch: 16 [1536/9494]	Loss: 0.3948	LR: 0.020000
Training Epoch: 16 [1792/9494]	Loss: 0.3176	LR: 0.020000
Training Epoch: 16 [2048/9494]	Loss: 0.3099	LR: 0.020000
Training Epoch: 16 [2304/9494]	Loss: 0.3684	LR: 0.020000
Training Epoch: 16 [2560/9494]	Loss: 0.3792	LR: 0.020000
Training Epoch: 16 [2816/9494]	Loss: 0.3337	LR: 0.020000
Training Epoch: 16 [3072/9494]	Loss: 0.3682	LR: 0.020000
Training Epoch: 16 [3328/9494]	Loss: 0.4159	LR: 0.020000
Training Epoch: 16 [3584/9494]	Loss: 0.3372	LR: 0.020000
Training Epoch: 16 [3840/9494]	Loss: 0.3276	LR: 0.020000
Training Epoch: 16 [4096/9494]	Loss: 0.2629	LR: 0.020000
Training Epoch: 16 [4352/9494]	Loss: 0.3276	LR: 0.020000
Training Epoch: 16 [4608/9494]	Loss: 0.4174	LR: 0.020000
Training Epoch: 16 [4864/9494]	Loss: 0.3444	LR: 0.020000
Training Epoch: 16 [5120/9494]	Loss: 0.3430	LR: 0.020000
Training Epoch: 16 [5376/9494]	Loss: 0.2935	LR: 0.020000
Training Epoch: 16 [5632/9494]	Loss: 0.4071	LR: 0.020000
Training Epoch: 16 [5888/9494]	Loss: 0.2924	LR: 0.020000
Training Epoch: 16 [6144/9494]	Loss: 0.2980	LR: 0.020000
Training Epoch: 16 [6400/9494]	Loss: 0.3028	LR: 0.020000
Training Epoch: 16 [6656/9494]	Loss: 0.2854	LR: 0.020000
Training Epoch: 16 [6912/9494]	Loss: 0.3095	LR: 0.020000
Training Epoch: 16 [7168/9494]	Loss: 0.3183	LR: 0.020000
Training Epoch: 16 [7424/9494]	Loss: 0.3859	LR: 0.020000
Training Epoch: 16 [7680/9494]	Loss: 0.3190	LR: 0.020000
Training Epoch: 16 [7936/9494]	Loss: 0.3730	LR: 0.020000
Training Epoch: 16 [8192/9494]	Loss: 0.4512	LR: 0.020000
Training Epoch: 16 [8448/9494]	Loss: 0.4045	LR: 0.020000
Training Epoch: 16 [8704/9494]	Loss: 0.3895	LR: 0.020000
Training Epoch: 16 [8960/9494]	Loss: 0.3402	LR: 0.020000
Training Epoch: 16 [9216/9494]	Loss: 0.2939	LR: 0.020000
Training Epoch: 16 [9472/9494]	Loss: 0.2986	LR: 0.020000
Training Epoch: 16 [9494/9494]	Loss: 0.1727	LR: 0.020000
Epoch 16 - Average Train Loss: 0.3482, Train Accuracy: 0.8490
Epoch 16 training time consumed: 136.06s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0014, Accuracy: 0.8644, Time consumed:7.92s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-16-best.pth
Training Epoch: 17 [256/9494]	Loss: 0.3043	LR: 0.020000
Training Epoch: 17 [512/9494]	Loss: 0.2208	LR: 0.020000
Training Epoch: 17 [768/9494]	Loss: 0.2855	LR: 0.020000
Training Epoch: 17 [1024/9494]	Loss: 0.3670	LR: 0.020000
Training Epoch: 17 [1280/9494]	Loss: 0.2867	LR: 0.020000
Training Epoch: 17 [1536/9494]	Loss: 0.2634	LR: 0.020000
Training Epoch: 17 [1792/9494]	Loss: 0.3181	LR: 0.020000
Training Epoch: 17 [2048/9494]	Loss: 0.2865	LR: 0.020000
Training Epoch: 17 [2304/9494]	Loss: 0.2937	LR: 0.020000
Training Epoch: 17 [2560/9494]	Loss: 0.3891	LR: 0.020000
Training Epoch: 17 [2816/9494]	Loss: 0.2881	LR: 0.020000
Training Epoch: 17 [3072/9494]	Loss: 0.3409	LR: 0.020000
Training Epoch: 17 [3328/9494]	Loss: 0.2541	LR: 0.020000
Training Epoch: 17 [3584/9494]	Loss: 0.3346	LR: 0.020000
Training Epoch: 17 [3840/9494]	Loss: 0.3492	LR: 0.020000
Training Epoch: 17 [4096/9494]	Loss: 0.2594	LR: 0.020000
Training Epoch: 17 [4352/9494]	Loss: 0.3486	LR: 0.020000
Training Epoch: 17 [4608/9494]	Loss: 0.3067	LR: 0.020000
Training Epoch: 17 [4864/9494]	Loss: 0.3376	LR: 0.020000
Training Epoch: 17 [5120/9494]	Loss: 0.3407	LR: 0.020000
Training Epoch: 17 [5376/9494]	Loss: 0.2812	LR: 0.020000
Training Epoch: 17 [5632/9494]	Loss: 0.3135	LR: 0.020000
Training Epoch: 17 [5888/9494]	Loss: 0.2994	LR: 0.020000
Training Epoch: 17 [6144/9494]	Loss: 0.3862	LR: 0.020000
Training Epoch: 17 [6400/9494]	Loss: 0.2850	LR: 0.020000
Training Epoch: 17 [6656/9494]	Loss: 0.3909	LR: 0.020000
Training Epoch: 17 [6912/9494]	Loss: 0.3298	LR: 0.020000
Training Epoch: 17 [7168/9494]	Loss: 0.3040	LR: 0.020000
Training Epoch: 17 [7424/9494]	Loss: 0.2860	LR: 0.020000
Training Epoch: 17 [7680/9494]	Loss: 0.3386	LR: 0.020000
Training Epoch: 17 [7936/9494]	Loss: 0.3193	LR: 0.020000
Training Epoch: 17 [8192/9494]	Loss: 0.3159	LR: 0.020000
Training Epoch: 17 [8448/9494]	Loss: 0.3169	LR: 0.020000
Training Epoch: 17 [8704/9494]	Loss: 0.2805	LR: 0.020000
Training Epoch: 17 [8960/9494]	Loss: 0.2397	LR: 0.020000
Training Epoch: 17 [9216/9494]	Loss: 0.2921	LR: 0.020000
Training Epoch: 17 [9472/9494]	Loss: 0.3307	LR: 0.020000
Training Epoch: 17 [9494/9494]	Loss: 0.1189	LR: 0.020000
Epoch 17 - Average Train Loss: 0.3100, Train Accuracy: 0.8676
Epoch 17 training time consumed: 137.80s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0014, Accuracy: 0.8717, Time consumed:7.85s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-17-best.pth
Training Epoch: 18 [256/9494]	Loss: 0.3287	LR: 0.020000
Training Epoch: 18 [512/9494]	Loss: 0.3575	LR: 0.020000
Training Epoch: 18 [768/9494]	Loss: 0.2573	LR: 0.020000
Training Epoch: 18 [1024/9494]	Loss: 0.3301	LR: 0.020000
Training Epoch: 18 [1280/9494]	Loss: 0.3786	LR: 0.020000
Training Epoch: 18 [1536/9494]	Loss: 0.3191	LR: 0.020000
Training Epoch: 18 [1792/9494]	Loss: 0.2840	LR: 0.020000
Training Epoch: 18 [2048/9494]	Loss: 0.2953	LR: 0.020000
Training Epoch: 18 [2304/9494]	Loss: 0.2944	LR: 0.020000
Training Epoch: 18 [2560/9494]	Loss: 0.3072	LR: 0.020000
Training Epoch: 18 [2816/9494]	Loss: 0.3302	LR: 0.020000
Training Epoch: 18 [3072/9494]	Loss: 0.2454	LR: 0.020000
Training Epoch: 18 [3328/9494]	Loss: 0.2648	LR: 0.020000
Training Epoch: 18 [3584/9494]	Loss: 0.2997	LR: 0.020000
Training Epoch: 18 [3840/9494]	Loss: 0.2993	LR: 0.020000
Training Epoch: 18 [4096/9494]	Loss: 0.2739	LR: 0.020000
Training Epoch: 18 [4352/9494]	Loss: 0.3410	LR: 0.020000
Training Epoch: 18 [4608/9494]	Loss: 0.2898	LR: 0.020000
Training Epoch: 18 [4864/9494]	Loss: 0.2644	LR: 0.020000
Training Epoch: 18 [5120/9494]	Loss: 0.4099	LR: 0.020000
Training Epoch: 18 [5376/9494]	Loss: 0.2374	LR: 0.020000
Training Epoch: 18 [5632/9494]	Loss: 0.2986	LR: 0.020000
Training Epoch: 18 [5888/9494]	Loss: 0.2662	LR: 0.020000
Training Epoch: 18 [6144/9494]	Loss: 0.3021	LR: 0.020000
Training Epoch: 18 [6400/9494]	Loss: 0.2960	LR: 0.020000
Training Epoch: 18 [6656/9494]	Loss: 0.2593	LR: 0.020000
Training Epoch: 18 [6912/9494]	Loss: 0.2908	LR: 0.020000
Training Epoch: 18 [7168/9494]	Loss: 0.2727	LR: 0.020000
Training Epoch: 18 [7424/9494]	Loss: 0.3150	LR: 0.020000
Training Epoch: 18 [7680/9494]	Loss: 0.2787	LR: 0.020000
Training Epoch: 18 [7936/9494]	Loss: 0.2938	LR: 0.020000
Training Epoch: 18 [8192/9494]	Loss: 0.3035	LR: 0.020000
Training Epoch: 18 [8448/9494]	Loss: 0.2393	LR: 0.020000
Training Epoch: 18 [8704/9494]	Loss: 0.3153	LR: 0.020000
Training Epoch: 18 [8960/9494]	Loss: 0.2187	LR: 0.020000
Training Epoch: 18 [9216/9494]	Loss: 0.2324	LR: 0.020000
Training Epoch: 18 [9472/9494]	Loss: 0.3261	LR: 0.020000
Training Epoch: 18 [9494/9494]	Loss: 0.4636	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2954, Train Accuracy: 0.8775
Epoch 18 training time consumed: 136.77s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0022, Accuracy: 0.7952, Time consumed:7.62s
Training Epoch: 19 [256/9494]	Loss: 0.2944	LR: 0.020000
Training Epoch: 19 [512/9494]	Loss: 0.3135	LR: 0.020000
Training Epoch: 19 [768/9494]	Loss: 0.4057	LR: 0.020000
Training Epoch: 19 [1024/9494]	Loss: 0.3631	LR: 0.020000
Training Epoch: 19 [1280/9494]	Loss: 0.3235	LR: 0.020000
Training Epoch: 19 [1536/9494]	Loss: 0.3163	LR: 0.020000
Training Epoch: 19 [1792/9494]	Loss: 0.2931	LR: 0.020000
Training Epoch: 19 [2048/9494]	Loss: 0.3207	LR: 0.020000
Training Epoch: 19 [2304/9494]	Loss: 0.3271	LR: 0.020000
Training Epoch: 19 [2560/9494]	Loss: 0.3354	LR: 0.020000
Training Epoch: 19 [2816/9494]	Loss: 0.2415	LR: 0.020000
Training Epoch: 19 [3072/9494]	Loss: 0.3063	LR: 0.020000
Training Epoch: 19 [3328/9494]	Loss: 0.2566	LR: 0.020000
Training Epoch: 19 [3584/9494]	Loss: 0.2667	LR: 0.020000
Training Epoch: 19 [3840/9494]	Loss: 0.3151	LR: 0.020000
Training Epoch: 19 [4096/9494]	Loss: 0.3593	LR: 0.020000
Training Epoch: 19 [4352/9494]	Loss: 0.3033	LR: 0.020000
Training Epoch: 19 [4608/9494]	Loss: 0.3338	LR: 0.020000
Training Epoch: 19 [4864/9494]	Loss: 0.2990	LR: 0.020000
Training Epoch: 19 [5120/9494]	Loss: 0.2902	LR: 0.020000
Training Epoch: 19 [5376/9494]	Loss: 0.2764	LR: 0.020000
Training Epoch: 19 [5632/9494]	Loss: 0.2583	LR: 0.020000
Training Epoch: 19 [5888/9494]	Loss: 0.2272	LR: 0.020000
Training Epoch: 19 [6144/9494]	Loss: 0.2982	LR: 0.020000
Training Epoch: 19 [6400/9494]	Loss: 0.2436	LR: 0.020000
Training Epoch: 19 [6656/9494]	Loss: 0.3225	LR: 0.020000
Training Epoch: 19 [6912/9494]	Loss: 0.2608	LR: 0.020000
Training Epoch: 19 [7168/9494]	Loss: 0.2661	LR: 0.020000
Training Epoch: 19 [7424/9494]	Loss: 0.2744	LR: 0.020000
Training Epoch: 19 [7680/9494]	Loss: 0.3065	LR: 0.020000
Training Epoch: 19 [7936/9494]	Loss: 0.2755	LR: 0.020000
Training Epoch: 19 [8192/9494]	Loss: 0.2831	LR: 0.020000
Training Epoch: 19 [8448/9494]	Loss: 0.3287	LR: 0.020000
Training Epoch: 19 [8704/9494]	Loss: 0.2317	LR: 0.020000
Training Epoch: 19 [8960/9494]	Loss: 0.3089	LR: 0.020000
Training Epoch: 19 [9216/9494]	Loss: 0.3019	LR: 0.020000
Training Epoch: 19 [9472/9494]	Loss: 0.2604	LR: 0.020000
Training Epoch: 19 [9494/9494]	Loss: 0.3472	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2971, Train Accuracy: 0.8714
Epoch 19 training time consumed: 135.64s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0016, Accuracy: 0.8484, Time consumed:7.88s
Training Epoch: 20 [256/9494]	Loss: 0.2660	LR: 0.004000
Training Epoch: 20 [512/9494]	Loss: 0.2511	LR: 0.004000
Training Epoch: 20 [768/9494]	Loss: 0.2666	LR: 0.004000
Training Epoch: 20 [1024/9494]	Loss: 0.2790	LR: 0.004000
Training Epoch: 20 [1280/9494]	Loss: 0.3199	LR: 0.004000
Training Epoch: 20 [1536/9494]	Loss: 0.3250	LR: 0.004000
Training Epoch: 20 [1792/9494]	Loss: 0.2481	LR: 0.004000
Training Epoch: 20 [2048/9494]	Loss: 0.2641	LR: 0.004000
Training Epoch: 20 [2304/9494]	Loss: 0.2436	LR: 0.004000
Training Epoch: 20 [2560/9494]	Loss: 0.2785	LR: 0.004000
Training Epoch: 20 [2816/9494]	Loss: 0.2006	LR: 0.004000
Training Epoch: 20 [3072/9494]	Loss: 0.2704	LR: 0.004000
Training Epoch: 20 [3328/9494]	Loss: 0.2433	LR: 0.004000
Training Epoch: 20 [3584/9494]	Loss: 0.2845	LR: 0.004000
Training Epoch: 20 [3840/9494]	Loss: 0.2859	LR: 0.004000
Training Epoch: 20 [4096/9494]	Loss: 0.2300	LR: 0.004000
Training Epoch: 20 [4352/9494]	Loss: 0.2544	LR: 0.004000
Training Epoch: 20 [4608/9494]	Loss: 0.2560	LR: 0.004000
Training Epoch: 20 [4864/9494]	Loss: 0.2147	LR: 0.004000
Training Epoch: 20 [5120/9494]	Loss: 0.2686	LR: 0.004000
Training Epoch: 20 [5376/9494]	Loss: 0.2340	LR: 0.004000
Training Epoch: 20 [5632/9494]	Loss: 0.2646	LR: 0.004000
Training Epoch: 20 [5888/9494]	Loss: 0.2404	LR: 0.004000
Training Epoch: 20 [6144/9494]	Loss: 0.2547	LR: 0.004000
Training Epoch: 20 [6400/9494]	Loss: 0.2611	LR: 0.004000
Training Epoch: 20 [6656/9494]	Loss: 0.2290	LR: 0.004000
Training Epoch: 20 [6912/9494]	Loss: 0.2854	LR: 0.004000
Training Epoch: 20 [7168/9494]	Loss: 0.1986	LR: 0.004000
Training Epoch: 20 [7424/9494]	Loss: 0.2676	LR: 0.004000
Training Epoch: 20 [7680/9494]	Loss: 0.3521	LR: 0.004000
Training Epoch: 20 [7936/9494]	Loss: 0.2352	LR: 0.004000
Training Epoch: 20 [8192/9494]	Loss: 0.2930	LR: 0.004000
Training Epoch: 20 [8448/9494]	Loss: 0.2009	LR: 0.004000
Training Epoch: 20 [8704/9494]	Loss: 0.2035	LR: 0.004000
Training Epoch: 20 [8960/9494]	Loss: 0.2515	LR: 0.004000
Training Epoch: 20 [9216/9494]	Loss: 0.1797	LR: 0.004000
Training Epoch: 20 [9472/9494]	Loss: 0.2170	LR: 0.004000
Training Epoch: 20 [9494/9494]	Loss: 0.2892	LR: 0.004000
Epoch 20 - Average Train Loss: 0.2546, Train Accuracy: 0.8927
Epoch 20 training time consumed: 140.24s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0009, Accuracy: 0.9080, Time consumed:7.74s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-20-best.pth
Training Epoch: 21 [256/9494]	Loss: 0.2590	LR: 0.004000
Training Epoch: 21 [512/9494]	Loss: 0.1822	LR: 0.004000
Training Epoch: 21 [768/9494]	Loss: 0.2044	LR: 0.004000
Training Epoch: 21 [1024/9494]	Loss: 0.3071	LR: 0.004000
Training Epoch: 21 [1280/9494]	Loss: 0.2163	LR: 0.004000
Training Epoch: 21 [1536/9494]	Loss: 0.2416	LR: 0.004000
Training Epoch: 21 [1792/9494]	Loss: 0.2647	LR: 0.004000
Training Epoch: 21 [2048/9494]	Loss: 0.2350	LR: 0.004000
Training Epoch: 21 [2304/9494]	Loss: 0.2295	LR: 0.004000
Training Epoch: 21 [2560/9494]	Loss: 0.2283	LR: 0.004000
Training Epoch: 21 [2816/9494]	Loss: 0.2299	LR: 0.004000
Training Epoch: 21 [3072/9494]	Loss: 0.1767	LR: 0.004000
Training Epoch: 21 [3328/9494]	Loss: 0.2390	LR: 0.004000
Training Epoch: 21 [3584/9494]	Loss: 0.2553	LR: 0.004000
Training Epoch: 21 [3840/9494]	Loss: 0.2497	LR: 0.004000
Training Epoch: 21 [4096/9494]	Loss: 0.1967	LR: 0.004000
Training Epoch: 21 [4352/9494]	Loss: 0.2120	LR: 0.004000
Training Epoch: 21 [4608/9494]	Loss: 0.2478	LR: 0.004000
Training Epoch: 21 [4864/9494]	Loss: 0.2673	LR: 0.004000
Training Epoch: 21 [5120/9494]	Loss: 0.2616	LR: 0.004000
Training Epoch: 21 [5376/9494]	Loss: 0.2155	LR: 0.004000
Training Epoch: 21 [5632/9494]	Loss: 0.2234	LR: 0.004000
Training Epoch: 21 [5888/9494]	Loss: 0.2569	LR: 0.004000
Training Epoch: 21 [6144/9494]	Loss: 0.2201	LR: 0.004000
Training Epoch: 21 [6400/9494]	Loss: 0.2400	LR: 0.004000
Training Epoch: 21 [6656/9494]	Loss: 0.2561	LR: 0.004000
Training Epoch: 21 [6912/9494]	Loss: 0.2133	LR: 0.004000
Training Epoch: 21 [7168/9494]	Loss: 0.1794	LR: 0.004000
Training Epoch: 21 [7424/9494]	Loss: 0.1762	LR: 0.004000
Training Epoch: 21 [7680/9494]	Loss: 0.2085	LR: 0.004000
Training Epoch: 21 [7936/9494]	Loss: 0.1980	LR: 0.004000
Training Epoch: 21 [8192/9494]	Loss: 0.1815	LR: 0.004000
Training Epoch: 21 [8448/9494]	Loss: 0.2343	LR: 0.004000
Training Epoch: 21 [8704/9494]	Loss: 0.2375	LR: 0.004000
Training Epoch: 21 [8960/9494]	Loss: 0.2568	LR: 0.004000
Training Epoch: 21 [9216/9494]	Loss: 0.2475	LR: 0.004000
Training Epoch: 21 [9472/9494]	Loss: 0.2142	LR: 0.004000
Training Epoch: 21 [9494/9494]	Loss: 0.2488	LR: 0.004000
Epoch 21 - Average Train Loss: 0.2288, Train Accuracy: 0.9078
Epoch 21 training time consumed: 136.49s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0010, Accuracy: 0.8993, Time consumed:7.87s
Training Epoch: 22 [256/9494]	Loss: 0.2252	LR: 0.004000
Training Epoch: 22 [512/9494]	Loss: 0.2583	LR: 0.004000
Training Epoch: 22 [768/9494]	Loss: 0.2608	LR: 0.004000
Training Epoch: 22 [1024/9494]	Loss: 0.2594	LR: 0.004000
Training Epoch: 22 [1280/9494]	Loss: 0.2393	LR: 0.004000
Training Epoch: 22 [1536/9494]	Loss: 0.2009	LR: 0.004000
Training Epoch: 22 [1792/9494]	Loss: 0.2493	LR: 0.004000
Training Epoch: 22 [2048/9494]	Loss: 0.2565	LR: 0.004000
Training Epoch: 22 [2304/9494]	Loss: 0.1941	LR: 0.004000
Training Epoch: 22 [2560/9494]	Loss: 0.2443	LR: 0.004000
Training Epoch: 22 [2816/9494]	Loss: 0.2146	LR: 0.004000
Training Epoch: 22 [3072/9494]	Loss: 0.1742	LR: 0.004000
Training Epoch: 22 [3328/9494]	Loss: 0.2112	LR: 0.004000
Training Epoch: 22 [3584/9494]	Loss: 0.2220	LR: 0.004000
Training Epoch: 22 [3840/9494]	Loss: 0.2430	LR: 0.004000
Training Epoch: 22 [4096/9494]	Loss: 0.2562	LR: 0.004000
Training Epoch: 22 [4352/9494]	Loss: 0.1749	LR: 0.004000
Training Epoch: 22 [4608/9494]	Loss: 0.2087	LR: 0.004000
Training Epoch: 22 [4864/9494]	Loss: 0.2371	LR: 0.004000
Training Epoch: 22 [5120/9494]	Loss: 0.2244	LR: 0.004000
Training Epoch: 22 [5376/9494]	Loss: 0.2540	LR: 0.004000
Training Epoch: 22 [5632/9494]	Loss: 0.2102	LR: 0.004000
Training Epoch: 22 [5888/9494]	Loss: 0.2037	LR: 0.004000
Training Epoch: 22 [6144/9494]	Loss: 0.2597	LR: 0.004000
Training Epoch: 22 [6400/9494]	Loss: 0.1875	LR: 0.004000
Training Epoch: 22 [6656/9494]	Loss: 0.2136	LR: 0.004000
Training Epoch: 22 [6912/9494]	Loss: 0.1964	LR: 0.004000
Training Epoch: 22 [7168/9494]	Loss: 0.2385	LR: 0.004000
Training Epoch: 22 [7424/9494]	Loss: 0.2077	LR: 0.004000
Training Epoch: 22 [7680/9494]	Loss: 0.1949	LR: 0.004000
Training Epoch: 22 [7936/9494]	Loss: 0.1645	LR: 0.004000
Training Epoch: 22 [8192/9494]	Loss: 0.2228	LR: 0.004000
Training Epoch: 22 [8448/9494]	Loss: 0.2708	LR: 0.004000
Training Epoch: 22 [8704/9494]	Loss: 0.2505	LR: 0.004000
Training Epoch: 22 [8960/9494]	Loss: 0.2420	LR: 0.004000
Training Epoch: 22 [9216/9494]	Loss: 0.2066	LR: 0.004000
Training Epoch: 22 [9472/9494]	Loss: 0.2631	LR: 0.004000
Training Epoch: 22 [9494/9494]	Loss: 0.3163	LR: 0.004000
Epoch 22 - Average Train Loss: 0.2256, Train Accuracy: 0.9046
Epoch 22 training time consumed: 136.43s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0009, Accuracy: 0.9119, Time consumed:8.03s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-22-best.pth
Training Epoch: 23 [256/9494]	Loss: 0.2296	LR: 0.004000
Training Epoch: 23 [512/9494]	Loss: 0.1926	LR: 0.004000
Training Epoch: 23 [768/9494]	Loss: 0.2197	LR: 0.004000
Training Epoch: 23 [1024/9494]	Loss: 0.2064	LR: 0.004000
Training Epoch: 23 [1280/9494]	Loss: 0.2243	LR: 0.004000
Training Epoch: 23 [1536/9494]	Loss: 0.1978	LR: 0.004000
Training Epoch: 23 [1792/9494]	Loss: 0.2460	LR: 0.004000
Training Epoch: 23 [2048/9494]	Loss: 0.1708	LR: 0.004000
Training Epoch: 23 [2304/9494]	Loss: 0.2095	LR: 0.004000
Training Epoch: 23 [2560/9494]	Loss: 0.1921	LR: 0.004000
Training Epoch: 23 [2816/9494]	Loss: 0.1898	LR: 0.004000
Training Epoch: 23 [3072/9494]	Loss: 0.1631	LR: 0.004000
Training Epoch: 23 [3328/9494]	Loss: 0.1712	LR: 0.004000
Training Epoch: 23 [3584/9494]	Loss: 0.2388	LR: 0.004000
Training Epoch: 23 [3840/9494]	Loss: 0.1906	LR: 0.004000
Training Epoch: 23 [4096/9494]	Loss: 0.1792	LR: 0.004000
Training Epoch: 23 [4352/9494]	Loss: 0.2282	LR: 0.004000
Training Epoch: 23 [4608/9494]	Loss: 0.2198	LR: 0.004000
Training Epoch: 23 [4864/9494]	Loss: 0.2194	LR: 0.004000
Training Epoch: 23 [5120/9494]	Loss: 0.1855	LR: 0.004000
Training Epoch: 23 [5376/9494]	Loss: 0.2614	LR: 0.004000
Training Epoch: 23 [5632/9494]	Loss: 0.2561	LR: 0.004000
Training Epoch: 23 [5888/9494]	Loss: 0.2206	LR: 0.004000
Training Epoch: 23 [6144/9494]	Loss: 0.2268	LR: 0.004000
Training Epoch: 23 [6400/9494]	Loss: 0.2431	LR: 0.004000
Training Epoch: 23 [6656/9494]	Loss: 0.2015	LR: 0.004000
Training Epoch: 23 [6912/9494]	Loss: 0.1903	LR: 0.004000
Training Epoch: 23 [7168/9494]	Loss: 0.2038	LR: 0.004000
Training Epoch: 23 [7424/9494]	Loss: 0.1893	LR: 0.004000
Training Epoch: 23 [7680/9494]	Loss: 0.1894	LR: 0.004000
Training Epoch: 23 [7936/9494]	Loss: 0.1929	LR: 0.004000
Training Epoch: 23 [8192/9494]	Loss: 0.2902	LR: 0.004000
Training Epoch: 23 [8448/9494]	Loss: 0.2391	LR: 0.004000
Training Epoch: 23 [8704/9494]	Loss: 0.1756	LR: 0.004000
Training Epoch: 23 [8960/9494]	Loss: 0.2194	LR: 0.004000
Training Epoch: 23 [9216/9494]	Loss: 0.2337	LR: 0.004000
Training Epoch: 23 [9472/9494]	Loss: 0.2270	LR: 0.004000
Training Epoch: 23 [9494/9494]	Loss: 0.4299	LR: 0.004000
Epoch 23 - Average Train Loss: 0.2123, Train Accuracy: 0.9131
Epoch 23 training time consumed: 135.87s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0012, Accuracy: 0.8949, Time consumed:8.06s
Training Epoch: 24 [256/9494]	Loss: 0.1881	LR: 0.004000
Training Epoch: 24 [512/9494]	Loss: 0.2962	LR: 0.004000
Training Epoch: 24 [768/9494]	Loss: 0.3405	LR: 0.004000
Training Epoch: 24 [1024/9494]	Loss: 0.2836	LR: 0.004000
Training Epoch: 24 [1280/9494]	Loss: 0.2540	LR: 0.004000
Training Epoch: 24 [1536/9494]	Loss: 0.1955	LR: 0.004000
Training Epoch: 24 [1792/9494]	Loss: 0.2711	LR: 0.004000
Training Epoch: 24 [2048/9494]	Loss: 0.2216	LR: 0.004000
Training Epoch: 24 [2304/9494]	Loss: 0.2065	LR: 0.004000
Training Epoch: 24 [2560/9494]	Loss: 0.2007	LR: 0.004000
Training Epoch: 24 [2816/9494]	Loss: 0.2210	LR: 0.004000
Training Epoch: 24 [3072/9494]	Loss: 0.2556	LR: 0.004000
Training Epoch: 24 [3328/9494]	Loss: 0.2039	LR: 0.004000
Training Epoch: 24 [3584/9494]	Loss: 0.2227	LR: 0.004000
Training Epoch: 24 [3840/9494]	Loss: 0.2225	LR: 0.004000
Training Epoch: 24 [4096/9494]	Loss: 0.1993	LR: 0.004000
Training Epoch: 24 [4352/9494]	Loss: 0.2326	LR: 0.004000
Training Epoch: 24 [4608/9494]	Loss: 0.1953	LR: 0.004000
Training Epoch: 24 [4864/9494]	Loss: 0.1940	LR: 0.004000
Training Epoch: 24 [5120/9494]	Loss: 0.1856	LR: 0.004000
Training Epoch: 24 [5376/9494]	Loss: 0.1992	LR: 0.004000
Training Epoch: 24 [5632/9494]	Loss: 0.1548	LR: 0.004000
Training Epoch: 24 [5888/9494]	Loss: 0.1674	LR: 0.004000
Training Epoch: 24 [6144/9494]	Loss: 0.3045	LR: 0.004000
Training Epoch: 24 [6400/9494]	Loss: 0.2172	LR: 0.004000
Training Epoch: 24 [6656/9494]	Loss: 0.2411	LR: 0.004000
Training Epoch: 24 [6912/9494]	Loss: 0.2147	LR: 0.004000
Training Epoch: 24 [7168/9494]	Loss: 0.1793	LR: 0.004000
Training Epoch: 24 [7424/9494]	Loss: 0.2443	LR: 0.004000
Training Epoch: 24 [7680/9494]	Loss: 0.1852	LR: 0.004000
Training Epoch: 24 [7936/9494]	Loss: 0.1717	LR: 0.004000
Training Epoch: 24 [8192/9494]	Loss: 0.2117	LR: 0.004000
Training Epoch: 24 [8448/9494]	Loss: 0.1717	LR: 0.004000
Training Epoch: 24 [8704/9494]	Loss: 0.2833	LR: 0.004000
Training Epoch: 24 [8960/9494]	Loss: 0.1882	LR: 0.004000
Training Epoch: 24 [9216/9494]	Loss: 0.2147	LR: 0.004000
Training Epoch: 24 [9472/9494]	Loss: 0.1630	LR: 0.004000
Training Epoch: 24 [9494/9494]	Loss: 0.2654	LR: 0.004000
Epoch 24 - Average Train Loss: 0.2191, Train Accuracy: 0.9116
Epoch 24 training time consumed: 135.82s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0008, Accuracy: 0.9201, Time consumed:8.18s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-24-best.pth
Training Epoch: 25 [256/9494]	Loss: 0.1428	LR: 0.004000
Training Epoch: 25 [512/9494]	Loss: 0.1898	LR: 0.004000
Training Epoch: 25 [768/9494]	Loss: 0.1769	LR: 0.004000
Training Epoch: 25 [1024/9494]	Loss: 0.2715	LR: 0.004000
Training Epoch: 25 [1280/9494]	Loss: 0.2139	LR: 0.004000
Training Epoch: 25 [1536/9494]	Loss: 0.2409	LR: 0.004000
Training Epoch: 25 [1792/9494]	Loss: 0.1875	LR: 0.004000
Training Epoch: 25 [2048/9494]	Loss: 0.2396	LR: 0.004000
Training Epoch: 25 [2304/9494]	Loss: 0.2157	LR: 0.004000
Training Epoch: 25 [2560/9494]	Loss: 0.2452	LR: 0.004000
Training Epoch: 25 [2816/9494]	Loss: 0.2167	LR: 0.004000
Training Epoch: 25 [3072/9494]	Loss: 0.2030	LR: 0.004000
Training Epoch: 25 [3328/9494]	Loss: 0.1443	LR: 0.004000
Training Epoch: 25 [3584/9494]	Loss: 0.2053	LR: 0.004000
Training Epoch: 25 [3840/9494]	Loss: 0.2823	LR: 0.004000
Training Epoch: 25 [4096/9494]	Loss: 0.1672	LR: 0.004000
Training Epoch: 25 [4352/9494]	Loss: 0.2102	LR: 0.004000
Training Epoch: 25 [4608/9494]	Loss: 0.1877	LR: 0.004000
Training Epoch: 25 [4864/9494]	Loss: 0.1530	LR: 0.004000
Training Epoch: 25 [5120/9494]	Loss: 0.1963	LR: 0.004000
Training Epoch: 25 [5376/9494]	Loss: 0.1882	LR: 0.004000
Training Epoch: 25 [5632/9494]	Loss: 0.2124	LR: 0.004000
Training Epoch: 25 [5888/9494]	Loss: 0.1912	LR: 0.004000
Training Epoch: 25 [6144/9494]	Loss: 0.2093	LR: 0.004000
Training Epoch: 25 [6400/9494]	Loss: 0.1956	LR: 0.004000
Training Epoch: 25 [6656/9494]	Loss: 0.2329	LR: 0.004000
Training Epoch: 25 [6912/9494]	Loss: 0.2202	LR: 0.004000
Training Epoch: 25 [7168/9494]	Loss: 0.2623	LR: 0.004000
Training Epoch: 25 [7424/9494]	Loss: 0.2903	LR: 0.004000
Training Epoch: 25 [7680/9494]	Loss: 0.2620	LR: 0.004000
Training Epoch: 25 [7936/9494]	Loss: 0.2123	LR: 0.004000
Training Epoch: 25 [8192/9494]	Loss: 0.1912	LR: 0.004000
Training Epoch: 25 [8448/9494]	Loss: 0.1738	LR: 0.004000
Training Epoch: 25 [8704/9494]	Loss: 0.2124	LR: 0.004000
Training Epoch: 25 [8960/9494]	Loss: 0.1970	LR: 0.004000
Training Epoch: 25 [9216/9494]	Loss: 0.1598	LR: 0.004000
Training Epoch: 25 [9472/9494]	Loss: 0.1782	LR: 0.004000
Training Epoch: 25 [9494/9494]	Loss: 0.1304	LR: 0.004000
Epoch 25 - Average Train Loss: 0.2074, Train Accuracy: 0.9184
Epoch 25 training time consumed: 135.78s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0011, Accuracy: 0.9027, Time consumed:8.04s
Training Epoch: 26 [256/9494]	Loss: 0.1840	LR: 0.004000
Training Epoch: 26 [512/9494]	Loss: 0.2916	LR: 0.004000
Training Epoch: 26 [768/9494]	Loss: 0.2404	LR: 0.004000
Training Epoch: 26 [1024/9494]	Loss: 0.2308	LR: 0.004000
Training Epoch: 26 [1280/9494]	Loss: 0.1539	LR: 0.004000
Training Epoch: 26 [1536/9494]	Loss: 0.2346	LR: 0.004000
Training Epoch: 26 [1792/9494]	Loss: 0.1985	LR: 0.004000
Training Epoch: 26 [2048/9494]	Loss: 0.1765	LR: 0.004000
Training Epoch: 26 [2304/9494]	Loss: 0.1979	LR: 0.004000
Training Epoch: 26 [2560/9494]	Loss: 0.1657	LR: 0.004000
Training Epoch: 26 [2816/9494]	Loss: 0.2004	LR: 0.004000
Training Epoch: 26 [3072/9494]	Loss: 0.1910	LR: 0.004000
Training Epoch: 26 [3328/9494]	Loss: 0.1804	LR: 0.004000
Training Epoch: 26 [3584/9494]	Loss: 0.2083	LR: 0.004000
Training Epoch: 26 [3840/9494]	Loss: 0.2149	LR: 0.004000
Training Epoch: 26 [4096/9494]	Loss: 0.2168	LR: 0.004000
Training Epoch: 26 [4352/9494]	Loss: 0.2210	LR: 0.004000
Training Epoch: 26 [4608/9494]	Loss: 0.1997	LR: 0.004000
Training Epoch: 26 [4864/9494]	Loss: 0.2117	LR: 0.004000
Training Epoch: 26 [5120/9494]	Loss: 0.1536	LR: 0.004000
Training Epoch: 26 [5376/9494]	Loss: 0.2114	LR: 0.004000
Training Epoch: 26 [5632/9494]	Loss: 0.2608	LR: 0.004000
Training Epoch: 26 [5888/9494]	Loss: 0.2347	LR: 0.004000
Training Epoch: 26 [6144/9494]	Loss: 0.2133	LR: 0.004000
Training Epoch: 26 [6400/9494]	Loss: 0.1711	LR: 0.004000
Training Epoch: 26 [6656/9494]	Loss: 0.1868	LR: 0.004000
Training Epoch: 26 [6912/9494]	Loss: 0.1739	LR: 0.004000
Training Epoch: 26 [7168/9494]	Loss: 0.2001	LR: 0.004000
Training Epoch: 26 [7424/9494]	Loss: 0.1800	LR: 0.004000
Training Epoch: 26 [7680/9494]	Loss: 0.1774	LR: 0.004000
Training Epoch: 26 [7936/9494]	Loss: 0.1975	LR: 0.004000
Training Epoch: 26 [8192/9494]	Loss: 0.2362	LR: 0.004000
Training Epoch: 26 [8448/9494]	Loss: 0.2502	LR: 0.004000
Training Epoch: 26 [8704/9494]	Loss: 0.2108	LR: 0.004000
Training Epoch: 26 [8960/9494]	Loss: 0.1818	LR: 0.004000
Training Epoch: 26 [9216/9494]	Loss: 0.1992	LR: 0.004000
Training Epoch: 26 [9472/9494]	Loss: 0.1757	LR: 0.004000
Training Epoch: 26 [9494/9494]	Loss: 0.3550	LR: 0.004000
Epoch 26 - Average Train Loss: 0.2039, Train Accuracy: 0.9146
Epoch 26 training time consumed: 136.20s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0010, Accuracy: 0.9041, Time consumed:7.81s
Training Epoch: 27 [256/9494]	Loss: 0.2674	LR: 0.004000
Training Epoch: 27 [512/9494]	Loss: 0.1760	LR: 0.004000
Training Epoch: 27 [768/9494]	Loss: 0.1558	LR: 0.004000
Training Epoch: 27 [1024/9494]	Loss: 0.1912	LR: 0.004000
Training Epoch: 27 [1280/9494]	Loss: 0.1682	LR: 0.004000
Training Epoch: 27 [1536/9494]	Loss: 0.2042	LR: 0.004000
Training Epoch: 27 [1792/9494]	Loss: 0.2037	LR: 0.004000
Training Epoch: 27 [2048/9494]	Loss: 0.1945	LR: 0.004000
Training Epoch: 27 [2304/9494]	Loss: 0.2062	LR: 0.004000
Training Epoch: 27 [2560/9494]	Loss: 0.2360	LR: 0.004000
Training Epoch: 27 [2816/9494]	Loss: 0.1850	LR: 0.004000
Training Epoch: 27 [3072/9494]	Loss: 0.2286	LR: 0.004000
Training Epoch: 27 [3328/9494]	Loss: 0.1759	LR: 0.004000
Training Epoch: 27 [3584/9494]	Loss: 0.1955	LR: 0.004000
Training Epoch: 27 [3840/9494]	Loss: 0.1690	LR: 0.004000
Training Epoch: 27 [4096/9494]	Loss: 0.2036	LR: 0.004000
Training Epoch: 27 [4352/9494]	Loss: 0.2538	LR: 0.004000
Training Epoch: 27 [4608/9494]	Loss: 0.2204	LR: 0.004000
Training Epoch: 27 [4864/9494]	Loss: 0.2270	LR: 0.004000
Training Epoch: 27 [5120/9494]	Loss: 0.2353	LR: 0.004000
Training Epoch: 27 [5376/9494]	Loss: 0.2184	LR: 0.004000
Training Epoch: 27 [5632/9494]	Loss: 0.1681	LR: 0.004000
Training Epoch: 27 [5888/9494]	Loss: 0.1860	LR: 0.004000
Training Epoch: 27 [6144/9494]	Loss: 0.1848	LR: 0.004000
Training Epoch: 27 [6400/9494]	Loss: 0.2197	LR: 0.004000
Training Epoch: 27 [6656/9494]	Loss: 0.1918	LR: 0.004000
Training Epoch: 27 [6912/9494]	Loss: 0.1998	LR: 0.004000
Training Epoch: 27 [7168/9494]	Loss: 0.1510	LR: 0.004000
Training Epoch: 27 [7424/9494]	Loss: 0.1300	LR: 0.004000
Training Epoch: 27 [7680/9494]	Loss: 0.1919	LR: 0.004000
Training Epoch: 27 [7936/9494]	Loss: 0.2149	LR: 0.004000
Training Epoch: 27 [8192/9494]	Loss: 0.2067	LR: 0.004000
Training Epoch: 27 [8448/9494]	Loss: 0.2276	LR: 0.004000
Training Epoch: 27 [8704/9494]	Loss: 0.1923	LR: 0.004000
Training Epoch: 27 [8960/9494]	Loss: 0.1546	LR: 0.004000
Training Epoch: 27 [9216/9494]	Loss: 0.1911	LR: 0.004000
Training Epoch: 27 [9472/9494]	Loss: 0.1692	LR: 0.004000
Training Epoch: 27 [9494/9494]	Loss: 0.4270	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1977, Train Accuracy: 0.9189
Epoch 27 training time consumed: 136.00s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0008, Accuracy: 0.9182, Time consumed:7.90s
Training Epoch: 28 [256/9494]	Loss: 0.1810	LR: 0.004000
Training Epoch: 28 [512/9494]	Loss: 0.1801	LR: 0.004000
Training Epoch: 28 [768/9494]	Loss: 0.1894	LR: 0.004000
Training Epoch: 28 [1024/9494]	Loss: 0.2014	LR: 0.004000
Training Epoch: 28 [1280/9494]	Loss: 0.1948	LR: 0.004000
Training Epoch: 28 [1536/9494]	Loss: 0.2548	LR: 0.004000
Training Epoch: 28 [1792/9494]	Loss: 0.2282	LR: 0.004000
Training Epoch: 28 [2048/9494]	Loss: 0.2280	LR: 0.004000
Training Epoch: 28 [2304/9494]	Loss: 0.1753	LR: 0.004000
Training Epoch: 28 [2560/9494]	Loss: 0.1802	LR: 0.004000
Training Epoch: 28 [2816/9494]	Loss: 0.2200	LR: 0.004000
Training Epoch: 28 [3072/9494]	Loss: 0.2205	LR: 0.004000
Training Epoch: 28 [3328/9494]	Loss: 0.2158	LR: 0.004000
Training Epoch: 28 [3584/9494]	Loss: 0.1905	LR: 0.004000
Training Epoch: 28 [3840/9494]	Loss: 0.1884	LR: 0.004000
Training Epoch: 28 [4096/9494]	Loss: 0.1972	LR: 0.004000
Training Epoch: 28 [4352/9494]	Loss: 0.2107	LR: 0.004000
Training Epoch: 28 [4608/9494]	Loss: 0.1861	LR: 0.004000
Training Epoch: 28 [4864/9494]	Loss: 0.1961	LR: 0.004000
Training Epoch: 28 [5120/9494]	Loss: 0.2140	LR: 0.004000
Training Epoch: 28 [5376/9494]	Loss: 0.1860	LR: 0.004000
Training Epoch: 28 [5632/9494]	Loss: 0.1510	LR: 0.004000
Training Epoch: 28 [5888/9494]	Loss: 0.1567	LR: 0.004000
Training Epoch: 28 [6144/9494]	Loss: 0.2277	LR: 0.004000
Training Epoch: 28 [6400/9494]	Loss: 0.1841	LR: 0.004000
Training Epoch: 28 [6656/9494]	Loss: 0.1864	LR: 0.004000
Training Epoch: 28 [6912/9494]	Loss: 0.1676	LR: 0.004000
Training Epoch: 28 [7168/9494]	Loss: 0.1986	LR: 0.004000
Training Epoch: 28 [7424/9494]	Loss: 0.2072	LR: 0.004000
Training Epoch: 28 [7680/9494]	Loss: 0.1672	LR: 0.004000
Training Epoch: 28 [7936/9494]	Loss: 0.1598	LR: 0.004000
Training Epoch: 28 [8192/9494]	Loss: 0.2542	LR: 0.004000
Training Epoch: 28 [8448/9494]	Loss: 0.2216	LR: 0.004000
Training Epoch: 28 [8704/9494]	Loss: 0.1839	LR: 0.004000
Training Epoch: 28 [8960/9494]	Loss: 0.2497	LR: 0.004000
Training Epoch: 28 [9216/9494]	Loss: 0.2025	LR: 0.004000
Training Epoch: 28 [9472/9494]	Loss: 0.1869	LR: 0.004000
Training Epoch: 28 [9494/9494]	Loss: 0.1264	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1983, Train Accuracy: 0.9191
Epoch 28 training time consumed: 136.15s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0008, Accuracy: 0.9094, Time consumed:7.87s
Training Epoch: 29 [256/9494]	Loss: 0.1874	LR: 0.004000
Training Epoch: 29 [512/9494]	Loss: 0.2022	LR: 0.004000
Training Epoch: 29 [768/9494]	Loss: 0.1433	LR: 0.004000
Training Epoch: 29 [1024/9494]	Loss: 0.1739	LR: 0.004000
Training Epoch: 29 [1280/9494]	Loss: 0.1481	LR: 0.004000
Training Epoch: 29 [1536/9494]	Loss: 0.1309	LR: 0.004000
Training Epoch: 29 [1792/9494]	Loss: 0.1238	LR: 0.004000
Training Epoch: 29 [2048/9494]	Loss: 0.2553	LR: 0.004000
Training Epoch: 29 [2304/9494]	Loss: 0.1866	LR: 0.004000
Training Epoch: 29 [2560/9494]	Loss: 0.1997	LR: 0.004000
Training Epoch: 29 [2816/9494]	Loss: 0.2223	LR: 0.004000
Training Epoch: 29 [3072/9494]	Loss: 0.1504	LR: 0.004000
Training Epoch: 29 [3328/9494]	Loss: 0.1951	LR: 0.004000
Training Epoch: 29 [3584/9494]	Loss: 0.2089	LR: 0.004000
Training Epoch: 29 [3840/9494]	Loss: 0.2079	LR: 0.004000
Training Epoch: 29 [4096/9494]	Loss: 0.2218	LR: 0.004000
Training Epoch: 29 [4352/9494]	Loss: 0.2259	LR: 0.004000
Training Epoch: 29 [4608/9494]	Loss: 0.1743	LR: 0.004000
Training Epoch: 29 [4864/9494]	Loss: 0.2115	LR: 0.004000
Training Epoch: 29 [5120/9494]	Loss: 0.1443	LR: 0.004000
Training Epoch: 29 [5376/9494]	Loss: 0.1684	LR: 0.004000
Training Epoch: 29 [5632/9494]	Loss: 0.1566	LR: 0.004000
Training Epoch: 29 [5888/9494]	Loss: 0.2278	LR: 0.004000
Training Epoch: 29 [6144/9494]	Loss: 0.1836	LR: 0.004000
Training Epoch: 29 [6400/9494]	Loss: 0.2152	LR: 0.004000
Training Epoch: 29 [6656/9494]	Loss: 0.1844	LR: 0.004000
Training Epoch: 29 [6912/9494]	Loss: 0.1850	LR: 0.004000
Training Epoch: 29 [7168/9494]	Loss: 0.1839	LR: 0.004000
Training Epoch: 29 [7424/9494]	Loss: 0.1807	LR: 0.004000
Training Epoch: 29 [7680/9494]	Loss: 0.1672	LR: 0.004000
Training Epoch: 29 [7936/9494]	Loss: 0.2445	LR: 0.004000
Training Epoch: 29 [8192/9494]	Loss: 0.1545	LR: 0.004000
Training Epoch: 29 [8448/9494]	Loss: 0.2553	LR: 0.004000
Training Epoch: 29 [8704/9494]	Loss: 0.1878	LR: 0.004000
Training Epoch: 29 [8960/9494]	Loss: 0.2243	LR: 0.004000
Training Epoch: 29 [9216/9494]	Loss: 0.1900	LR: 0.004000
Training Epoch: 29 [9472/9494]	Loss: 0.1554	LR: 0.004000
Training Epoch: 29 [9494/9494]	Loss: 0.3890	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1891, Train Accuracy: 0.9230
Epoch 29 training time consumed: 135.98s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0008, Accuracy: 0.9191, Time consumed:8.08s
Training Epoch: 30 [256/9494]	Loss: 0.1542	LR: 0.004000
Training Epoch: 30 [512/9494]	Loss: 0.2579	LR: 0.004000
Training Epoch: 30 [768/9494]	Loss: 0.1501	LR: 0.004000
Training Epoch: 30 [1024/9494]	Loss: 0.1965	LR: 0.004000
Training Epoch: 30 [1280/9494]	Loss: 0.1728	LR: 0.004000
Training Epoch: 30 [1536/9494]	Loss: 0.1761	LR: 0.004000
Training Epoch: 30 [1792/9494]	Loss: 0.2530	LR: 0.004000
Training Epoch: 30 [2048/9494]	Loss: 0.1976	LR: 0.004000
Training Epoch: 30 [2304/9494]	Loss: 0.1690	LR: 0.004000
Training Epoch: 30 [2560/9494]	Loss: 0.1981	LR: 0.004000
Training Epoch: 30 [2816/9494]	Loss: 0.2091	LR: 0.004000
Training Epoch: 30 [3072/9494]	Loss: 0.2171	LR: 0.004000
Training Epoch: 30 [3328/9494]	Loss: 0.1578	LR: 0.004000
Training Epoch: 30 [3584/9494]	Loss: 0.1843	LR: 0.004000
Training Epoch: 30 [3840/9494]	Loss: 0.2141	LR: 0.004000
Training Epoch: 30 [4096/9494]	Loss: 0.1416	LR: 0.004000
Training Epoch: 30 [4352/9494]	Loss: 0.1644	LR: 0.004000
Training Epoch: 30 [4608/9494]	Loss: 0.2196	LR: 0.004000
Training Epoch: 30 [4864/9494]	Loss: 0.2139	LR: 0.004000
Training Epoch: 30 [5120/9494]	Loss: 0.2077	LR: 0.004000
Training Epoch: 30 [5376/9494]	Loss: 0.1762	LR: 0.004000
Training Epoch: 30 [5632/9494]	Loss: 0.1536	LR: 0.004000
Training Epoch: 30 [5888/9494]	Loss: 0.2735	LR: 0.004000
Training Epoch: 30 [6144/9494]	Loss: 0.2237	LR: 0.004000
Training Epoch: 30 [6400/9494]	Loss: 0.1380	LR: 0.004000
Training Epoch: 30 [6656/9494]	Loss: 0.1520	LR: 0.004000
Training Epoch: 30 [6912/9494]	Loss: 0.1985	LR: 0.004000
Training Epoch: 30 [7168/9494]	Loss: 0.1933	LR: 0.004000
Training Epoch: 30 [7424/9494]	Loss: 0.1739	LR: 0.004000
Training Epoch: 30 [7680/9494]	Loss: 0.1939	LR: 0.004000
Training Epoch: 30 [7936/9494]	Loss: 0.1981	LR: 0.004000
Training Epoch: 30 [8192/9494]	Loss: 0.1941	LR: 0.004000
Training Epoch: 30 [8448/9494]	Loss: 0.1281	LR: 0.004000
Training Epoch: 30 [8704/9494]	Loss: 0.1409	LR: 0.004000
Training Epoch: 30 [8960/9494]	Loss: 0.1804	LR: 0.004000
Training Epoch: 30 [9216/9494]	Loss: 0.1645	LR: 0.004000
Training Epoch: 30 [9472/9494]	Loss: 0.1207	LR: 0.004000
Training Epoch: 30 [9494/9494]	Loss: 0.3486	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1857, Train Accuracy: 0.9241
Epoch 30 training time consumed: 135.86s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0011, Accuracy: 0.8988, Time consumed:8.20s
Training Epoch: 31 [256/9494]	Loss: 0.1984	LR: 0.004000
Training Epoch: 31 [512/9494]	Loss: 0.1880	LR: 0.004000
Training Epoch: 31 [768/9494]	Loss: 0.1989	LR: 0.004000
Training Epoch: 31 [1024/9494]	Loss: 0.2314	LR: 0.004000
Training Epoch: 31 [1280/9494]	Loss: 0.1938	LR: 0.004000
Training Epoch: 31 [1536/9494]	Loss: 0.2859	LR: 0.004000
Training Epoch: 31 [1792/9494]	Loss: 0.1535	LR: 0.004000
Training Epoch: 31 [2048/9494]	Loss: 0.2387	LR: 0.004000
Training Epoch: 31 [2304/9494]	Loss: 0.1717	LR: 0.004000
Training Epoch: 31 [2560/9494]	Loss: 0.2253	LR: 0.004000
Training Epoch: 31 [2816/9494]	Loss: 0.1100	LR: 0.004000
Training Epoch: 31 [3072/9494]	Loss: 0.1936	LR: 0.004000
Training Epoch: 31 [3328/9494]	Loss: 0.1649	LR: 0.004000
Training Epoch: 31 [3584/9494]	Loss: 0.2000	LR: 0.004000
Training Epoch: 31 [3840/9494]	Loss: 0.1753	LR: 0.004000
Training Epoch: 31 [4096/9494]	Loss: 0.1692	LR: 0.004000
Training Epoch: 31 [4352/9494]	Loss: 0.1851	LR: 0.004000
Training Epoch: 31 [4608/9494]	Loss: 0.2260	LR: 0.004000
Training Epoch: 31 [4864/9494]	Loss: 0.1508	LR: 0.004000
Training Epoch: 31 [5120/9494]	Loss: 0.1787	LR: 0.004000
Training Epoch: 31 [5376/9494]	Loss: 0.3015	LR: 0.004000
Training Epoch: 31 [5632/9494]	Loss: 0.1782	LR: 0.004000
Training Epoch: 31 [5888/9494]	Loss: 0.1824	LR: 0.004000
Training Epoch: 31 [6144/9494]	Loss: 0.2192	LR: 0.004000
Training Epoch: 31 [6400/9494]	Loss: 0.1481	LR: 0.004000
Training Epoch: 31 [6656/9494]	Loss: 0.1660	LR: 0.004000
Training Epoch: 31 [6912/9494]	Loss: 0.2064	LR: 0.004000
Training Epoch: 31 [7168/9494]	Loss: 0.1605	LR: 0.004000
Training Epoch: 31 [7424/9494]	Loss: 0.1802	LR: 0.004000
Training Epoch: 31 [7680/9494]	Loss: 0.2020	LR: 0.004000
Training Epoch: 31 [7936/9494]	Loss: 0.1613	LR: 0.004000
Training Epoch: 31 [8192/9494]	Loss: 0.1921	LR: 0.004000
Training Epoch: 31 [8448/9494]	Loss: 0.2155	LR: 0.004000
Training Epoch: 31 [8704/9494]	Loss: 0.1452	LR: 0.004000
Training Epoch: 31 [8960/9494]	Loss: 0.2583	LR: 0.004000
Training Epoch: 31 [9216/9494]	Loss: 0.1742	LR: 0.004000
Training Epoch: 31 [9472/9494]	Loss: 0.1449	LR: 0.004000
Training Epoch: 31 [9494/9494]	Loss: 0.1016	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1910, Train Accuracy: 0.9209
Epoch 31 training time consumed: 135.71s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0007, Accuracy: 0.9264, Time consumed:8.02s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_16h_50m_56s/ResNet18-MUCAC-seed1-ret100-31-best.pth
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  9494
Forget Train Dl:  1054
Retain Valid Dl:  9494
Forget Valid Dl:  1054
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 1054 samples
Set1 Distribution: 1054 samples
Set2 Distribution: 1054 samples
Set1 Distribution: 1054 samples
Set2 Distribution: 1054 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 93.40277862548828
Retain Accuracy: 92.23703002929688
Zero-Retain Forget (ZRF): 0.841374933719635
Membership Inference Attack (MIA): 0.3757115749525617
Forget vs Retain Membership Inference Attack (MIA): 0.495260663507109
Forget vs Test Membership Inference Attack (MIA): 0.5734597156398105
Test vs Retain Membership Inference Attack (MIA): 0.5314769975786925
Train vs Test Membership Inference Attack (MIA): 0.5423728813559322
Forget Set Accuracy (Df): 91.984375
Method Execution Time: 22561.83 seconds
