./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
./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: 0.6986	LR: 0.000000
Training Epoch: 1 [512/9494]	Loss: 0.6853	LR: 0.002632
Training Epoch: 1 [768/9494]	Loss: 0.6963	LR: 0.005263
Training Epoch: 1 [1024/9494]	Loss: 0.6941	LR: 0.007895
Training Epoch: 1 [1280/9494]	Loss: 0.7051	LR: 0.010526
Training Epoch: 1 [1536/9494]	Loss: 0.6799	LR: 0.013158
Training Epoch: 1 [1792/9494]	Loss: 0.7281	LR: 0.015789
Training Epoch: 1 [2048/9494]	Loss: 0.6839	LR: 0.018421
Training Epoch: 1 [2304/9494]	Loss: 0.6653	LR: 0.021053
Training Epoch: 1 [2560/9494]	Loss: 0.7427	LR: 0.023684
Training Epoch: 1 [2816/9494]	Loss: 0.9418	LR: 0.026316
Training Epoch: 1 [3072/9494]	Loss: 0.8752	LR: 0.028947
Training Epoch: 1 [3328/9494]	Loss: 0.7562	LR: 0.031579
Training Epoch: 1 [3584/9494]	Loss: 0.8161	LR: 0.034211
Training Epoch: 1 [3840/9494]	Loss: 1.1704	LR: 0.036842
Training Epoch: 1 [4096/9494]	Loss: 1.7014	LR: 0.039474
Training Epoch: 1 [4352/9494]	Loss: 0.9878	LR: 0.042105
Training Epoch: 1 [4608/9494]	Loss: 0.7310	LR: 0.044737
Training Epoch: 1 [4864/9494]	Loss: 0.7451	LR: 0.047368
Training Epoch: 1 [5120/9494]	Loss: 0.6995	LR: 0.050000
Training Epoch: 1 [5376/9494]	Loss: 0.7102	LR: 0.052632
Training Epoch: 1 [5632/9494]	Loss: 0.6849	LR: 0.055263
Training Epoch: 1 [5888/9494]	Loss: 0.7269	LR: 0.057895
Training Epoch: 1 [6144/9494]	Loss: 0.8952	LR: 0.060526
Training Epoch: 1 [6400/9494]	Loss: 0.8980	LR: 0.063158
Training Epoch: 1 [6656/9494]	Loss: 0.7539	LR: 0.065789
Training Epoch: 1 [6912/9494]	Loss: 0.9824	LR: 0.068421
Training Epoch: 1 [7168/9494]	Loss: 0.7487	LR: 0.071053
Training Epoch: 1 [7424/9494]	Loss: 0.9915	LR: 0.073684
Training Epoch: 1 [7680/9494]	Loss: 1.0149	LR: 0.076316
Training Epoch: 1 [7936/9494]	Loss: 0.6951	LR: 0.078947
Training Epoch: 1 [8192/9494]	Loss: 0.8689	LR: 0.081579
Training Epoch: 1 [8448/9494]	Loss: 0.7593	LR: 0.084211
Training Epoch: 1 [8704/9494]	Loss: 0.7381	LR: 0.086842
Training Epoch: 1 [8960/9494]	Loss: 0.7827	LR: 0.089474
Training Epoch: 1 [9216/9494]	Loss: 0.7641	LR: 0.092105
Training Epoch: 1 [9472/9494]	Loss: 0.7891	LR: 0.094737
Training Epoch: 1 [9494/9494]	Loss: 0.6305	LR: 0.097368
Epoch 1 - Average Train Loss: 0.8160, Train Accuracy: 0.5218
Epoch 1 training time consumed: 8026.53s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0333, Accuracy: 0.4450, Time consumed:444.15s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-1-best.pth
Training Epoch: 2 [256/9494]	Loss: 0.7016	LR: 0.100000
Training Epoch: 2 [512/9494]	Loss: 0.7474	LR: 0.100000
Training Epoch: 2 [768/9494]	Loss: 0.7003	LR: 0.100000
Training Epoch: 2 [1024/9494]	Loss: 0.7458	LR: 0.100000
Training Epoch: 2 [1280/9494]	Loss: 0.7382	LR: 0.100000
Training Epoch: 2 [1536/9494]	Loss: 0.6829	LR: 0.100000
Training Epoch: 2 [1792/9494]	Loss: 0.7601	LR: 0.100000
Training Epoch: 2 [2048/9494]	Loss: 0.6764	LR: 0.100000
Training Epoch: 2 [2304/9494]	Loss: 0.7129	LR: 0.100000
Training Epoch: 2 [2560/9494]	Loss: 0.6846	LR: 0.100000
Training Epoch: 2 [2816/9494]	Loss: 0.7616	LR: 0.100000
Training Epoch: 2 [3072/9494]	Loss: 0.6838	LR: 0.100000
Training Epoch: 2 [3328/9494]	Loss: 0.7202	LR: 0.100000
Training Epoch: 2 [3584/9494]	Loss: 0.7692	LR: 0.100000
Training Epoch: 2 [3840/9494]	Loss: 0.6813	LR: 0.100000
Training Epoch: 2 [4096/9494]	Loss: 0.6703	LR: 0.100000
Training Epoch: 2 [4352/9494]	Loss: 0.6592	LR: 0.100000
Training Epoch: 2 [4608/9494]	Loss: 0.7531	LR: 0.100000
Training Epoch: 2 [4864/9494]	Loss: 0.6672	LR: 0.100000
Training Epoch: 2 [5120/9494]	Loss: 0.6962	LR: 0.100000
Training Epoch: 2 [5376/9494]	Loss: 0.6860	LR: 0.100000
Training Epoch: 2 [5632/9494]	Loss: 0.7224	LR: 0.100000
Training Epoch: 2 [5888/9494]	Loss: 0.6783	LR: 0.100000
Training Epoch: 2 [6144/9494]	Loss: 0.6746	LR: 0.100000
Training Epoch: 2 [6400/9494]	Loss: 0.6890	LR: 0.100000
Training Epoch: 2 [6656/9494]	Loss: 0.6903	LR: 0.100000
Training Epoch: 2 [6912/9494]	Loss: 0.6758	LR: 0.100000
Training Epoch: 2 [7168/9494]	Loss: 0.6778	LR: 0.100000
Training Epoch: 2 [7424/9494]	Loss: 0.6923	LR: 0.100000
Training Epoch: 2 [7680/9494]	Loss: 0.6730	LR: 0.100000
Training Epoch: 2 [7936/9494]	Loss: 0.6713	LR: 0.100000
Training Epoch: 2 [8192/9494]	Loss: 0.6838	LR: 0.100000
Training Epoch: 2 [8448/9494]	Loss: 0.6653	LR: 0.100000
Training Epoch: 2 [8704/9494]	Loss: 0.6965	LR: 0.100000
Training Epoch: 2 [8960/9494]	Loss: 0.7195	LR: 0.100000
Training Epoch: 2 [9216/9494]	Loss: 0.6844	LR: 0.100000
Training Epoch: 2 [9472/9494]	Loss: 0.6970	LR: 0.100000
Training Epoch: 2 [9494/9494]	Loss: 0.6483	LR: 0.100000
Epoch 2 - Average Train Loss: 0.6996, Train Accuracy: 0.5422
Epoch 2 training time consumed: 137.50s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0036, Accuracy: 0.4479, Time consumed:7.93s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-2-best.pth
Training Epoch: 3 [256/9494]	Loss: 0.7458	LR: 0.100000
Training Epoch: 3 [512/9494]	Loss: 0.6895	LR: 0.100000
Training Epoch: 3 [768/9494]	Loss: 0.6952	LR: 0.100000
Training Epoch: 3 [1024/9494]	Loss: 0.6700	LR: 0.100000
Training Epoch: 3 [1280/9494]	Loss: 0.7685	LR: 0.100000
Training Epoch: 3 [1536/9494]	Loss: 0.7421	LR: 0.100000
Training Epoch: 3 [1792/9494]	Loss: 0.6559	LR: 0.100000
Training Epoch: 3 [2048/9494]	Loss: 0.6982	LR: 0.100000
Training Epoch: 3 [2304/9494]	Loss: 0.7210	LR: 0.100000
Training Epoch: 3 [2560/9494]	Loss: 0.6859	LR: 0.100000
Training Epoch: 3 [2816/9494]	Loss: 0.6778	LR: 0.100000
Training Epoch: 3 [3072/9494]	Loss: 0.6686	LR: 0.100000
Training Epoch: 3 [3328/9494]	Loss: 0.7006	LR: 0.100000
Training Epoch: 3 [3584/9494]	Loss: 0.6620	LR: 0.100000
Training Epoch: 3 [3840/9494]	Loss: 0.6694	LR: 0.100000
Training Epoch: 3 [4096/9494]	Loss: 0.6701	LR: 0.100000
Training Epoch: 3 [4352/9494]	Loss: 0.6946	LR: 0.100000
Training Epoch: 3 [4608/9494]	Loss: 0.7253	LR: 0.100000
Training Epoch: 3 [4864/9494]	Loss: 0.6618	LR: 0.100000
Training Epoch: 3 [5120/9494]	Loss: 0.6880	LR: 0.100000
Training Epoch: 3 [5376/9494]	Loss: 0.6975	LR: 0.100000
Training Epoch: 3 [5632/9494]	Loss: 0.7121	LR: 0.100000
Training Epoch: 3 [5888/9494]	Loss: 0.6732	LR: 0.100000
Training Epoch: 3 [6144/9494]	Loss: 0.6816	LR: 0.100000
Training Epoch: 3 [6400/9494]	Loss: 0.7100	LR: 0.100000
Training Epoch: 3 [6656/9494]	Loss: 0.6749	LR: 0.100000
Training Epoch: 3 [6912/9494]	Loss: 0.6771	LR: 0.100000
Training Epoch: 3 [7168/9494]	Loss: 0.6740	LR: 0.100000
Training Epoch: 3 [7424/9494]	Loss: 0.6803	LR: 0.100000
Training Epoch: 3 [7680/9494]	Loss: 0.6748	LR: 0.100000
Training Epoch: 3 [7936/9494]	Loss: 0.6435	LR: 0.100000
Training Epoch: 3 [8192/9494]	Loss: 0.7071	LR: 0.100000
Training Epoch: 3 [8448/9494]	Loss: 0.6836	LR: 0.100000
Training Epoch: 3 [8704/9494]	Loss: 0.6662	LR: 0.100000
Training Epoch: 3 [8960/9494]	Loss: 0.6557	LR: 0.100000
Training Epoch: 3 [9216/9494]	Loss: 0.6872	LR: 0.100000
Training Epoch: 3 [9472/9494]	Loss: 0.7008	LR: 0.100000
Training Epoch: 3 [9494/9494]	Loss: 0.6553	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6888, Train Accuracy: 0.5618
Epoch 3 training time consumed: 137.31s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5540, Time consumed:8.00s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-3-best.pth
Training Epoch: 4 [256/9494]	Loss: 0.6617	LR: 0.100000
Training Epoch: 4 [512/9494]	Loss: 0.7286	LR: 0.100000
Training Epoch: 4 [768/9494]	Loss: 0.7194	LR: 0.100000
Training Epoch: 4 [1024/9494]	Loss: 0.7319	LR: 0.100000
Training Epoch: 4 [1280/9494]	Loss: 0.6736	LR: 0.100000
Training Epoch: 4 [1536/9494]	Loss: 0.6592	LR: 0.100000
Training Epoch: 4 [1792/9494]	Loss: 0.6941	LR: 0.100000
Training Epoch: 4 [2048/9494]	Loss: 0.7215	LR: 0.100000
Training Epoch: 4 [2304/9494]	Loss: 0.6925	LR: 0.100000
Training Epoch: 4 [2560/9494]	Loss: 0.6872	LR: 0.100000
Training Epoch: 4 [2816/9494]	Loss: 0.6676	LR: 0.100000
Training Epoch: 4 [3072/9494]	Loss: 0.6531	LR: 0.100000
Training Epoch: 4 [3328/9494]	Loss: 0.6631	LR: 0.100000
Training Epoch: 4 [3584/9494]	Loss: 0.6801	LR: 0.100000
Training Epoch: 4 [3840/9494]	Loss: 0.6752	LR: 0.100000
Training Epoch: 4 [4096/9494]	Loss: 0.6863	LR: 0.100000
Training Epoch: 4 [4352/9494]	Loss: 0.6697	LR: 0.100000
Training Epoch: 4 [4608/9494]	Loss: 0.6584	LR: 0.100000
Training Epoch: 4 [4864/9494]	Loss: 0.6815	LR: 0.100000
Training Epoch: 4 [5120/9494]	Loss: 0.6747	LR: 0.100000
Training Epoch: 4 [5376/9494]	Loss: 0.6778	LR: 0.100000
Training Epoch: 4 [5632/9494]	Loss: 0.6549	LR: 0.100000
Training Epoch: 4 [5888/9494]	Loss: 0.6614	LR: 0.100000
Training Epoch: 4 [6144/9494]	Loss: 0.6940	LR: 0.100000
Training Epoch: 4 [6400/9494]	Loss: 0.6943	LR: 0.100000
Training Epoch: 4 [6656/9494]	Loss: 0.6914	LR: 0.100000
Training Epoch: 4 [6912/9494]	Loss: 0.6517	LR: 0.100000
Training Epoch: 4 [7168/9494]	Loss: 0.6670	LR: 0.100000
Training Epoch: 4 [7424/9494]	Loss: 0.6856	LR: 0.100000
Training Epoch: 4 [7680/9494]	Loss: 0.7266	LR: 0.100000
Training Epoch: 4 [7936/9494]	Loss: 0.6852	LR: 0.100000
Training Epoch: 4 [8192/9494]	Loss: 0.6870	LR: 0.100000
Training Epoch: 4 [8448/9494]	Loss: 0.6682	LR: 0.100000
Training Epoch: 4 [8704/9494]	Loss: 0.6719	LR: 0.100000
Training Epoch: 4 [8960/9494]	Loss: 0.6755	LR: 0.100000
Training Epoch: 4 [9216/9494]	Loss: 0.6763	LR: 0.100000
Training Epoch: 4 [9472/9494]	Loss: 0.6688	LR: 0.100000
Training Epoch: 4 [9494/9494]	Loss: 0.7147	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6816, Train Accuracy: 0.5703
Epoch 4 training time consumed: 137.33s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0030, Accuracy: 0.5564, Time consumed:8.10s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-4-best.pth
Training Epoch: 5 [256/9494]	Loss: 0.6742	LR: 0.100000
Training Epoch: 5 [512/9494]	Loss: 0.6599	LR: 0.100000
Training Epoch: 5 [768/9494]	Loss: 0.6961	LR: 0.100000
Training Epoch: 5 [1024/9494]	Loss: 0.6806	LR: 0.100000
Training Epoch: 5 [1280/9494]	Loss: 0.6542	LR: 0.100000
Training Epoch: 5 [1536/9494]	Loss: 0.6713	LR: 0.100000
Training Epoch: 5 [1792/9494]	Loss: 0.6463	LR: 0.100000
Training Epoch: 5 [2048/9494]	Loss: 0.6630	LR: 0.100000
Training Epoch: 5 [2304/9494]	Loss: 0.6768	LR: 0.100000
Training Epoch: 5 [2560/9494]	Loss: 0.6353	LR: 0.100000
Training Epoch: 5 [2816/9494]	Loss: 0.6620	LR: 0.100000
Training Epoch: 5 [3072/9494]	Loss: 0.6931	LR: 0.100000
Training Epoch: 5 [3328/9494]	Loss: 0.6496	LR: 0.100000
Training Epoch: 5 [3584/9494]	Loss: 0.6709	LR: 0.100000
Training Epoch: 5 [3840/9494]	Loss: 0.6629	LR: 0.100000
Training Epoch: 5 [4096/9494]	Loss: 0.6702	LR: 0.100000
Training Epoch: 5 [4352/9494]	Loss: 0.6805	LR: 0.100000
Training Epoch: 5 [4608/9494]	Loss: 0.6696	LR: 0.100000
Training Epoch: 5 [4864/9494]	Loss: 0.6653	LR: 0.100000
Training Epoch: 5 [5120/9494]	Loss: 0.6669	LR: 0.100000
Training Epoch: 5 [5376/9494]	Loss: 0.6712	LR: 0.100000
Training Epoch: 5 [5632/9494]	Loss: 0.6764	LR: 0.100000
Training Epoch: 5 [5888/9494]	Loss: 0.6684	LR: 0.100000
Training Epoch: 5 [6144/9494]	Loss: 0.6724	LR: 0.100000
Training Epoch: 5 [6400/9494]	Loss: 0.7184	LR: 0.100000
Training Epoch: 5 [6656/9494]	Loss: 0.6849	LR: 0.100000
Training Epoch: 5 [6912/9494]	Loss: 0.6665	LR: 0.100000
Training Epoch: 5 [7168/9494]	Loss: 0.6781	LR: 0.100000
Training Epoch: 5 [7424/9494]	Loss: 0.6678	LR: 0.100000
Training Epoch: 5 [7680/9494]	Loss: 0.6718	LR: 0.100000
Training Epoch: 5 [7936/9494]	Loss: 0.6779	LR: 0.100000
Training Epoch: 5 [8192/9494]	Loss: 0.6715	LR: 0.100000
Training Epoch: 5 [8448/9494]	Loss: 0.6824	LR: 0.100000
Training Epoch: 5 [8704/9494]	Loss: 0.6442	LR: 0.100000
Training Epoch: 5 [8960/9494]	Loss: 0.6598	LR: 0.100000
Training Epoch: 5 [9216/9494]	Loss: 0.6595	LR: 0.100000
Training Epoch: 5 [9472/9494]	Loss: 0.6582	LR: 0.100000
Training Epoch: 5 [9494/9494]	Loss: 0.6011	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6695, Train Accuracy: 0.5880
Epoch 5 training time consumed: 137.26s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0029, Accuracy: 0.6097, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-5-best.pth
Training Epoch: 6 [256/9494]	Loss: 0.6755	LR: 0.100000
Training Epoch: 6 [512/9494]	Loss: 0.6889	LR: 0.100000
Training Epoch: 6 [768/9494]	Loss: 0.6947	LR: 0.100000
Training Epoch: 6 [1024/9494]	Loss: 0.6695	LR: 0.100000
Training Epoch: 6 [1280/9494]	Loss: 0.6631	LR: 0.100000
Training Epoch: 6 [1536/9494]	Loss: 0.6697	LR: 0.100000
Training Epoch: 6 [1792/9494]	Loss: 0.6660	LR: 0.100000
Training Epoch: 6 [2048/9494]	Loss: 0.6655	LR: 0.100000
Training Epoch: 6 [2304/9494]	Loss: 0.6633	LR: 0.100000
Training Epoch: 6 [2560/9494]	Loss: 0.6588	LR: 0.100000
Training Epoch: 6 [2816/9494]	Loss: 0.6519	LR: 0.100000
Training Epoch: 6 [3072/9494]	Loss: 0.6449	LR: 0.100000
Training Epoch: 6 [3328/9494]	Loss: 0.6560	LR: 0.100000
Training Epoch: 6 [3584/9494]	Loss: 0.6596	LR: 0.100000
Training Epoch: 6 [3840/9494]	Loss: 0.6168	LR: 0.100000
Training Epoch: 6 [4096/9494]	Loss: 0.6891	LR: 0.100000
Training Epoch: 6 [4352/9494]	Loss: 0.6388	LR: 0.100000
Training Epoch: 6 [4608/9494]	Loss: 0.6378	LR: 0.100000
Training Epoch: 6 [4864/9494]	Loss: 0.7076	LR: 0.100000
Training Epoch: 6 [5120/9494]	Loss: 0.6435	LR: 0.100000
Training Epoch: 6 [5376/9494]	Loss: 0.6303	LR: 0.100000
Training Epoch: 6 [5632/9494]	Loss: 0.6785	LR: 0.100000
Training Epoch: 6 [5888/9494]	Loss: 0.6509	LR: 0.100000
Training Epoch: 6 [6144/9494]	Loss: 0.6322	LR: 0.100000
Training Epoch: 6 [6400/9494]	Loss: 0.7052	LR: 0.100000
Training Epoch: 6 [6656/9494]	Loss: 0.6446	LR: 0.100000
Training Epoch: 6 [6912/9494]	Loss: 0.6233	LR: 0.100000
Training Epoch: 6 [7168/9494]	Loss: 0.6033	LR: 0.100000
Training Epoch: 6 [7424/9494]	Loss: 0.7015	LR: 0.100000
Training Epoch: 6 [7680/9494]	Loss: 0.6343	LR: 0.100000
Training Epoch: 6 [7936/9494]	Loss: 0.6265	LR: 0.100000
Training Epoch: 6 [8192/9494]	Loss: 0.6189	LR: 0.100000
Training Epoch: 6 [8448/9494]	Loss: 0.6506	LR: 0.100000
Training Epoch: 6 [8704/9494]	Loss: 0.6639	LR: 0.100000
Training Epoch: 6 [8960/9494]	Loss: 0.6310	LR: 0.100000
Training Epoch: 6 [9216/9494]	Loss: 0.6472	LR: 0.100000
Training Epoch: 6 [9472/9494]	Loss: 0.6557	LR: 0.100000
Training Epoch: 6 [9494/9494]	Loss: 0.5236	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6553, Train Accuracy: 0.6219
Epoch 6 training time consumed: 137.18s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0030, Accuracy: 0.6048, Time consumed:8.02s
Training Epoch: 7 [256/9494]	Loss: 0.6629	LR: 0.100000
Training Epoch: 7 [512/9494]	Loss: 0.6236	LR: 0.100000
Training Epoch: 7 [768/9494]	Loss: 0.6585	LR: 0.100000
Training Epoch: 7 [1024/9494]	Loss: 0.6497	LR: 0.100000
Training Epoch: 7 [1280/9494]	Loss: 0.6167	LR: 0.100000
Training Epoch: 7 [1536/9494]	Loss: 0.6607	LR: 0.100000
Training Epoch: 7 [1792/9494]	Loss: 0.6381	LR: 0.100000
Training Epoch: 7 [2048/9494]	Loss: 0.6347	LR: 0.100000
Training Epoch: 7 [2304/9494]	Loss: 0.6399	LR: 0.100000
Training Epoch: 7 [2560/9494]	Loss: 0.6360	LR: 0.100000
Training Epoch: 7 [2816/9494]	Loss: 0.6483	LR: 0.100000
Training Epoch: 7 [3072/9494]	Loss: 0.6513	LR: 0.100000
Training Epoch: 7 [3328/9494]	Loss: 0.5975	LR: 0.100000
Training Epoch: 7 [3584/9494]	Loss: 0.6234	LR: 0.100000
Training Epoch: 7 [3840/9494]	Loss: 0.6194	LR: 0.100000
Training Epoch: 7 [4096/9494]	Loss: 0.6035	LR: 0.100000
Training Epoch: 7 [4352/9494]	Loss: 0.6449	LR: 0.100000
Training Epoch: 7 [4608/9494]	Loss: 0.6435	LR: 0.100000
Training Epoch: 7 [4864/9494]	Loss: 0.5983	LR: 0.100000
Training Epoch: 7 [5120/9494]	Loss: 0.6496	LR: 0.100000
Training Epoch: 7 [5376/9494]	Loss: 0.6250	LR: 0.100000
Training Epoch: 7 [5632/9494]	Loss: 0.6597	LR: 0.100000
Training Epoch: 7 [5888/9494]	Loss: 0.6189	LR: 0.100000
Training Epoch: 7 [6144/9494]	Loss: 0.6038	LR: 0.100000
Training Epoch: 7 [6400/9494]	Loss: 0.6661	LR: 0.100000
Training Epoch: 7 [6656/9494]	Loss: 0.6125	LR: 0.100000
Training Epoch: 7 [6912/9494]	Loss: 0.6325	LR: 0.100000
Training Epoch: 7 [7168/9494]	Loss: 0.6048	LR: 0.100000
Training Epoch: 7 [7424/9494]	Loss: 0.6159	LR: 0.100000
Training Epoch: 7 [7680/9494]	Loss: 0.5908	LR: 0.100000
Training Epoch: 7 [7936/9494]	Loss: 0.6161	LR: 0.100000
Training Epoch: 7 [8192/9494]	Loss: 0.6440	LR: 0.100000
Training Epoch: 7 [8448/9494]	Loss: 0.6267	LR: 0.100000
Training Epoch: 7 [8704/9494]	Loss: 0.6135	LR: 0.100000
Training Epoch: 7 [8960/9494]	Loss: 0.6399	LR: 0.100000
Training Epoch: 7 [9216/9494]	Loss: 0.6313	LR: 0.100000
Training Epoch: 7 [9472/9494]	Loss: 0.5892	LR: 0.100000
Training Epoch: 7 [9494/9494]	Loss: 0.5770	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6294, Train Accuracy: 0.6479
Epoch 7 training time consumed: 137.22s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0027, Accuracy: 0.6518, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-7-best.pth
Training Epoch: 8 [256/9494]	Loss: 0.5422	LR: 0.100000
Training Epoch: 8 [512/9494]	Loss: 0.5931	LR: 0.100000
Training Epoch: 8 [768/9494]	Loss: 0.5945	LR: 0.100000
Training Epoch: 8 [1024/9494]	Loss: 0.6278	LR: 0.100000
Training Epoch: 8 [1280/9494]	Loss: 0.6372	LR: 0.100000
Training Epoch: 8 [1536/9494]	Loss: 0.5729	LR: 0.100000
Training Epoch: 8 [1792/9494]	Loss: 0.5948	LR: 0.100000
Training Epoch: 8 [2048/9494]	Loss: 0.6449	LR: 0.100000
Training Epoch: 8 [2304/9494]	Loss: 0.6251	LR: 0.100000
Training Epoch: 8 [2560/9494]	Loss: 0.5776	LR: 0.100000
Training Epoch: 8 [2816/9494]	Loss: 0.5718	LR: 0.100000
Training Epoch: 8 [3072/9494]	Loss: 0.5725	LR: 0.100000
Training Epoch: 8 [3328/9494]	Loss: 0.5886	LR: 0.100000
Training Epoch: 8 [3584/9494]	Loss: 0.6415	LR: 0.100000
Training Epoch: 8 [3840/9494]	Loss: 0.5680	LR: 0.100000
Training Epoch: 8 [4096/9494]	Loss: 0.5593	LR: 0.100000
Training Epoch: 8 [4352/9494]	Loss: 0.5563	LR: 0.100000
Training Epoch: 8 [4608/9494]	Loss: 0.6046	LR: 0.100000
Training Epoch: 8 [4864/9494]	Loss: 0.5569	LR: 0.100000
Training Epoch: 8 [5120/9494]	Loss: 0.6029	LR: 0.100000
Training Epoch: 8 [5376/9494]	Loss: 0.5814	LR: 0.100000
Training Epoch: 8 [5632/9494]	Loss: 0.5368	LR: 0.100000
Training Epoch: 8 [5888/9494]	Loss: 0.5470	LR: 0.100000
Training Epoch: 8 [6144/9494]	Loss: 0.5633	LR: 0.100000
Training Epoch: 8 [6400/9494]	Loss: 0.5656	LR: 0.100000
Training Epoch: 8 [6656/9494]	Loss: 0.5271	LR: 0.100000
Training Epoch: 8 [6912/9494]	Loss: 0.5137	LR: 0.100000
Training Epoch: 8 [7168/9494]	Loss: 0.5357	LR: 0.100000
Training Epoch: 8 [7424/9494]	Loss: 0.5625	LR: 0.100000
Training Epoch: 8 [7680/9494]	Loss: 0.5621	LR: 0.100000
Training Epoch: 8 [7936/9494]	Loss: 0.5390	LR: 0.100000
Training Epoch: 8 [8192/9494]	Loss: 0.4992	LR: 0.100000
Training Epoch: 8 [8448/9494]	Loss: 0.5541	LR: 0.100000
Training Epoch: 8 [8704/9494]	Loss: 0.5501	LR: 0.100000
Training Epoch: 8 [8960/9494]	Loss: 0.5027	LR: 0.100000
Training Epoch: 8 [9216/9494]	Loss: 0.4884	LR: 0.100000
Training Epoch: 8 [9472/9494]	Loss: 0.5486	LR: 0.100000
Training Epoch: 8 [9494/9494]	Loss: 0.4563	LR: 0.100000
Epoch 8 - Average Train Loss: 0.5676, Train Accuracy: 0.7074
Epoch 8 training time consumed: 137.76s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0036, Accuracy: 0.5617, Time consumed:8.11s
Training Epoch: 9 [256/9494]	Loss: 0.4728	LR: 0.100000
Training Epoch: 9 [512/9494]	Loss: 0.5835	LR: 0.100000
Training Epoch: 9 [768/9494]	Loss: 0.5082	LR: 0.100000
Training Epoch: 9 [1024/9494]	Loss: 0.5306	LR: 0.100000
Training Epoch: 9 [1280/9494]	Loss: 0.5102	LR: 0.100000
Training Epoch: 9 [1536/9494]	Loss: 0.5679	LR: 0.100000
Training Epoch: 9 [1792/9494]	Loss: 0.4926	LR: 0.100000
Training Epoch: 9 [2048/9494]	Loss: 0.4983	LR: 0.100000
Training Epoch: 9 [2304/9494]	Loss: 0.4541	LR: 0.100000
Training Epoch: 9 [2560/9494]	Loss: 0.4804	LR: 0.100000
Training Epoch: 9 [2816/9494]	Loss: 0.4577	LR: 0.100000
Training Epoch: 9 [3072/9494]	Loss: 0.4416	LR: 0.100000
Training Epoch: 9 [3328/9494]	Loss: 0.5200	LR: 0.100000
Training Epoch: 9 [3584/9494]	Loss: 0.5221	LR: 0.100000
Training Epoch: 9 [3840/9494]	Loss: 0.5581	LR: 0.100000
Training Epoch: 9 [4096/9494]	Loss: 0.4217	LR: 0.100000
Training Epoch: 9 [4352/9494]	Loss: 0.5088	LR: 0.100000
Training Epoch: 9 [4608/9494]	Loss: 0.4088	LR: 0.100000
Training Epoch: 9 [4864/9494]	Loss: 0.3932	LR: 0.100000
Training Epoch: 9 [5120/9494]	Loss: 0.4542	LR: 0.100000
Training Epoch: 9 [5376/9494]	Loss: 0.4896	LR: 0.100000
Training Epoch: 9 [5632/9494]	Loss: 0.4745	LR: 0.100000
Training Epoch: 9 [5888/9494]	Loss: 0.4556	LR: 0.100000
Training Epoch: 9 [6144/9494]	Loss: 0.5090	LR: 0.100000
Training Epoch: 9 [6400/9494]	Loss: 0.4242	LR: 0.100000
Training Epoch: 9 [6656/9494]	Loss: 0.4370	LR: 0.100000
Training Epoch: 9 [6912/9494]	Loss: 0.4993	LR: 0.100000
Training Epoch: 9 [7168/9494]	Loss: 0.4697	LR: 0.100000
Training Epoch: 9 [7424/9494]	Loss: 0.4901	LR: 0.100000
Training Epoch: 9 [7680/9494]	Loss: 0.5571	LR: 0.100000
Training Epoch: 9 [7936/9494]	Loss: 0.4584	LR: 0.100000
Training Epoch: 9 [8192/9494]	Loss: 0.4353	LR: 0.100000
Training Epoch: 9 [8448/9494]	Loss: 0.4089	LR: 0.100000
Training Epoch: 9 [8704/9494]	Loss: 0.4325	LR: 0.100000
Training Epoch: 9 [8960/9494]	Loss: 0.4628	LR: 0.100000
Training Epoch: 9 [9216/9494]	Loss: 0.3965	LR: 0.100000
Training Epoch: 9 [9472/9494]	Loss: 0.3537	LR: 0.100000
Training Epoch: 9 [9494/9494]	Loss: 0.5733	LR: 0.100000
Epoch 9 - Average Train Loss: 0.4742, Train Accuracy: 0.7802
Epoch 9 training time consumed: 137.20s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0028, Accuracy: 0.7366, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-9-best.pth
Training Epoch: 10 [256/9494]	Loss: 0.4483	LR: 0.020000
Training Epoch: 10 [512/9494]	Loss: 0.3647	LR: 0.020000
Training Epoch: 10 [768/9494]	Loss: 0.3716	LR: 0.020000
Training Epoch: 10 [1024/9494]	Loss: 0.3915	LR: 0.020000
Training Epoch: 10 [1280/9494]	Loss: 0.4062	LR: 0.020000
Training Epoch: 10 [1536/9494]	Loss: 0.3813	LR: 0.020000
Training Epoch: 10 [1792/9494]	Loss: 0.3313	LR: 0.020000
Training Epoch: 10 [2048/9494]	Loss: 0.3727	LR: 0.020000
Training Epoch: 10 [2304/9494]	Loss: 0.3216	LR: 0.020000
Training Epoch: 10 [2560/9494]	Loss: 0.3926	LR: 0.020000
Training Epoch: 10 [2816/9494]	Loss: 0.3060	LR: 0.020000
Training Epoch: 10 [3072/9494]	Loss: 0.3704	LR: 0.020000
Training Epoch: 10 [3328/9494]	Loss: 0.3710	LR: 0.020000
Training Epoch: 10 [3584/9494]	Loss: 0.3016	LR: 0.020000
Training Epoch: 10 [3840/9494]	Loss: 0.3334	LR: 0.020000
Training Epoch: 10 [4096/9494]	Loss: 0.3681	LR: 0.020000
Training Epoch: 10 [4352/9494]	Loss: 0.3552	LR: 0.020000
Training Epoch: 10 [4608/9494]	Loss: 0.3284	LR: 0.020000
Training Epoch: 10 [4864/9494]	Loss: 0.2560	LR: 0.020000
Training Epoch: 10 [5120/9494]	Loss: 0.3407	LR: 0.020000
Training Epoch: 10 [5376/9494]	Loss: 0.2893	LR: 0.020000
Training Epoch: 10 [5632/9494]	Loss: 0.3800	LR: 0.020000
Training Epoch: 10 [5888/9494]	Loss: 0.2983	LR: 0.020000
Training Epoch: 10 [6144/9494]	Loss: 0.3616	LR: 0.020000
Training Epoch: 10 [6400/9494]	Loss: 0.4051	LR: 0.020000
Training Epoch: 10 [6656/9494]	Loss: 0.3413	LR: 0.020000
Training Epoch: 10 [6912/9494]	Loss: 0.3304	LR: 0.020000
Training Epoch: 10 [7168/9494]	Loss: 0.3576	LR: 0.020000
Training Epoch: 10 [7424/9494]	Loss: 0.3318	LR: 0.020000
Training Epoch: 10 [7680/9494]	Loss: 0.3109	LR: 0.020000
Training Epoch: 10 [7936/9494]	Loss: 0.3427	LR: 0.020000
Training Epoch: 10 [8192/9494]	Loss: 0.3472	LR: 0.020000
Training Epoch: 10 [8448/9494]	Loss: 0.2963	LR: 0.020000
Training Epoch: 10 [8704/9494]	Loss: 0.3440	LR: 0.020000
Training Epoch: 10 [8960/9494]	Loss: 0.2957	LR: 0.020000
Training Epoch: 10 [9216/9494]	Loss: 0.2602	LR: 0.020000
Training Epoch: 10 [9472/9494]	Loss: 0.3177	LR: 0.020000
Training Epoch: 10 [9494/9494]	Loss: 0.3508	LR: 0.020000
Epoch 10 - Average Train Loss: 0.3439, Train Accuracy: 0.8497
Epoch 10 training time consumed: 137.35s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0012, Accuracy: 0.8920, Time consumed:7.78s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-10-best.pth
Training Epoch: 11 [256/9494]	Loss: 0.3364	LR: 0.020000
Training Epoch: 11 [512/9494]	Loss: 0.2847	LR: 0.020000
Training Epoch: 11 [768/9494]	Loss: 0.3002	LR: 0.020000
Training Epoch: 11 [1024/9494]	Loss: 0.2580	LR: 0.020000
Training Epoch: 11 [1280/9494]	Loss: 0.2390	LR: 0.020000
Training Epoch: 11 [1536/9494]	Loss: 0.2975	LR: 0.020000
Training Epoch: 11 [1792/9494]	Loss: 0.3260	LR: 0.020000
Training Epoch: 11 [2048/9494]	Loss: 0.3537	LR: 0.020000
Training Epoch: 11 [2304/9494]	Loss: 0.2335	LR: 0.020000
Training Epoch: 11 [2560/9494]	Loss: 0.3059	LR: 0.020000
Training Epoch: 11 [2816/9494]	Loss: 0.2630	LR: 0.020000
Training Epoch: 11 [3072/9494]	Loss: 0.2934	LR: 0.020000
Training Epoch: 11 [3328/9494]	Loss: 0.3592	LR: 0.020000
Training Epoch: 11 [3584/9494]	Loss: 0.3415	LR: 0.020000
Training Epoch: 11 [3840/9494]	Loss: 0.3206	LR: 0.020000
Training Epoch: 11 [4096/9494]	Loss: 0.3198	LR: 0.020000
Training Epoch: 11 [4352/9494]	Loss: 0.3341	LR: 0.020000
Training Epoch: 11 [4608/9494]	Loss: 0.3986	LR: 0.020000
Training Epoch: 11 [4864/9494]	Loss: 0.3559	LR: 0.020000
Training Epoch: 11 [5120/9494]	Loss: 0.3466	LR: 0.020000
Training Epoch: 11 [5376/9494]	Loss: 0.2833	LR: 0.020000
Training Epoch: 11 [5632/9494]	Loss: 0.2689	LR: 0.020000
Training Epoch: 11 [5888/9494]	Loss: 0.2849	LR: 0.020000
Training Epoch: 11 [6144/9494]	Loss: 0.2179	LR: 0.020000
Training Epoch: 11 [6400/9494]	Loss: 0.3087	LR: 0.020000
Training Epoch: 11 [6656/9494]	Loss: 0.2504	LR: 0.020000
Training Epoch: 11 [6912/9494]	Loss: 0.2942	LR: 0.020000
Training Epoch: 11 [7168/9494]	Loss: 0.3285	LR: 0.020000
Training Epoch: 11 [7424/9494]	Loss: 0.3120	LR: 0.020000
Training Epoch: 11 [7680/9494]	Loss: 0.3048	LR: 0.020000
Training Epoch: 11 [7936/9494]	Loss: 0.2704	LR: 0.020000
Training Epoch: 11 [8192/9494]	Loss: 0.2854	LR: 0.020000
Training Epoch: 11 [8448/9494]	Loss: 0.2939	LR: 0.020000
Training Epoch: 11 [8704/9494]	Loss: 0.2514	LR: 0.020000
Training Epoch: 11 [8960/9494]	Loss: 0.2859	LR: 0.020000
Training Epoch: 11 [9216/9494]	Loss: 0.2869	LR: 0.020000
Training Epoch: 11 [9472/9494]	Loss: 0.3228	LR: 0.020000
Training Epoch: 11 [9494/9494]	Loss: 0.3286	LR: 0.020000
Epoch 11 - Average Train Loss: 0.3005, Train Accuracy: 0.8790
Epoch 11 training time consumed: 136.77s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0013, Accuracy: 0.8857, Time consumed:7.96s
Training Epoch: 12 [256/9494]	Loss: 0.3292	LR: 0.020000
Training Epoch: 12 [512/9494]	Loss: 0.3697	LR: 0.020000
Training Epoch: 12 [768/9494]	Loss: 0.3289	LR: 0.020000
Training Epoch: 12 [1024/9494]	Loss: 0.2884	LR: 0.020000
Training Epoch: 12 [1280/9494]	Loss: 0.3132	LR: 0.020000
Training Epoch: 12 [1536/9494]	Loss: 0.3216	LR: 0.020000
Training Epoch: 12 [1792/9494]	Loss: 0.2458	LR: 0.020000
Training Epoch: 12 [2048/9494]	Loss: 0.3322	LR: 0.020000
Training Epoch: 12 [2304/9494]	Loss: 0.2963	LR: 0.020000
Training Epoch: 12 [2560/9494]	Loss: 0.2759	LR: 0.020000
Training Epoch: 12 [2816/9494]	Loss: 0.2311	LR: 0.020000
Training Epoch: 12 [3072/9494]	Loss: 0.2359	LR: 0.020000
Training Epoch: 12 [3328/9494]	Loss: 0.3091	LR: 0.020000
Training Epoch: 12 [3584/9494]	Loss: 0.1885	LR: 0.020000
Training Epoch: 12 [3840/9494]	Loss: 0.2909	LR: 0.020000
Training Epoch: 12 [4096/9494]	Loss: 0.2799	LR: 0.020000
Training Epoch: 12 [4352/9494]	Loss: 0.2435	LR: 0.020000
Training Epoch: 12 [4608/9494]	Loss: 0.3131	LR: 0.020000
Training Epoch: 12 [4864/9494]	Loss: 0.3228	LR: 0.020000
Training Epoch: 12 [5120/9494]	Loss: 0.2687	LR: 0.020000
Training Epoch: 12 [5376/9494]	Loss: 0.2691	LR: 0.020000
Training Epoch: 12 [5632/9494]	Loss: 0.3149	LR: 0.020000
Training Epoch: 12 [5888/9494]	Loss: 0.2202	LR: 0.020000
Training Epoch: 12 [6144/9494]	Loss: 0.2966	LR: 0.020000
Training Epoch: 12 [6400/9494]	Loss: 0.2085	LR: 0.020000
Training Epoch: 12 [6656/9494]	Loss: 0.3076	LR: 0.020000
Training Epoch: 12 [6912/9494]	Loss: 0.2606	LR: 0.020000
Training Epoch: 12 [7168/9494]	Loss: 0.2192	LR: 0.020000
Training Epoch: 12 [7424/9494]	Loss: 0.2811	LR: 0.020000
Training Epoch: 12 [7680/9494]	Loss: 0.3002	LR: 0.020000
Training Epoch: 12 [7936/9494]	Loss: 0.3232	LR: 0.020000
Training Epoch: 12 [8192/9494]	Loss: 0.2129	LR: 0.020000
Training Epoch: 12 [8448/9494]	Loss: 0.2816	LR: 0.020000
Training Epoch: 12 [8704/9494]	Loss: 0.2855	LR: 0.020000
Training Epoch: 12 [8960/9494]	Loss: 0.2317	LR: 0.020000
Training Epoch: 12 [9216/9494]	Loss: 0.2098	LR: 0.020000
Training Epoch: 12 [9472/9494]	Loss: 0.3333	LR: 0.020000
Training Epoch: 12 [9494/9494]	Loss: 0.3778	LR: 0.020000
Epoch 12 - Average Train Loss: 0.2797, Train Accuracy: 0.8856
Epoch 12 training time consumed: 136.90s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0013, Accuracy: 0.8862, Time consumed:7.84s
Training Epoch: 13 [256/9494]	Loss: 0.2590	LR: 0.020000
Training Epoch: 13 [512/9494]	Loss: 0.3004	LR: 0.020000
Training Epoch: 13 [768/9494]	Loss: 0.2740	LR: 0.020000
Training Epoch: 13 [1024/9494]	Loss: 0.2512	LR: 0.020000
Training Epoch: 13 [1280/9494]	Loss: 0.3065	LR: 0.020000
Training Epoch: 13 [1536/9494]	Loss: 0.2729	LR: 0.020000
Training Epoch: 13 [1792/9494]	Loss: 0.2739	LR: 0.020000
Training Epoch: 13 [2048/9494]	Loss: 0.2429	LR: 0.020000
Training Epoch: 13 [2304/9494]	Loss: 0.2453	LR: 0.020000
Training Epoch: 13 [2560/9494]	Loss: 0.2748	LR: 0.020000
Training Epoch: 13 [2816/9494]	Loss: 0.2964	LR: 0.020000
Training Epoch: 13 [3072/9494]	Loss: 0.2920	LR: 0.020000
Training Epoch: 13 [3328/9494]	Loss: 0.2525	LR: 0.020000
Training Epoch: 13 [3584/9494]	Loss: 0.2675	LR: 0.020000
Training Epoch: 13 [3840/9494]	Loss: 0.2460	LR: 0.020000
Training Epoch: 13 [4096/9494]	Loss: 0.2681	LR: 0.020000
Training Epoch: 13 [4352/9494]	Loss: 0.2854	LR: 0.020000
Training Epoch: 13 [4608/9494]	Loss: 0.2464	LR: 0.020000
Training Epoch: 13 [4864/9494]	Loss: 0.2592	LR: 0.020000
Training Epoch: 13 [5120/9494]	Loss: 0.3129	LR: 0.020000
Training Epoch: 13 [5376/9494]	Loss: 0.3190	LR: 0.020000
Training Epoch: 13 [5632/9494]	Loss: 0.2889	LR: 0.020000
Training Epoch: 13 [5888/9494]	Loss: 0.3464	LR: 0.020000
Training Epoch: 13 [6144/9494]	Loss: 0.2790	LR: 0.020000
Training Epoch: 13 [6400/9494]	Loss: 0.2563	LR: 0.020000
Training Epoch: 13 [6656/9494]	Loss: 0.2525	LR: 0.020000
Training Epoch: 13 [6912/9494]	Loss: 0.2627	LR: 0.020000
Training Epoch: 13 [7168/9494]	Loss: 0.2557	LR: 0.020000
Training Epoch: 13 [7424/9494]	Loss: 0.2393	LR: 0.020000
Training Epoch: 13 [7680/9494]	Loss: 0.2299	LR: 0.020000
Training Epoch: 13 [7936/9494]	Loss: 0.2154	LR: 0.020000
Training Epoch: 13 [8192/9494]	Loss: 0.3013	LR: 0.020000
Training Epoch: 13 [8448/9494]	Loss: 0.1948	LR: 0.020000
Training Epoch: 13 [8704/9494]	Loss: 0.2179	LR: 0.020000
Training Epoch: 13 [8960/9494]	Loss: 0.2797	LR: 0.020000
Training Epoch: 13 [9216/9494]	Loss: 0.2185	LR: 0.020000
Training Epoch: 13 [9472/9494]	Loss: 0.2653	LR: 0.020000
Training Epoch: 13 [9494/9494]	Loss: 0.1305	LR: 0.020000
Epoch 13 - Average Train Loss: 0.2659, Train Accuracy: 0.8913
Epoch 13 training time consumed: 137.23s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0011, Accuracy: 0.9007, Time consumed:7.82s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-13-best.pth
Training Epoch: 14 [256/9494]	Loss: 0.2665	LR: 0.020000
Training Epoch: 14 [512/9494]	Loss: 0.3185	LR: 0.020000
Training Epoch: 14 [768/9494]	Loss: 0.3013	LR: 0.020000
Training Epoch: 14 [1024/9494]	Loss: 0.2246	LR: 0.020000
Training Epoch: 14 [1280/9494]	Loss: 0.2254	LR: 0.020000
Training Epoch: 14 [1536/9494]	Loss: 0.2232	LR: 0.020000
Training Epoch: 14 [1792/9494]	Loss: 0.2099	LR: 0.020000
Training Epoch: 14 [2048/9494]	Loss: 0.3372	LR: 0.020000
Training Epoch: 14 [2304/9494]	Loss: 0.1985	LR: 0.020000
Training Epoch: 14 [2560/9494]	Loss: 0.2288	LR: 0.020000
Training Epoch: 14 [2816/9494]	Loss: 0.2605	LR: 0.020000
Training Epoch: 14 [3072/9494]	Loss: 0.2804	LR: 0.020000
Training Epoch: 14 [3328/9494]	Loss: 0.1987	LR: 0.020000
Training Epoch: 14 [3584/9494]	Loss: 0.2748	LR: 0.020000
Training Epoch: 14 [3840/9494]	Loss: 0.2409	LR: 0.020000
Training Epoch: 14 [4096/9494]	Loss: 0.2597	LR: 0.020000
Training Epoch: 14 [4352/9494]	Loss: 0.2295	LR: 0.020000
Training Epoch: 14 [4608/9494]	Loss: 0.2628	LR: 0.020000
Training Epoch: 14 [4864/9494]	Loss: 0.2283	LR: 0.020000
Training Epoch: 14 [5120/9494]	Loss: 0.2652	LR: 0.020000
Training Epoch: 14 [5376/9494]	Loss: 0.2275	LR: 0.020000
Training Epoch: 14 [5632/9494]	Loss: 0.2659	LR: 0.020000
Training Epoch: 14 [5888/9494]	Loss: 0.2317	LR: 0.020000
Training Epoch: 14 [6144/9494]	Loss: 0.2840	LR: 0.020000
Training Epoch: 14 [6400/9494]	Loss: 0.2082	LR: 0.020000
Training Epoch: 14 [6656/9494]	Loss: 0.1968	LR: 0.020000
Training Epoch: 14 [6912/9494]	Loss: 0.2337	LR: 0.020000
Training Epoch: 14 [7168/9494]	Loss: 0.1942	LR: 0.020000
Training Epoch: 14 [7424/9494]	Loss: 0.1666	LR: 0.020000
Training Epoch: 14 [7680/9494]	Loss: 0.2381	LR: 0.020000
Training Epoch: 14 [7936/9494]	Loss: 0.1778	LR: 0.020000
Training Epoch: 14 [8192/9494]	Loss: 0.2101	LR: 0.020000
Training Epoch: 14 [8448/9494]	Loss: 0.2189	LR: 0.020000
Training Epoch: 14 [8704/9494]	Loss: 0.2309	LR: 0.020000
Training Epoch: 14 [8960/9494]	Loss: 0.2347	LR: 0.020000
Training Epoch: 14 [9216/9494]	Loss: 0.2487	LR: 0.020000
Training Epoch: 14 [9472/9494]	Loss: 0.1970	LR: 0.020000
Training Epoch: 14 [9494/9494]	Loss: 0.0710	LR: 0.020000
Epoch 14 - Average Train Loss: 0.2374, Train Accuracy: 0.9030
Epoch 14 training time consumed: 138.44s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0011, Accuracy: 0.8930, Time consumed:8.06s
Training Epoch: 15 [256/9494]	Loss: 0.2119	LR: 0.020000
Training Epoch: 15 [512/9494]	Loss: 0.1899	LR: 0.020000
Training Epoch: 15 [768/9494]	Loss: 0.2706	LR: 0.020000
Training Epoch: 15 [1024/9494]	Loss: 0.2035	LR: 0.020000
Training Epoch: 15 [1280/9494]	Loss: 0.1842	LR: 0.020000
Training Epoch: 15 [1536/9494]	Loss: 0.2224	LR: 0.020000
Training Epoch: 15 [1792/9494]	Loss: 0.1472	LR: 0.020000
Training Epoch: 15 [2048/9494]	Loss: 0.2778	LR: 0.020000
Training Epoch: 15 [2304/9494]	Loss: 0.1602	LR: 0.020000
Training Epoch: 15 [2560/9494]	Loss: 0.2163	LR: 0.020000
Training Epoch: 15 [2816/9494]	Loss: 0.2737	LR: 0.020000
Training Epoch: 15 [3072/9494]	Loss: 0.2920	LR: 0.020000
Training Epoch: 15 [3328/9494]	Loss: 0.2017	LR: 0.020000
Training Epoch: 15 [3584/9494]	Loss: 0.2125	LR: 0.020000
Training Epoch: 15 [3840/9494]	Loss: 0.2092	LR: 0.020000
Training Epoch: 15 [4096/9494]	Loss: 0.2347	LR: 0.020000
Training Epoch: 15 [4352/9494]	Loss: 0.2157	LR: 0.020000
Training Epoch: 15 [4608/9494]	Loss: 0.2214	LR: 0.020000
Training Epoch: 15 [4864/9494]	Loss: 0.2841	LR: 0.020000
Training Epoch: 15 [5120/9494]	Loss: 0.2588	LR: 0.020000
Training Epoch: 15 [5376/9494]	Loss: 0.2218	LR: 0.020000
Training Epoch: 15 [5632/9494]	Loss: 0.2601	LR: 0.020000
Training Epoch: 15 [5888/9494]	Loss: 0.2110	LR: 0.020000
Training Epoch: 15 [6144/9494]	Loss: 0.2283	LR: 0.020000
Training Epoch: 15 [6400/9494]	Loss: 0.1522	LR: 0.020000
Training Epoch: 15 [6656/9494]	Loss: 0.2125	LR: 0.020000
Training Epoch: 15 [6912/9494]	Loss: 0.1775	LR: 0.020000
Training Epoch: 15 [7168/9494]	Loss: 0.2088	LR: 0.020000
Training Epoch: 15 [7424/9494]	Loss: 0.1737	LR: 0.020000
Training Epoch: 15 [7680/9494]	Loss: 0.2761	LR: 0.020000
Training Epoch: 15 [7936/9494]	Loss: 0.2341	LR: 0.020000
Training Epoch: 15 [8192/9494]	Loss: 0.2380	LR: 0.020000
Training Epoch: 15 [8448/9494]	Loss: 0.2417	LR: 0.020000
Training Epoch: 15 [8704/9494]	Loss: 0.2157	LR: 0.020000
Training Epoch: 15 [8960/9494]	Loss: 0.2667	LR: 0.020000
Training Epoch: 15 [9216/9494]	Loss: 0.2036	LR: 0.020000
Training Epoch: 15 [9472/9494]	Loss: 0.2009	LR: 0.020000
Training Epoch: 15 [9494/9494]	Loss: 0.0772	LR: 0.020000
Epoch 15 - Average Train Loss: 0.2216, Train Accuracy: 0.9086
Epoch 15 training time consumed: 137.05s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0009, Accuracy: 0.9172, Time consumed:7.79s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-15-best.pth
Training Epoch: 16 [256/9494]	Loss: 0.1850	LR: 0.020000
Training Epoch: 16 [512/9494]	Loss: 0.2026	LR: 0.020000
Training Epoch: 16 [768/9494]	Loss: 0.1793	LR: 0.020000
Training Epoch: 16 [1024/9494]	Loss: 0.2844	LR: 0.020000
Training Epoch: 16 [1280/9494]	Loss: 0.1295	LR: 0.020000
Training Epoch: 16 [1536/9494]	Loss: 0.2253	LR: 0.020000
Training Epoch: 16 [1792/9494]	Loss: 0.1780	LR: 0.020000
Training Epoch: 16 [2048/9494]	Loss: 0.2006	LR: 0.020000
Training Epoch: 16 [2304/9494]	Loss: 0.1790	LR: 0.020000
Training Epoch: 16 [2560/9494]	Loss: 0.2224	LR: 0.020000
Training Epoch: 16 [2816/9494]	Loss: 0.2626	LR: 0.020000
Training Epoch: 16 [3072/9494]	Loss: 0.2118	LR: 0.020000
Training Epoch: 16 [3328/9494]	Loss: 0.2290	LR: 0.020000
Training Epoch: 16 [3584/9494]	Loss: 0.2316	LR: 0.020000
Training Epoch: 16 [3840/9494]	Loss: 0.2110	LR: 0.020000
Training Epoch: 16 [4096/9494]	Loss: 0.1404	LR: 0.020000
Training Epoch: 16 [4352/9494]	Loss: 0.1757	LR: 0.020000
Training Epoch: 16 [4608/9494]	Loss: 0.2309	LR: 0.020000
Training Epoch: 16 [4864/9494]	Loss: 0.1713	LR: 0.020000
Training Epoch: 16 [5120/9494]	Loss: 0.2049	LR: 0.020000
Training Epoch: 16 [5376/9494]	Loss: 0.2097	LR: 0.020000
Training Epoch: 16 [5632/9494]	Loss: 0.2401	LR: 0.020000
Training Epoch: 16 [5888/9494]	Loss: 0.2373	LR: 0.020000
Training Epoch: 16 [6144/9494]	Loss: 0.2756	LR: 0.020000
Training Epoch: 16 [6400/9494]	Loss: 0.1705	LR: 0.020000
Training Epoch: 16 [6656/9494]	Loss: 0.1787	LR: 0.020000
Training Epoch: 16 [6912/9494]	Loss: 0.2038	LR: 0.020000
Training Epoch: 16 [7168/9494]	Loss: 0.1805	LR: 0.020000
Training Epoch: 16 [7424/9494]	Loss: 0.2035	LR: 0.020000
Training Epoch: 16 [7680/9494]	Loss: 0.2505	LR: 0.020000
Training Epoch: 16 [7936/9494]	Loss: 0.2647	LR: 0.020000
Training Epoch: 16 [8192/9494]	Loss: 0.1630	LR: 0.020000
Training Epoch: 16 [8448/9494]	Loss: 0.2176	LR: 0.020000
Training Epoch: 16 [8704/9494]	Loss: 0.1680	LR: 0.020000
Training Epoch: 16 [8960/9494]	Loss: 0.2007	LR: 0.020000
Training Epoch: 16 [9216/9494]	Loss: 0.1618	LR: 0.020000
Training Epoch: 16 [9472/9494]	Loss: 0.2256	LR: 0.020000
Training Epoch: 16 [9494/9494]	Loss: 0.7118	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2068, Train Accuracy: 0.9170
Epoch 16 training time consumed: 137.21s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0017, Accuracy: 0.8634, Time consumed:7.73s
Training Epoch: 17 [256/9494]	Loss: 0.2259	LR: 0.020000
Training Epoch: 17 [512/9494]	Loss: 0.2625	LR: 0.020000
Training Epoch: 17 [768/9494]	Loss: 0.2402	LR: 0.020000
Training Epoch: 17 [1024/9494]	Loss: 0.2765	LR: 0.020000
Training Epoch: 17 [1280/9494]	Loss: 0.2829	LR: 0.020000
Training Epoch: 17 [1536/9494]	Loss: 0.3399	LR: 0.020000
Training Epoch: 17 [1792/9494]	Loss: 0.2637	LR: 0.020000
Training Epoch: 17 [2048/9494]	Loss: 0.2408	LR: 0.020000
Training Epoch: 17 [2304/9494]	Loss: 0.2627	LR: 0.020000
Training Epoch: 17 [2560/9494]	Loss: 0.3132	LR: 0.020000
Training Epoch: 17 [2816/9494]	Loss: 0.2515	LR: 0.020000
Training Epoch: 17 [3072/9494]	Loss: 0.2236	LR: 0.020000
Training Epoch: 17 [3328/9494]	Loss: 0.2735	LR: 0.020000
Training Epoch: 17 [3584/9494]	Loss: 0.2710	LR: 0.020000
Training Epoch: 17 [3840/9494]	Loss: 0.3246	LR: 0.020000
Training Epoch: 17 [4096/9494]	Loss: 0.2594	LR: 0.020000
Training Epoch: 17 [4352/9494]	Loss: 0.2664	LR: 0.020000
Training Epoch: 17 [4608/9494]	Loss: 0.2447	LR: 0.020000
Training Epoch: 17 [4864/9494]	Loss: 0.2075	LR: 0.020000
Training Epoch: 17 [5120/9494]	Loss: 0.2808	LR: 0.020000
Training Epoch: 17 [5376/9494]	Loss: 0.2175	LR: 0.020000
Training Epoch: 17 [5632/9494]	Loss: 0.1961	LR: 0.020000
Training Epoch: 17 [5888/9494]	Loss: 0.1804	LR: 0.020000
Training Epoch: 17 [6144/9494]	Loss: 0.2156	LR: 0.020000
Training Epoch: 17 [6400/9494]	Loss: 0.1618	LR: 0.020000
Training Epoch: 17 [6656/9494]	Loss: 0.1910	LR: 0.020000
Training Epoch: 17 [6912/9494]	Loss: 0.2122	LR: 0.020000
Training Epoch: 17 [7168/9494]	Loss: 0.1487	LR: 0.020000
Training Epoch: 17 [7424/9494]	Loss: 0.1366	LR: 0.020000
Training Epoch: 17 [7680/9494]	Loss: 0.1876	LR: 0.020000
Training Epoch: 17 [7936/9494]	Loss: 0.2360	LR: 0.020000
Training Epoch: 17 [8192/9494]	Loss: 0.1999	LR: 0.020000
Training Epoch: 17 [8448/9494]	Loss: 0.2159	LR: 0.020000
Training Epoch: 17 [8704/9494]	Loss: 0.2381	LR: 0.020000
Training Epoch: 17 [8960/9494]	Loss: 0.1683	LR: 0.020000
Training Epoch: 17 [9216/9494]	Loss: 0.2090	LR: 0.020000
Training Epoch: 17 [9472/9494]	Loss: 0.1667	LR: 0.020000
Training Epoch: 17 [9494/9494]	Loss: 0.1541	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2321, Train Accuracy: 0.9040
Epoch 17 training time consumed: 138.64s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0009, Accuracy: 0.9245, Time consumed:8.03s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-17-best.pth
Training Epoch: 18 [256/9494]	Loss: 0.1571	LR: 0.020000
Training Epoch: 18 [512/9494]	Loss: 0.2083	LR: 0.020000
Training Epoch: 18 [768/9494]	Loss: 0.1697	LR: 0.020000
Training Epoch: 18 [1024/9494]	Loss: 0.1865	LR: 0.020000
Training Epoch: 18 [1280/9494]	Loss: 0.2286	LR: 0.020000
Training Epoch: 18 [1536/9494]	Loss: 0.1860	LR: 0.020000
Training Epoch: 18 [1792/9494]	Loss: 0.2121	LR: 0.020000
Training Epoch: 18 [2048/9494]	Loss: 0.2098	LR: 0.020000
Training Epoch: 18 [2304/9494]	Loss: 0.2248	LR: 0.020000
Training Epoch: 18 [2560/9494]	Loss: 0.2146	LR: 0.020000
Training Epoch: 18 [2816/9494]	Loss: 0.1780	LR: 0.020000
Training Epoch: 18 [3072/9494]	Loss: 0.2290	LR: 0.020000
Training Epoch: 18 [3328/9494]	Loss: 0.2086	LR: 0.020000
Training Epoch: 18 [3584/9494]	Loss: 0.1889	LR: 0.020000
Training Epoch: 18 [3840/9494]	Loss: 0.2401	LR: 0.020000
Training Epoch: 18 [4096/9494]	Loss: 0.2076	LR: 0.020000
Training Epoch: 18 [4352/9494]	Loss: 0.1794	LR: 0.020000
Training Epoch: 18 [4608/9494]	Loss: 0.1574	LR: 0.020000
Training Epoch: 18 [4864/9494]	Loss: 0.2128	LR: 0.020000
Training Epoch: 18 [5120/9494]	Loss: 0.1880	LR: 0.020000
Training Epoch: 18 [5376/9494]	Loss: 0.1729	LR: 0.020000
Training Epoch: 18 [5632/9494]	Loss: 0.2542	LR: 0.020000
Training Epoch: 18 [5888/9494]	Loss: 0.2540	LR: 0.020000
Training Epoch: 18 [6144/9494]	Loss: 0.1539	LR: 0.020000
Training Epoch: 18 [6400/9494]	Loss: 0.2326	LR: 0.020000
Training Epoch: 18 [6656/9494]	Loss: 0.2258	LR: 0.020000
Training Epoch: 18 [6912/9494]	Loss: 0.2179	LR: 0.020000
Training Epoch: 18 [7168/9494]	Loss: 0.1925	LR: 0.020000
Training Epoch: 18 [7424/9494]	Loss: 0.1868	LR: 0.020000
Training Epoch: 18 [7680/9494]	Loss: 0.1838	LR: 0.020000
Training Epoch: 18 [7936/9494]	Loss: 0.1630	LR: 0.020000
Training Epoch: 18 [8192/9494]	Loss: 0.1779	LR: 0.020000
Training Epoch: 18 [8448/9494]	Loss: 0.1432	LR: 0.020000
Training Epoch: 18 [8704/9494]	Loss: 0.1986	LR: 0.020000
Training Epoch: 18 [8960/9494]	Loss: 0.2177	LR: 0.020000
Training Epoch: 18 [9216/9494]	Loss: 0.2034	LR: 0.020000
Training Epoch: 18 [9472/9494]	Loss: 0.1898	LR: 0.020000
Training Epoch: 18 [9494/9494]	Loss: 0.1086	LR: 0.020000
Epoch 18 - Average Train Loss: 0.1986, Train Accuracy: 0.9178
Epoch 18 training time consumed: 137.79s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0009, Accuracy: 0.9138, Time consumed:7.92s
Training Epoch: 19 [256/9494]	Loss: 0.2280	LR: 0.020000
Training Epoch: 19 [512/9494]	Loss: 0.1418	LR: 0.020000
Training Epoch: 19 [768/9494]	Loss: 0.1792	LR: 0.020000
Training Epoch: 19 [1024/9494]	Loss: 0.1819	LR: 0.020000
Training Epoch: 19 [1280/9494]	Loss: 0.1657	LR: 0.020000
Training Epoch: 19 [1536/9494]	Loss: 0.1868	LR: 0.020000
Training Epoch: 19 [1792/9494]	Loss: 0.1528	LR: 0.020000
Training Epoch: 19 [2048/9494]	Loss: 0.2150	LR: 0.020000
Training Epoch: 19 [2304/9494]	Loss: 0.1781	LR: 0.020000
Training Epoch: 19 [2560/9494]	Loss: 0.1779	LR: 0.020000
Training Epoch: 19 [2816/9494]	Loss: 0.1807	LR: 0.020000
Training Epoch: 19 [3072/9494]	Loss: 0.2153	LR: 0.020000
Training Epoch: 19 [3328/9494]	Loss: 0.1560	LR: 0.020000
Training Epoch: 19 [3584/9494]	Loss: 0.1929	LR: 0.020000
Training Epoch: 19 [3840/9494]	Loss: 0.2331	LR: 0.020000
Training Epoch: 19 [4096/9494]	Loss: 0.1887	LR: 0.020000
Training Epoch: 19 [4352/9494]	Loss: 0.1799	LR: 0.020000
Training Epoch: 19 [4608/9494]	Loss: 0.1881	LR: 0.020000
Training Epoch: 19 [4864/9494]	Loss: 0.1949	LR: 0.020000
Training Epoch: 19 [5120/9494]	Loss: 0.2263	LR: 0.020000
Training Epoch: 19 [5376/9494]	Loss: 0.1117	LR: 0.020000
Training Epoch: 19 [5632/9494]	Loss: 0.1780	LR: 0.020000
Training Epoch: 19 [5888/9494]	Loss: 0.1568	LR: 0.020000
Training Epoch: 19 [6144/9494]	Loss: 0.1910	LR: 0.020000
Training Epoch: 19 [6400/9494]	Loss: 0.1340	LR: 0.020000
Training Epoch: 19 [6656/9494]	Loss: 0.2321	LR: 0.020000
Training Epoch: 19 [6912/9494]	Loss: 0.1878	LR: 0.020000
Training Epoch: 19 [7168/9494]	Loss: 0.1715	LR: 0.020000
Training Epoch: 19 [7424/9494]	Loss: 0.1520	LR: 0.020000
Training Epoch: 19 [7680/9494]	Loss: 0.1696	LR: 0.020000
Training Epoch: 19 [7936/9494]	Loss: 0.1595	LR: 0.020000
Training Epoch: 19 [8192/9494]	Loss: 0.1711	LR: 0.020000
Training Epoch: 19 [8448/9494]	Loss: 0.1600	LR: 0.020000
Training Epoch: 19 [8704/9494]	Loss: 0.2173	LR: 0.020000
Training Epoch: 19 [8960/9494]	Loss: 0.1998	LR: 0.020000
Training Epoch: 19 [9216/9494]	Loss: 0.1737	LR: 0.020000
Training Epoch: 19 [9472/9494]	Loss: 0.1753	LR: 0.020000
Training Epoch: 19 [9494/9494]	Loss: 0.3198	LR: 0.020000
Epoch 19 - Average Train Loss: 0.1815, Train Accuracy: 0.9252
Epoch 19 training time consumed: 138.33s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0012, Accuracy: 0.8804, Time consumed:7.92s
Training Epoch: 20 [256/9494]	Loss: 0.2088	LR: 0.004000
Training Epoch: 20 [512/9494]	Loss: 0.1597	LR: 0.004000
Training Epoch: 20 [768/9494]	Loss: 0.1668	LR: 0.004000
Training Epoch: 20 [1024/9494]	Loss: 0.1918	LR: 0.004000
Training Epoch: 20 [1280/9494]	Loss: 0.2296	LR: 0.004000
Training Epoch: 20 [1536/9494]	Loss: 0.2107	LR: 0.004000
Training Epoch: 20 [1792/9494]	Loss: 0.2037	LR: 0.004000
Training Epoch: 20 [2048/9494]	Loss: 0.1721	LR: 0.004000
Training Epoch: 20 [2304/9494]	Loss: 0.1917	LR: 0.004000
Training Epoch: 20 [2560/9494]	Loss: 0.1948	LR: 0.004000
Training Epoch: 20 [2816/9494]	Loss: 0.1934	LR: 0.004000
Training Epoch: 20 [3072/9494]	Loss: 0.1491	LR: 0.004000
Training Epoch: 20 [3328/9494]	Loss: 0.1646	LR: 0.004000
Training Epoch: 20 [3584/9494]	Loss: 0.1900	LR: 0.004000
Training Epoch: 20 [3840/9494]	Loss: 0.1663	LR: 0.004000
Training Epoch: 20 [4096/9494]	Loss: 0.1985	LR: 0.004000
Training Epoch: 20 [4352/9494]	Loss: 0.1535	LR: 0.004000
Training Epoch: 20 [4608/9494]	Loss: 0.1935	LR: 0.004000
Training Epoch: 20 [4864/9494]	Loss: 0.1270	LR: 0.004000
Training Epoch: 20 [5120/9494]	Loss: 0.1884	LR: 0.004000
Training Epoch: 20 [5376/9494]	Loss: 0.2459	LR: 0.004000
Training Epoch: 20 [5632/9494]	Loss: 0.1171	LR: 0.004000
Training Epoch: 20 [5888/9494]	Loss: 0.1582	LR: 0.004000
Training Epoch: 20 [6144/9494]	Loss: 0.1646	LR: 0.004000
Training Epoch: 20 [6400/9494]	Loss: 0.1963	LR: 0.004000
Training Epoch: 20 [6656/9494]	Loss: 0.1405	LR: 0.004000
Training Epoch: 20 [6912/9494]	Loss: 0.1322	LR: 0.004000
Training Epoch: 20 [7168/9494]	Loss: 0.1531	LR: 0.004000
Training Epoch: 20 [7424/9494]	Loss: 0.1385	LR: 0.004000
Training Epoch: 20 [7680/9494]	Loss: 0.1701	LR: 0.004000
Training Epoch: 20 [7936/9494]	Loss: 0.1826	LR: 0.004000
Training Epoch: 20 [8192/9494]	Loss: 0.1658	LR: 0.004000
Training Epoch: 20 [8448/9494]	Loss: 0.1358	LR: 0.004000
Training Epoch: 20 [8704/9494]	Loss: 0.1398	LR: 0.004000
Training Epoch: 20 [8960/9494]	Loss: 0.1929	LR: 0.004000
Training Epoch: 20 [9216/9494]	Loss: 0.1016	LR: 0.004000
Training Epoch: 20 [9472/9494]	Loss: 0.1386	LR: 0.004000
Training Epoch: 20 [9494/9494]	Loss: 0.4855	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1717, Train Accuracy: 0.9299
Epoch 20 training time consumed: 137.72s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0007, Accuracy: 0.9346, Time consumed:7.83s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-20-best.pth
Training Epoch: 21 [256/9494]	Loss: 0.1780	LR: 0.004000
Training Epoch: 21 [512/9494]	Loss: 0.1629	LR: 0.004000
Training Epoch: 21 [768/9494]	Loss: 0.1930	LR: 0.004000
Training Epoch: 21 [1024/9494]	Loss: 0.1828	LR: 0.004000
Training Epoch: 21 [1280/9494]	Loss: 0.1437	LR: 0.004000
Training Epoch: 21 [1536/9494]	Loss: 0.1765	LR: 0.004000
Training Epoch: 21 [1792/9494]	Loss: 0.1559	LR: 0.004000
Training Epoch: 21 [2048/9494]	Loss: 0.1514	LR: 0.004000
Training Epoch: 21 [2304/9494]	Loss: 0.1594	LR: 0.004000
Training Epoch: 21 [2560/9494]	Loss: 0.1012	LR: 0.004000
Training Epoch: 21 [2816/9494]	Loss: 0.1076	LR: 0.004000
Training Epoch: 21 [3072/9494]	Loss: 0.1837	LR: 0.004000
Training Epoch: 21 [3328/9494]	Loss: 0.1189	LR: 0.004000
Training Epoch: 21 [3584/9494]	Loss: 0.1643	LR: 0.004000
Training Epoch: 21 [3840/9494]	Loss: 0.1892	LR: 0.004000
Training Epoch: 21 [4096/9494]	Loss: 0.1697	LR: 0.004000
Training Epoch: 21 [4352/9494]	Loss: 0.1545	LR: 0.004000
Training Epoch: 21 [4608/9494]	Loss: 0.1313	LR: 0.004000
Training Epoch: 21 [4864/9494]	Loss: 0.1916	LR: 0.004000
Training Epoch: 21 [5120/9494]	Loss: 0.1527	LR: 0.004000
Training Epoch: 21 [5376/9494]	Loss: 0.1620	LR: 0.004000
Training Epoch: 21 [5632/9494]	Loss: 0.1685	LR: 0.004000
Training Epoch: 21 [5888/9494]	Loss: 0.1457	LR: 0.004000
Training Epoch: 21 [6144/9494]	Loss: 0.1554	LR: 0.004000
Training Epoch: 21 [6400/9494]	Loss: 0.2026	LR: 0.004000
Training Epoch: 21 [6656/9494]	Loss: 0.1784	LR: 0.004000
Training Epoch: 21 [6912/9494]	Loss: 0.1653	LR: 0.004000
Training Epoch: 21 [7168/9494]	Loss: 0.1586	LR: 0.004000
Training Epoch: 21 [7424/9494]	Loss: 0.1281	LR: 0.004000
Training Epoch: 21 [7680/9494]	Loss: 0.1813	LR: 0.004000
Training Epoch: 21 [7936/9494]	Loss: 0.1409	LR: 0.004000
Training Epoch: 21 [8192/9494]	Loss: 0.2205	LR: 0.004000
Training Epoch: 21 [8448/9494]	Loss: 0.1152	LR: 0.004000
Training Epoch: 21 [8704/9494]	Loss: 0.1252	LR: 0.004000
Training Epoch: 21 [8960/9494]	Loss: 0.1403	LR: 0.004000
Training Epoch: 21 [9216/9494]	Loss: 0.1566	LR: 0.004000
Training Epoch: 21 [9472/9494]	Loss: 0.1450	LR: 0.004000
Training Epoch: 21 [9494/9494]	Loss: 0.0644	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1581, Train Accuracy: 0.9347
Epoch 21 training time consumed: 138.06s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0006, Accuracy: 0.9395, Time consumed:7.88s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-21-best.pth
Training Epoch: 22 [256/9494]	Loss: 0.0925	LR: 0.004000
Training Epoch: 22 [512/9494]	Loss: 0.1060	LR: 0.004000
Training Epoch: 22 [768/9494]	Loss: 0.1058	LR: 0.004000
Training Epoch: 22 [1024/9494]	Loss: 0.1752	LR: 0.004000
Training Epoch: 22 [1280/9494]	Loss: 0.1549	LR: 0.004000
Training Epoch: 22 [1536/9494]	Loss: 0.1454	LR: 0.004000
Training Epoch: 22 [1792/9494]	Loss: 0.1571	LR: 0.004000
Training Epoch: 22 [2048/9494]	Loss: 0.1013	LR: 0.004000
Training Epoch: 22 [2304/9494]	Loss: 0.1252	LR: 0.004000
Training Epoch: 22 [2560/9494]	Loss: 0.1362	LR: 0.004000
Training Epoch: 22 [2816/9494]	Loss: 0.1606	LR: 0.004000
Training Epoch: 22 [3072/9494]	Loss: 0.2073	LR: 0.004000
Training Epoch: 22 [3328/9494]	Loss: 0.1325	LR: 0.004000
Training Epoch: 22 [3584/9494]	Loss: 0.1056	LR: 0.004000
Training Epoch: 22 [3840/9494]	Loss: 0.2172	LR: 0.004000
Training Epoch: 22 [4096/9494]	Loss: 0.1114	LR: 0.004000
Training Epoch: 22 [4352/9494]	Loss: 0.1735	LR: 0.004000
Training Epoch: 22 [4608/9494]	Loss: 0.1799	LR: 0.004000
Training Epoch: 22 [4864/9494]	Loss: 0.1551	LR: 0.004000
Training Epoch: 22 [5120/9494]	Loss: 0.1344	LR: 0.004000
Training Epoch: 22 [5376/9494]	Loss: 0.1818	LR: 0.004000
Training Epoch: 22 [5632/9494]	Loss: 0.1542	LR: 0.004000
Training Epoch: 22 [5888/9494]	Loss: 0.1645	LR: 0.004000
Training Epoch: 22 [6144/9494]	Loss: 0.1566	LR: 0.004000
Training Epoch: 22 [6400/9494]	Loss: 0.1542	LR: 0.004000
Training Epoch: 22 [6656/9494]	Loss: 0.1297	LR: 0.004000
Training Epoch: 22 [6912/9494]	Loss: 0.1365	LR: 0.004000
Training Epoch: 22 [7168/9494]	Loss: 0.1571	LR: 0.004000
Training Epoch: 22 [7424/9494]	Loss: 0.1459	LR: 0.004000
Training Epoch: 22 [7680/9494]	Loss: 0.1709	LR: 0.004000
Training Epoch: 22 [7936/9494]	Loss: 0.2333	LR: 0.004000
Training Epoch: 22 [8192/9494]	Loss: 0.1579	LR: 0.004000
Training Epoch: 22 [8448/9494]	Loss: 0.1686	LR: 0.004000
Training Epoch: 22 [8704/9494]	Loss: 0.1471	LR: 0.004000
Training Epoch: 22 [8960/9494]	Loss: 0.1159	LR: 0.004000
Training Epoch: 22 [9216/9494]	Loss: 0.1118	LR: 0.004000
Training Epoch: 22 [9472/9494]	Loss: 0.1453	LR: 0.004000
Training Epoch: 22 [9494/9494]	Loss: 0.1015	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1488, Train Accuracy: 0.9391
Epoch 22 training time consumed: 137.34s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0008, Accuracy: 0.9298, Time consumed:7.76s
Training Epoch: 23 [256/9494]	Loss: 0.1909	LR: 0.004000
Training Epoch: 23 [512/9494]	Loss: 0.1854	LR: 0.004000
Training Epoch: 23 [768/9494]	Loss: 0.1414	LR: 0.004000
Training Epoch: 23 [1024/9494]	Loss: 0.1610	LR: 0.004000
Training Epoch: 23 [1280/9494]	Loss: 0.1433	LR: 0.004000
Training Epoch: 23 [1536/9494]	Loss: 0.1564	LR: 0.004000
Training Epoch: 23 [1792/9494]	Loss: 0.1309	LR: 0.004000
Training Epoch: 23 [2048/9494]	Loss: 0.1409	LR: 0.004000
Training Epoch: 23 [2304/9494]	Loss: 0.1507	LR: 0.004000
Training Epoch: 23 [2560/9494]	Loss: 0.1094	LR: 0.004000
Training Epoch: 23 [2816/9494]	Loss: 0.1647	LR: 0.004000
Training Epoch: 23 [3072/9494]	Loss: 0.1285	LR: 0.004000
Training Epoch: 23 [3328/9494]	Loss: 0.1831	LR: 0.004000
Training Epoch: 23 [3584/9494]	Loss: 0.1258	LR: 0.004000
Training Epoch: 23 [3840/9494]	Loss: 0.1790	LR: 0.004000
Training Epoch: 23 [4096/9494]	Loss: 0.1530	LR: 0.004000
Training Epoch: 23 [4352/9494]	Loss: 0.1584	LR: 0.004000
Training Epoch: 23 [4608/9494]	Loss: 0.1620	LR: 0.004000
Training Epoch: 23 [4864/9494]	Loss: 0.1496	LR: 0.004000
Training Epoch: 23 [5120/9494]	Loss: 0.1468	LR: 0.004000
Training Epoch: 23 [5376/9494]	Loss: 0.1501	LR: 0.004000
Training Epoch: 23 [5632/9494]	Loss: 0.1330	LR: 0.004000
Training Epoch: 23 [5888/9494]	Loss: 0.1134	LR: 0.004000
Training Epoch: 23 [6144/9494]	Loss: 0.1253	LR: 0.004000
Training Epoch: 23 [6400/9494]	Loss: 0.1365	LR: 0.004000
Training Epoch: 23 [6656/9494]	Loss: 0.1339	LR: 0.004000
Training Epoch: 23 [6912/9494]	Loss: 0.1509	LR: 0.004000
Training Epoch: 23 [7168/9494]	Loss: 0.1728	LR: 0.004000
Training Epoch: 23 [7424/9494]	Loss: 0.1509	LR: 0.004000
Training Epoch: 23 [7680/9494]	Loss: 0.1867	LR: 0.004000
Training Epoch: 23 [7936/9494]	Loss: 0.1604	LR: 0.004000
Training Epoch: 23 [8192/9494]	Loss: 0.1475	LR: 0.004000
Training Epoch: 23 [8448/9494]	Loss: 0.1430	LR: 0.004000
Training Epoch: 23 [8704/9494]	Loss: 0.1797	LR: 0.004000
Training Epoch: 23 [8960/9494]	Loss: 0.1843	LR: 0.004000
Training Epoch: 23 [9216/9494]	Loss: 0.1437	LR: 0.004000
Training Epoch: 23 [9472/9494]	Loss: 0.1392	LR: 0.004000
Training Epoch: 23 [9494/9494]	Loss: 0.1395	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1517, Train Accuracy: 0.9369
Epoch 23 training time consumed: 137.29s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9443, Time consumed:7.76s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-23-best.pth
Training Epoch: 24 [256/9494]	Loss: 0.1357	LR: 0.004000
Training Epoch: 24 [512/9494]	Loss: 0.1002	LR: 0.004000
Training Epoch: 24 [768/9494]	Loss: 0.1378	LR: 0.004000
Training Epoch: 24 [1024/9494]	Loss: 0.0904	LR: 0.004000
Training Epoch: 24 [1280/9494]	Loss: 0.1600	LR: 0.004000
Training Epoch: 24 [1536/9494]	Loss: 0.1270	LR: 0.004000
Training Epoch: 24 [1792/9494]	Loss: 0.1386	LR: 0.004000
Training Epoch: 24 [2048/9494]	Loss: 0.1409	LR: 0.004000
Training Epoch: 24 [2304/9494]	Loss: 0.1738	LR: 0.004000
Training Epoch: 24 [2560/9494]	Loss: 0.1963	LR: 0.004000
Training Epoch: 24 [2816/9494]	Loss: 0.1140	LR: 0.004000
Training Epoch: 24 [3072/9494]	Loss: 0.1154	LR: 0.004000
Training Epoch: 24 [3328/9494]	Loss: 0.1324	LR: 0.004000
Training Epoch: 24 [3584/9494]	Loss: 0.1609	LR: 0.004000
Training Epoch: 24 [3840/9494]	Loss: 0.1368	LR: 0.004000
Training Epoch: 24 [4096/9494]	Loss: 0.1195	LR: 0.004000
Training Epoch: 24 [4352/9494]	Loss: 0.1397	LR: 0.004000
Training Epoch: 24 [4608/9494]	Loss: 0.1429	LR: 0.004000
Training Epoch: 24 [4864/9494]	Loss: 0.1846	LR: 0.004000
Training Epoch: 24 [5120/9494]	Loss: 0.1167	LR: 0.004000
Training Epoch: 24 [5376/9494]	Loss: 0.1412	LR: 0.004000
Training Epoch: 24 [5632/9494]	Loss: 0.1118	LR: 0.004000
Training Epoch: 24 [5888/9494]	Loss: 0.1132	LR: 0.004000
Training Epoch: 24 [6144/9494]	Loss: 0.1112	LR: 0.004000
Training Epoch: 24 [6400/9494]	Loss: 0.1611	LR: 0.004000
Training Epoch: 24 [6656/9494]	Loss: 0.1884	LR: 0.004000
Training Epoch: 24 [6912/9494]	Loss: 0.1547	LR: 0.004000
Training Epoch: 24 [7168/9494]	Loss: 0.1659	LR: 0.004000
Training Epoch: 24 [7424/9494]	Loss: 0.1568	LR: 0.004000
Training Epoch: 24 [7680/9494]	Loss: 0.1330	LR: 0.004000
Training Epoch: 24 [7936/9494]	Loss: 0.1147	LR: 0.004000
Training Epoch: 24 [8192/9494]	Loss: 0.1432	LR: 0.004000
Training Epoch: 24 [8448/9494]	Loss: 0.1731	LR: 0.004000
Training Epoch: 24 [8704/9494]	Loss: 0.1610	LR: 0.004000
Training Epoch: 24 [8960/9494]	Loss: 0.1304	LR: 0.004000
Training Epoch: 24 [9216/9494]	Loss: 0.1610	LR: 0.004000
Training Epoch: 24 [9472/9494]	Loss: 0.1698	LR: 0.004000
Training Epoch: 24 [9494/9494]	Loss: 0.2558	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1423, Train Accuracy: 0.9415
Epoch 24 training time consumed: 138.14s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0006, Accuracy: 0.9448, Time consumed:7.90s
Saving weights file to checkpoint/retrain/ResNet18/Thursday_24_July_2025_18h_00m_11s/ResNet18-MUCAC-seed2-ret100-24-best.pth
Training Epoch: 25 [256/9494]	Loss: 0.1650	LR: 0.004000
Training Epoch: 25 [512/9494]	Loss: 0.1316	LR: 0.004000
Training Epoch: 25 [768/9494]	Loss: 0.1645	LR: 0.004000
Training Epoch: 25 [1024/9494]	Loss: 0.1097	LR: 0.004000
Training Epoch: 25 [1280/9494]	Loss: 0.1294	LR: 0.004000
Training Epoch: 25 [1536/9494]	Loss: 0.1317	LR: 0.004000
Training Epoch: 25 [1792/9494]	Loss: 0.1467	LR: 0.004000
Training Epoch: 25 [2048/9494]	Loss: 0.1195	LR: 0.004000
Training Epoch: 25 [2304/9494]	Loss: 0.1542	LR: 0.004000
Training Epoch: 25 [2560/9494]	Loss: 0.1672	LR: 0.004000
Training Epoch: 25 [2816/9494]	Loss: 0.1113	LR: 0.004000
Training Epoch: 25 [3072/9494]	Loss: 0.1718	LR: 0.004000
Training Epoch: 25 [3328/9494]	Loss: 0.1856	LR: 0.004000
Training Epoch: 25 [3584/9494]	Loss: 0.1892	LR: 0.004000
Training Epoch: 25 [3840/9494]	Loss: 0.1274	LR: 0.004000
Training Epoch: 25 [4096/9494]	Loss: 0.1504	LR: 0.004000
Training Epoch: 25 [4352/9494]	Loss: 0.1460	LR: 0.004000
Training Epoch: 25 [4608/9494]	Loss: 0.1321	LR: 0.004000
Training Epoch: 25 [4864/9494]	Loss: 0.1139	LR: 0.004000
Training Epoch: 25 [5120/9494]	Loss: 0.1733	LR: 0.004000
Training Epoch: 25 [5376/9494]	Loss: 0.1178	LR: 0.004000
Training Epoch: 25 [5632/9494]	Loss: 0.1739	LR: 0.004000
Training Epoch: 25 [5888/9494]	Loss: 0.1670	LR: 0.004000
Training Epoch: 25 [6144/9494]	Loss: 0.1381	LR: 0.004000
Training Epoch: 25 [6400/9494]	Loss: 0.1385	LR: 0.004000
Training Epoch: 25 [6656/9494]	Loss: 0.1342	LR: 0.004000
Training Epoch: 25 [6912/9494]	Loss: 0.1245	LR: 0.004000
Training Epoch: 25 [7168/9494]	Loss: 0.1655	LR: 0.004000
Training Epoch: 25 [7424/9494]	Loss: 0.1376	LR: 0.004000
Training Epoch: 25 [7680/9494]	Loss: 0.1427	LR: 0.004000
Training Epoch: 25 [7936/9494]	Loss: 0.1393	LR: 0.004000
Training Epoch: 25 [8192/9494]	Loss: 0.1523	LR: 0.004000
Training Epoch: 25 [8448/9494]	Loss: 0.1475	LR: 0.004000
Training Epoch: 25 [8704/9494]	Loss: 0.1487	LR: 0.004000
Training Epoch: 25 [8960/9494]	Loss: 0.1759	LR: 0.004000
Training Epoch: 25 [9216/9494]	Loss: 0.1687	LR: 0.004000
Training Epoch: 25 [9472/9494]	Loss: 0.2088	LR: 0.004000
Training Epoch: 25 [9494/9494]	Loss: 0.1699	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1487, Train Accuracy: 0.9374
Epoch 25 training time consumed: 137.26s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9409, Time consumed:7.87s
Training Epoch: 26 [256/9494]	Loss: 0.1159	LR: 0.004000
Training Epoch: 26 [512/9494]	Loss: 0.1619	LR: 0.004000
Training Epoch: 26 [768/9494]	Loss: 0.1241	LR: 0.004000
Training Epoch: 26 [1024/9494]	Loss: 0.1419	LR: 0.004000
Training Epoch: 26 [1280/9494]	Loss: 0.1652	LR: 0.004000
Training Epoch: 26 [1536/9494]	Loss: 0.1571	LR: 0.004000
Training Epoch: 26 [1792/9494]	Loss: 0.1839	LR: 0.004000
Training Epoch: 26 [2048/9494]	Loss: 0.1379	LR: 0.004000
Training Epoch: 26 [2304/9494]	Loss: 0.1440	LR: 0.004000
Training Epoch: 26 [2560/9494]	Loss: 0.1350	LR: 0.004000
Training Epoch: 26 [2816/9494]	Loss: 0.1442	LR: 0.004000
Training Epoch: 26 [3072/9494]	Loss: 0.1296	LR: 0.004000
Training Epoch: 26 [3328/9494]	Loss: 0.1509	LR: 0.004000
Training Epoch: 26 [3584/9494]	Loss: 0.1533	LR: 0.004000
Training Epoch: 26 [3840/9494]	Loss: 0.1243	LR: 0.004000
Training Epoch: 26 [4096/9494]	Loss: 0.1523	LR: 0.004000
Training Epoch: 26 [4352/9494]	Loss: 0.2188	LR: 0.004000
Training Epoch: 26 [4608/9494]	Loss: 0.1638	LR: 0.004000
Training Epoch: 26 [4864/9494]	Loss: 0.1648	LR: 0.004000
Training Epoch: 26 [5120/9494]	Loss: 0.1588	LR: 0.004000
Training Epoch: 26 [5376/9494]	Loss: 0.1689	LR: 0.004000
Training Epoch: 26 [5632/9494]	Loss: 0.1534	LR: 0.004000
Training Epoch: 26 [5888/9494]	Loss: 0.1166	LR: 0.004000
Training Epoch: 26 [6144/9494]	Loss: 0.1612	LR: 0.004000
Training Epoch: 26 [6400/9494]	Loss: 0.1333	LR: 0.004000
Training Epoch: 26 [6656/9494]	Loss: 0.1561	LR: 0.004000
Training Epoch: 26 [6912/9494]	Loss: 0.1011	LR: 0.004000
Training Epoch: 26 [7168/9494]	Loss: 0.1552	LR: 0.004000
Training Epoch: 26 [7424/9494]	Loss: 0.1306	LR: 0.004000
Training Epoch: 26 [7680/9494]	Loss: 0.1490	LR: 0.004000
Training Epoch: 26 [7936/9494]	Loss: 0.1203	LR: 0.004000
Training Epoch: 26 [8192/9494]	Loss: 0.1473	LR: 0.004000
Training Epoch: 26 [8448/9494]	Loss: 0.1329	LR: 0.004000
Training Epoch: 26 [8704/9494]	Loss: 0.0919	LR: 0.004000
Training Epoch: 26 [8960/9494]	Loss: 0.1240	LR: 0.004000
Training Epoch: 26 [9216/9494]	Loss: 0.1604	LR: 0.004000
Training Epoch: 26 [9472/9494]	Loss: 0.1082	LR: 0.004000
Training Epoch: 26 [9494/9494]	Loss: 0.1112	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1442, Train Accuracy: 0.9402
Epoch 26 training time consumed: 137.31s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0005, Accuracy: 0.9448, Time consumed:7.85s
Training Epoch: 27 [256/9494]	Loss: 0.0846	LR: 0.004000
Training Epoch: 27 [512/9494]	Loss: 0.1343	LR: 0.004000
Training Epoch: 27 [768/9494]	Loss: 0.0961	LR: 0.004000
Training Epoch: 27 [1024/9494]	Loss: 0.1081	LR: 0.004000
Training Epoch: 27 [1280/9494]	Loss: 0.1373	LR: 0.004000
Training Epoch: 27 [1536/9494]	Loss: 0.0998	LR: 0.004000
Training Epoch: 27 [1792/9494]	Loss: 0.1389	LR: 0.004000
Training Epoch: 27 [2048/9494]	Loss: 0.1574	LR: 0.004000
Training Epoch: 27 [2304/9494]	Loss: 0.1490	LR: 0.004000
Training Epoch: 27 [2560/9494]	Loss: 0.1368	LR: 0.004000
Training Epoch: 27 [2816/9494]	Loss: 0.1730	LR: 0.004000
Training Epoch: 27 [3072/9494]	Loss: 0.1297	LR: 0.004000
Training Epoch: 27 [3328/9494]	Loss: 0.1383	LR: 0.004000
Training Epoch: 27 [3584/9494]	Loss: 0.1645	LR: 0.004000
Training Epoch: 27 [3840/9494]	Loss: 0.1338	LR: 0.004000
Training Epoch: 27 [4096/9494]	Loss: 0.1354	LR: 0.004000
Training Epoch: 27 [4352/9494]	Loss: 0.1235	LR: 0.004000
Training Epoch: 27 [4608/9494]	Loss: 0.1809	LR: 0.004000
Training Epoch: 27 [4864/9494]	Loss: 0.1231	LR: 0.004000
Training Epoch: 27 [5120/9494]	Loss: 0.1564	LR: 0.004000
Training Epoch: 27 [5376/9494]	Loss: 0.1618	LR: 0.004000
Training Epoch: 27 [5632/9494]	Loss: 0.1526	LR: 0.004000
Training Epoch: 27 [5888/9494]	Loss: 0.1597	LR: 0.004000
Training Epoch: 27 [6144/9494]	Loss: 0.1729	LR: 0.004000
Training Epoch: 27 [6400/9494]	Loss: 0.1829	LR: 0.004000
Training Epoch: 27 [6656/9494]	Loss: 0.1345	LR: 0.004000
Training Epoch: 27 [6912/9494]	Loss: 0.1309	LR: 0.004000
Training Epoch: 27 [7168/9494]	Loss: 0.1451	LR: 0.004000
Training Epoch: 27 [7424/9494]	Loss: 0.1318	LR: 0.004000
Training Epoch: 27 [7680/9494]	Loss: 0.1470	LR: 0.004000
Training Epoch: 27 [7936/9494]	Loss: 0.1216	LR: 0.004000
Training Epoch: 27 [8192/9494]	Loss: 0.1077	LR: 0.004000
Training Epoch: 27 [8448/9494]	Loss: 0.1576	LR: 0.004000
Training Epoch: 27 [8704/9494]	Loss: 0.1417	LR: 0.004000
Training Epoch: 27 [8960/9494]	Loss: 0.1147	LR: 0.004000
Training Epoch: 27 [9216/9494]	Loss: 0.1775	LR: 0.004000
Training Epoch: 27 [9472/9494]	Loss: 0.1315	LR: 0.004000
Training Epoch: 27 [9494/9494]	Loss: 0.1316	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1398, Train Accuracy: 0.9440
Epoch 27 training time consumed: 136.97s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0005, Accuracy: 0.9448, Time consumed:7.94s
Training Epoch: 28 [256/9494]	Loss: 0.1272	LR: 0.004000
Training Epoch: 28 [512/9494]	Loss: 0.1628	LR: 0.004000
Training Epoch: 28 [768/9494]	Loss: 0.1381	LR: 0.004000
Training Epoch: 28 [1024/9494]	Loss: 0.1086	LR: 0.004000
Training Epoch: 28 [1280/9494]	Loss: 0.1306	LR: 0.004000
Training Epoch: 28 [1536/9494]	Loss: 0.1674	LR: 0.004000
Training Epoch: 28 [1792/9494]	Loss: 0.1104	LR: 0.004000
Training Epoch: 28 [2048/9494]	Loss: 0.1193	LR: 0.004000
Training Epoch: 28 [2304/9494]	Loss: 0.0961	LR: 0.004000
Training Epoch: 28 [2560/9494]	Loss: 0.1053	LR: 0.004000
Training Epoch: 28 [2816/9494]	Loss: 0.1742	LR: 0.004000
Training Epoch: 28 [3072/9494]	Loss: 0.1448	LR: 0.004000
Training Epoch: 28 [3328/9494]	Loss: 0.1549	LR: 0.004000
Training Epoch: 28 [3584/9494]	Loss: 0.1477	LR: 0.004000
Training Epoch: 28 [3840/9494]	Loss: 0.1152	LR: 0.004000
Training Epoch: 28 [4096/9494]	Loss: 0.1202	LR: 0.004000
Training Epoch: 28 [4352/9494]	Loss: 0.1271	LR: 0.004000
Training Epoch: 28 [4608/9494]	Loss: 0.1349	LR: 0.004000
Training Epoch: 28 [4864/9494]	Loss: 0.1259	LR: 0.004000
Training Epoch: 28 [5120/9494]	Loss: 0.1263	LR: 0.004000
Training Epoch: 28 [5376/9494]	Loss: 0.1306	LR: 0.004000
Training Epoch: 28 [5632/9494]	Loss: 0.1463	LR: 0.004000
Training Epoch: 28 [5888/9494]	Loss: 0.1772	LR: 0.004000
Training Epoch: 28 [6144/9494]	Loss: 0.1305	LR: 0.004000
Training Epoch: 28 [6400/9494]	Loss: 0.0947	LR: 0.004000
Training Epoch: 28 [6656/9494]	Loss: 0.1114	LR: 0.004000
Training Epoch: 28 [6912/9494]	Loss: 0.1437	LR: 0.004000
Training Epoch: 28 [7168/9494]	Loss: 0.1249	LR: 0.004000
Training Epoch: 28 [7424/9494]	Loss: 0.1413	LR: 0.004000
Training Epoch: 28 [7680/9494]	Loss: 0.1452	LR: 0.004000
Training Epoch: 28 [7936/9494]	Loss: 0.1273	LR: 0.004000
Training Epoch: 28 [8192/9494]	Loss: 0.1709	LR: 0.004000
Training Epoch: 28 [8448/9494]	Loss: 0.1363	LR: 0.004000
Training Epoch: 28 [8704/9494]	Loss: 0.0969	LR: 0.004000
Training Epoch: 28 [8960/9494]	Loss: 0.1548	LR: 0.004000
Training Epoch: 28 [9216/9494]	Loss: 0.1696	LR: 0.004000
Training Epoch: 28 [9472/9494]	Loss: 0.1027	LR: 0.004000
Training Epoch: 28 [9494/9494]	Loss: 0.4924	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1344, Train Accuracy: 0.9452
Epoch 28 training time consumed: 136.95s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0005, Accuracy: 0.9443, Time consumed:7.96s
Training Epoch: 29 [256/9494]	Loss: 0.1448	LR: 0.004000
Training Epoch: 29 [512/9494]	Loss: 0.1225	LR: 0.004000
Training Epoch: 29 [768/9494]	Loss: 0.1647	LR: 0.004000
Training Epoch: 29 [1024/9494]	Loss: 0.2001	LR: 0.004000
Training Epoch: 29 [1280/9494]	Loss: 0.0988	LR: 0.004000
Training Epoch: 29 [1536/9494]	Loss: 0.0820	LR: 0.004000
Training Epoch: 29 [1792/9494]	Loss: 0.1562	LR: 0.004000
Training Epoch: 29 [2048/9494]	Loss: 0.1592	LR: 0.004000
Training Epoch: 29 [2304/9494]	Loss: 0.1097	LR: 0.004000
Training Epoch: 29 [2560/9494]	Loss: 0.1577	LR: 0.004000
Training Epoch: 29 [2816/9494]	Loss: 0.1460	LR: 0.004000
Training Epoch: 29 [3072/9494]	Loss: 0.1731	LR: 0.004000
Training Epoch: 29 [3328/9494]	Loss: 0.1359	LR: 0.004000
Training Epoch: 29 [3584/9494]	Loss: 0.1454	LR: 0.004000
Training Epoch: 29 [3840/9494]	Loss: 0.1683	LR: 0.004000
Training Epoch: 29 [4096/9494]	Loss: 0.1669	LR: 0.004000
Training Epoch: 29 [4352/9494]	Loss: 0.1965	LR: 0.004000
Training Epoch: 29 [4608/9494]	Loss: 0.1657	LR: 0.004000
Training Epoch: 29 [4864/9494]	Loss: 0.1355	LR: 0.004000
Training Epoch: 29 [5120/9494]	Loss: 0.1443	LR: 0.004000
Training Epoch: 29 [5376/9494]	Loss: 0.1571	LR: 0.004000
Training Epoch: 29 [5632/9494]	Loss: 0.1394	LR: 0.004000
Training Epoch: 29 [5888/9494]	Loss: 0.1134	LR: 0.004000
Training Epoch: 29 [6144/9494]	Loss: 0.0982	LR: 0.004000
Training Epoch: 29 [6400/9494]	Loss: 0.1956	LR: 0.004000
Training Epoch: 29 [6656/9494]	Loss: 0.1387	LR: 0.004000
Training Epoch: 29 [6912/9494]	Loss: 0.1207	LR: 0.004000
Training Epoch: 29 [7168/9494]	Loss: 0.1047	LR: 0.004000
Training Epoch: 29 [7424/9494]	Loss: 0.0957	LR: 0.004000
Training Epoch: 29 [7680/9494]	Loss: 0.1436	LR: 0.004000
Training Epoch: 29 [7936/9494]	Loss: 0.1229	LR: 0.004000
Training Epoch: 29 [8192/9494]	Loss: 0.1547	LR: 0.004000
Training Epoch: 29 [8448/9494]	Loss: 0.1544	LR: 0.004000
Training Epoch: 29 [8704/9494]	Loss: 0.1588	LR: 0.004000
Training Epoch: 29 [8960/9494]	Loss: 0.1445	LR: 0.004000
Training Epoch: 29 [9216/9494]	Loss: 0.1284	LR: 0.004000
Training Epoch: 29 [9472/9494]	Loss: 0.1330	LR: 0.004000
Training Epoch: 29 [9494/9494]	Loss: 0.1109	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1426, Train Accuracy: 0.9393
Epoch 29 training time consumed: 137.08s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0006, Accuracy: 0.9375, Time consumed:8.05s
Training Epoch: 30 [256/9494]	Loss: 0.1171	LR: 0.004000
Training Epoch: 30 [512/9494]	Loss: 0.1716	LR: 0.004000
Training Epoch: 30 [768/9494]	Loss: 0.1686	LR: 0.004000
Training Epoch: 30 [1024/9494]	Loss: 0.1349	LR: 0.004000
Training Epoch: 30 [1280/9494]	Loss: 0.1788	LR: 0.004000
Training Epoch: 30 [1536/9494]	Loss: 0.1464	LR: 0.004000
Training Epoch: 30 [1792/9494]	Loss: 0.1343	LR: 0.004000
Training Epoch: 30 [2048/9494]	Loss: 0.1107	LR: 0.004000
Training Epoch: 30 [2304/9494]	Loss: 0.1452	LR: 0.004000
Training Epoch: 30 [2560/9494]	Loss: 0.1659	LR: 0.004000
Training Epoch: 30 [2816/9494]	Loss: 0.1479	LR: 0.004000
Training Epoch: 30 [3072/9494]	Loss: 0.1740	LR: 0.004000
Training Epoch: 30 [3328/9494]	Loss: 0.1231	LR: 0.004000
Training Epoch: 30 [3584/9494]	Loss: 0.0938	LR: 0.004000
Training Epoch: 30 [3840/9494]	Loss: 0.1172	LR: 0.004000
Training Epoch: 30 [4096/9494]	Loss: 0.1469	LR: 0.004000
Training Epoch: 30 [4352/9494]	Loss: 0.1103	LR: 0.004000
Training Epoch: 30 [4608/9494]	Loss: 0.1020	LR: 0.004000
Training Epoch: 30 [4864/9494]	Loss: 0.1639	LR: 0.004000
Training Epoch: 30 [5120/9494]	Loss: 0.1225	LR: 0.004000
Training Epoch: 30 [5376/9494]	Loss: 0.1548	LR: 0.004000
Training Epoch: 30 [5632/9494]	Loss: 0.1310	LR: 0.004000
Training Epoch: 30 [5888/9494]	Loss: 0.1674	LR: 0.004000
Training Epoch: 30 [6144/9494]	Loss: 0.1168	LR: 0.004000
Training Epoch: 30 [6400/9494]	Loss: 0.1308	LR: 0.004000
Training Epoch: 30 [6656/9494]	Loss: 0.1553	LR: 0.004000
Training Epoch: 30 [6912/9494]	Loss: 0.1197	LR: 0.004000
Training Epoch: 30 [7168/9494]	Loss: 0.1599	LR: 0.004000
Training Epoch: 30 [7424/9494]	Loss: 0.1303	LR: 0.004000
Training Epoch: 30 [7680/9494]	Loss: 0.1124	LR: 0.004000
Training Epoch: 30 [7936/9494]	Loss: 0.2109	LR: 0.004000
Training Epoch: 30 [8192/9494]	Loss: 0.1288	LR: 0.004000
Training Epoch: 30 [8448/9494]	Loss: 0.1333	LR: 0.004000
Training Epoch: 30 [8704/9494]	Loss: 0.1285	LR: 0.004000
Training Epoch: 30 [8960/9494]	Loss: 0.1148	LR: 0.004000
Training Epoch: 30 [9216/9494]	Loss: 0.1851	LR: 0.004000
Training Epoch: 30 [9472/9494]	Loss: 0.1072	LR: 0.004000
Training Epoch: 30 [9494/9494]	Loss: 0.0808	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1394, Train Accuracy: 0.9432
Epoch 30 training time consumed: 136.97s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0005, Accuracy: 0.9448, Time consumed:7.93s
Training Epoch: 31 [256/9494]	Loss: 0.1153	LR: 0.004000
Training Epoch: 31 [512/9494]	Loss: 0.1421	LR: 0.004000
Training Epoch: 31 [768/9494]	Loss: 0.0927	LR: 0.004000
Training Epoch: 31 [1024/9494]	Loss: 0.1737	LR: 0.004000
Training Epoch: 31 [1280/9494]	Loss: 0.0947	LR: 0.004000
Training Epoch: 31 [1536/9494]	Loss: 0.0663	LR: 0.004000
Training Epoch: 31 [1792/9494]	Loss: 0.1221	LR: 0.004000
Training Epoch: 31 [2048/9494]	Loss: 0.1575	LR: 0.004000
Training Epoch: 31 [2304/9494]	Loss: 0.1573	LR: 0.004000
Training Epoch: 31 [2560/9494]	Loss: 0.1040	LR: 0.004000
Training Epoch: 31 [2816/9494]	Loss: 0.1245	LR: 0.004000
Training Epoch: 31 [3072/9494]	Loss: 0.1086	LR: 0.004000
Training Epoch: 31 [3328/9494]	Loss: 0.1378	LR: 0.004000
Training Epoch: 31 [3584/9494]	Loss: 0.1184	LR: 0.004000
Training Epoch: 31 [3840/9494]	Loss: 0.1282	LR: 0.004000
Training Epoch: 31 [4096/9494]	Loss: 0.1030	LR: 0.004000
Training Epoch: 31 [4352/9494]	Loss: 0.1272	LR: 0.004000
Training Epoch: 31 [4608/9494]	Loss: 0.1602	LR: 0.004000
Training Epoch: 31 [4864/9494]	Loss: 0.1234	LR: 0.004000
Training Epoch: 31 [5120/9494]	Loss: 0.1114	LR: 0.004000
Training Epoch: 31 [5376/9494]	Loss: 0.1108	LR: 0.004000
Training Epoch: 31 [5632/9494]	Loss: 0.1317	LR: 0.004000
Training Epoch: 31 [5888/9494]	Loss: 0.1538	LR: 0.004000
Training Epoch: 31 [6144/9494]	Loss: 0.1835	LR: 0.004000
Training Epoch: 31 [6400/9494]	Loss: 0.1089	LR: 0.004000
Training Epoch: 31 [6656/9494]	Loss: 0.1648	LR: 0.004000
Training Epoch: 31 [6912/9494]	Loss: 0.1481	LR: 0.004000
Training Epoch: 31 [7168/9494]	Loss: 0.1411	LR: 0.004000
Training Epoch: 31 [7424/9494]	Loss: 0.1789	LR: 0.004000
Training Epoch: 31 [7680/9494]	Loss: 0.0943	LR: 0.004000
Training Epoch: 31 [7936/9494]	Loss: 0.1550	LR: 0.004000
Training Epoch: 31 [8192/9494]	Loss: 0.1685	LR: 0.004000
Training Epoch: 31 [8448/9494]	Loss: 0.0778	LR: 0.004000
Training Epoch: 31 [8704/9494]	Loss: 0.1528	LR: 0.004000
Training Epoch: 31 [8960/9494]	Loss: 0.1240	LR: 0.004000
Training Epoch: 31 [9216/9494]	Loss: 0.1366	LR: 0.004000
Training Epoch: 31 [9472/9494]	Loss: 0.1104	LR: 0.004000
Training Epoch: 31 [9494/9494]	Loss: 0.2135	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1302, Train Accuracy: 0.9473
Epoch 31 training time consumed: 137.15s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9429, Time consumed:8.06s
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: 94.87847137451172
Retain Accuracy: 94.06586456298828
Zero-Retain Forget (ZRF): 0.771500289440155
Membership Inference Attack (MIA): 0.32637571157495254
Forget vs Retain Membership Inference Attack (MIA): 0.4834123222748815
Forget vs Test Membership Inference Attack (MIA): 0.5497630331753555
Test vs Retain Membership Inference Attack (MIA): 0.5145278450363197
Train vs Test Membership Inference Attack (MIA): 0.5435835351089588
Forget Set Accuracy (Df): 92.09895324707031
Method Execution Time: 23399.36 seconds
