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

📌 S Retain class distribution for seed 5:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 5:
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: 0.7844	LR: 0.000000
Training Epoch: 1 [512/9494]	Loss: 0.7804	LR: 0.002632
Training Epoch: 1 [768/9494]	Loss: 0.6910	LR: 0.005263
Training Epoch: 1 [1024/9494]	Loss: 0.9289	LR: 0.007895
Training Epoch: 1 [1280/9494]	Loss: 1.0110	LR: 0.010526
Training Epoch: 1 [1536/9494]	Loss: 0.6852	LR: 0.013158
Training Epoch: 1 [1792/9494]	Loss: 1.2849	LR: 0.015789
Training Epoch: 1 [2048/9494]	Loss: 0.6752	LR: 0.018421
Training Epoch: 1 [2304/9494]	Loss: 1.0331	LR: 0.021053
Training Epoch: 1 [2560/9494]	Loss: 0.7064	LR: 0.023684
Training Epoch: 1 [2816/9494]	Loss: 0.7479	LR: 0.026316
Training Epoch: 1 [3072/9494]	Loss: 0.8278	LR: 0.028947
Training Epoch: 1 [3328/9494]	Loss: 1.0305	LR: 0.031579
Training Epoch: 1 [3584/9494]	Loss: 0.9051	LR: 0.034211
Training Epoch: 1 [3840/9494]	Loss: 0.7899	LR: 0.036842
Training Epoch: 1 [4096/9494]	Loss: 0.7270	LR: 0.039474
Training Epoch: 1 [4352/9494]	Loss: 1.0046	LR: 0.042105
Training Epoch: 1 [4608/9494]	Loss: 0.8727	LR: 0.044737
Training Epoch: 1 [4864/9494]	Loss: 0.6857	LR: 0.047368
Training Epoch: 1 [5120/9494]	Loss: 0.8351	LR: 0.050000
Training Epoch: 1 [5376/9494]	Loss: 0.6719	LR: 0.052632
Training Epoch: 1 [5632/9494]	Loss: 0.6988	LR: 0.055263
Training Epoch: 1 [5888/9494]	Loss: 0.6815	LR: 0.057895
Training Epoch: 1 [6144/9494]	Loss: 0.7335	LR: 0.060526
Training Epoch: 1 [6400/9494]	Loss: 0.6750	LR: 0.063158
Training Epoch: 1 [6656/9494]	Loss: 0.7052	LR: 0.065789
Training Epoch: 1 [6912/9494]	Loss: 0.6998	LR: 0.068421
Training Epoch: 1 [7168/9494]	Loss: 0.6882	LR: 0.071053
Training Epoch: 1 [7424/9494]	Loss: 0.6611	LR: 0.073684
Training Epoch: 1 [7680/9494]	Loss: 0.7074	LR: 0.076316
Training Epoch: 1 [7936/9494]	Loss: 0.7490	LR: 0.078947
Training Epoch: 1 [8192/9494]	Loss: 0.6697	LR: 0.081579
Training Epoch: 1 [8448/9494]	Loss: 0.6760	LR: 0.084211
Training Epoch: 1 [8704/9494]	Loss: 0.6976	LR: 0.086842
Training Epoch: 1 [8960/9494]	Loss: 0.7015	LR: 0.089474
Training Epoch: 1 [9216/9494]	Loss: 0.6803	LR: 0.092105
Training Epoch: 1 [9472/9494]	Loss: 0.6839	LR: 0.094737
Training Epoch: 1 [9494/9494]	Loss: 0.7453	LR: 0.097368
Epoch 1 - Average Train Loss: 0.7779, Train Accuracy: 0.5371
Epoch 1 training time consumed: 320.44s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0036, Accuracy: 0.5487, Time consumed:7.96s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-1-best.pth
Training Epoch: 2 [256/9494]	Loss: 0.7830	LR: 0.100000
Training Epoch: 2 [512/9494]	Loss: 0.7931	LR: 0.100000
Training Epoch: 2 [768/9494]	Loss: 0.8411	LR: 0.100000
Training Epoch: 2 [1024/9494]	Loss: 0.6841	LR: 0.100000
Training Epoch: 2 [1280/9494]	Loss: 0.9369	LR: 0.100000
Training Epoch: 2 [1536/9494]	Loss: 0.6617	LR: 0.100000
Training Epoch: 2 [1792/9494]	Loss: 0.8803	LR: 0.100000
Training Epoch: 2 [2048/9494]	Loss: 0.7361	LR: 0.100000
Training Epoch: 2 [2304/9494]	Loss: 0.6824	LR: 0.100000
Training Epoch: 2 [2560/9494]	Loss: 0.6754	LR: 0.100000
Training Epoch: 2 [2816/9494]	Loss: 0.7466	LR: 0.100000
Training Epoch: 2 [3072/9494]	Loss: 0.6765	LR: 0.100000
Training Epoch: 2 [3328/9494]	Loss: 0.6793	LR: 0.100000
Training Epoch: 2 [3584/9494]	Loss: 0.7346	LR: 0.100000
Training Epoch: 2 [3840/9494]	Loss: 0.6840	LR: 0.100000
Training Epoch: 2 [4096/9494]	Loss: 0.6791	LR: 0.100000
Training Epoch: 2 [4352/9494]	Loss: 0.7047	LR: 0.100000
Training Epoch: 2 [4608/9494]	Loss: 0.6868	LR: 0.100000
Training Epoch: 2 [4864/9494]	Loss: 0.6727	LR: 0.100000
Training Epoch: 2 [5120/9494]	Loss: 0.6976	LR: 0.100000
Training Epoch: 2 [5376/9494]	Loss: 0.6605	LR: 0.100000
Training Epoch: 2 [5632/9494]	Loss: 0.6623	LR: 0.100000
Training Epoch: 2 [5888/9494]	Loss: 0.7367	LR: 0.100000
Training Epoch: 2 [6144/9494]	Loss: 0.6937	LR: 0.100000
Training Epoch: 2 [6400/9494]	Loss: 0.6933	LR: 0.100000
Training Epoch: 2 [6656/9494]	Loss: 0.7058	LR: 0.100000
Training Epoch: 2 [6912/9494]	Loss: 0.6603	LR: 0.100000
Training Epoch: 2 [7168/9494]	Loss: 0.6740	LR: 0.100000
Training Epoch: 2 [7424/9494]	Loss: 0.6733	LR: 0.100000
Training Epoch: 2 [7680/9494]	Loss: 0.6734	LR: 0.100000
Training Epoch: 2 [7936/9494]	Loss: 0.6911	LR: 0.100000
Training Epoch: 2 [8192/9494]	Loss: 0.6665	LR: 0.100000
Training Epoch: 2 [8448/9494]	Loss: 0.6909	LR: 0.100000
Training Epoch: 2 [8704/9494]	Loss: 0.6755	LR: 0.100000
Training Epoch: 2 [8960/9494]	Loss: 0.6841	LR: 0.100000
Training Epoch: 2 [9216/9494]	Loss: 0.6881	LR: 0.100000
Training Epoch: 2 [9472/9494]	Loss: 0.7056	LR: 0.100000
Training Epoch: 2 [9494/9494]	Loss: 0.6653	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7099, Train Accuracy: 0.5544
Epoch 2 training time consumed: 137.53s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0031, Accuracy: 0.5540, Time consumed:7.91s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-2-best.pth
Training Epoch: 3 [256/9494]	Loss: 0.7454	LR: 0.100000
Training Epoch: 3 [512/9494]	Loss: 0.6937	LR: 0.100000
Training Epoch: 3 [768/9494]	Loss: 0.7192	LR: 0.100000
Training Epoch: 3 [1024/9494]	Loss: 0.6927	LR: 0.100000
Training Epoch: 3 [1280/9494]	Loss: 0.7010	LR: 0.100000
Training Epoch: 3 [1536/9494]	Loss: 0.6828	LR: 0.100000
Training Epoch: 3 [1792/9494]	Loss: 0.6663	LR: 0.100000
Training Epoch: 3 [2048/9494]	Loss: 0.6889	LR: 0.100000
Training Epoch: 3 [2304/9494]	Loss: 0.6616	LR: 0.100000
Training Epoch: 3 [2560/9494]	Loss: 0.6668	LR: 0.100000
Training Epoch: 3 [2816/9494]	Loss: 0.6760	LR: 0.100000
Training Epoch: 3 [3072/9494]	Loss: 0.6860	LR: 0.100000
Training Epoch: 3 [3328/9494]	Loss: 0.6494	LR: 0.100000
Training Epoch: 3 [3584/9494]	Loss: 0.6553	LR: 0.100000
Training Epoch: 3 [3840/9494]	Loss: 0.6447	LR: 0.100000
Training Epoch: 3 [4096/9494]	Loss: 0.6813	LR: 0.100000
Training Epoch: 3 [4352/9494]	Loss: 0.6625	LR: 0.100000
Training Epoch: 3 [4608/9494]	Loss: 0.7008	LR: 0.100000
Training Epoch: 3 [4864/9494]	Loss: 0.8313	LR: 0.100000
Training Epoch: 3 [5120/9494]	Loss: 0.7124	LR: 0.100000
Training Epoch: 3 [5376/9494]	Loss: 0.6345	LR: 0.100000
Training Epoch: 3 [5632/9494]	Loss: 0.7792	LR: 0.100000
Training Epoch: 3 [5888/9494]	Loss: 0.8073	LR: 0.100000
Training Epoch: 3 [6144/9494]	Loss: 0.7288	LR: 0.100000
Training Epoch: 3 [6400/9494]	Loss: 0.7110	LR: 0.100000
Training Epoch: 3 [6656/9494]	Loss: 0.7032	LR: 0.100000
Training Epoch: 3 [6912/9494]	Loss: 0.7033	LR: 0.100000
Training Epoch: 3 [7168/9494]	Loss: 0.7667	LR: 0.100000
Training Epoch: 3 [7424/9494]	Loss: 0.7519	LR: 0.100000
Training Epoch: 3 [7680/9494]	Loss: 0.6896	LR: 0.100000
Training Epoch: 3 [7936/9494]	Loss: 0.6936	LR: 0.100000
Training Epoch: 3 [8192/9494]	Loss: 0.6954	LR: 0.100000
Training Epoch: 3 [8448/9494]	Loss: 0.7097	LR: 0.100000
Training Epoch: 3 [8704/9494]	Loss: 0.6860	LR: 0.100000
Training Epoch: 3 [8960/9494]	Loss: 0.6606	LR: 0.100000
Training Epoch: 3 [9216/9494]	Loss: 0.6798	LR: 0.100000
Training Epoch: 3 [9472/9494]	Loss: 0.6789	LR: 0.100000
Training Epoch: 3 [9494/9494]	Loss: 0.7338	LR: 0.100000
Epoch 3 - Average Train Loss: 0.7000, Train Accuracy: 0.5434
Epoch 3 training time consumed: 137.28s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5743, Time consumed:7.88s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-3-best.pth
Training Epoch: 4 [256/9494]	Loss: 0.6650	LR: 0.100000
Training Epoch: 4 [512/9494]	Loss: 0.6670	LR: 0.100000
Training Epoch: 4 [768/9494]	Loss: 0.7015	LR: 0.100000
Training Epoch: 4 [1024/9494]	Loss: 0.6900	LR: 0.100000
Training Epoch: 4 [1280/9494]	Loss: 0.6800	LR: 0.100000
Training Epoch: 4 [1536/9494]	Loss: 0.6686	LR: 0.100000
Training Epoch: 4 [1792/9494]	Loss: 0.6828	LR: 0.100000
Training Epoch: 4 [2048/9494]	Loss: 0.7036	LR: 0.100000
Training Epoch: 4 [2304/9494]	Loss: 0.6687	LR: 0.100000
Training Epoch: 4 [2560/9494]	Loss: 0.6716	LR: 0.100000
Training Epoch: 4 [2816/9494]	Loss: 0.6615	LR: 0.100000
Training Epoch: 4 [3072/9494]	Loss: 0.6466	LR: 0.100000
Training Epoch: 4 [3328/9494]	Loss: 0.6735	LR: 0.100000
Training Epoch: 4 [3584/9494]	Loss: 0.6667	LR: 0.100000
Training Epoch: 4 [3840/9494]	Loss: 0.6936	LR: 0.100000
Training Epoch: 4 [4096/9494]	Loss: 0.7016	LR: 0.100000
Training Epoch: 4 [4352/9494]	Loss: 0.6550	LR: 0.100000
Training Epoch: 4 [4608/9494]	Loss: 0.6779	LR: 0.100000
Training Epoch: 4 [4864/9494]	Loss: 0.6455	LR: 0.100000
Training Epoch: 4 [5120/9494]	Loss: 0.6225	LR: 0.100000
Training Epoch: 4 [5376/9494]	Loss: 0.6703	LR: 0.100000
Training Epoch: 4 [5632/9494]	Loss: 0.7010	LR: 0.100000
Training Epoch: 4 [5888/9494]	Loss: 0.6859	LR: 0.100000
Training Epoch: 4 [6144/9494]	Loss: 0.6921	LR: 0.100000
Training Epoch: 4 [6400/9494]	Loss: 0.6572	LR: 0.100000
Training Epoch: 4 [6656/9494]	Loss: 0.6652	LR: 0.100000
Training Epoch: 4 [6912/9494]	Loss: 0.6567	LR: 0.100000
Training Epoch: 4 [7168/9494]	Loss: 0.6628	LR: 0.100000
Training Epoch: 4 [7424/9494]	Loss: 0.6760	LR: 0.100000
Training Epoch: 4 [7680/9494]	Loss: 0.6642	LR: 0.100000
Training Epoch: 4 [7936/9494]	Loss: 0.6705	LR: 0.100000
Training Epoch: 4 [8192/9494]	Loss: 0.6687	LR: 0.100000
Training Epoch: 4 [8448/9494]	Loss: 0.6681	LR: 0.100000
Training Epoch: 4 [8704/9494]	Loss: 0.6595	LR: 0.100000
Training Epoch: 4 [8960/9494]	Loss: 0.6558	LR: 0.100000
Training Epoch: 4 [9216/9494]	Loss: 0.6722	LR: 0.100000
Training Epoch: 4 [9472/9494]	Loss: 0.7086	LR: 0.100000
Training Epoch: 4 [9494/9494]	Loss: 0.5717	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6721, Train Accuracy: 0.5927
Epoch 4 training time consumed: 137.21s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0030, Accuracy: 0.5879, Time consumed:7.96s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-4-best.pth
Training Epoch: 5 [256/9494]	Loss: 0.6422	LR: 0.100000
Training Epoch: 5 [512/9494]	Loss: 0.6788	LR: 0.100000
Training Epoch: 5 [768/9494]	Loss: 0.6518	LR: 0.100000
Training Epoch: 5 [1024/9494]	Loss: 0.6770	LR: 0.100000
Training Epoch: 5 [1280/9494]	Loss: 0.6684	LR: 0.100000
Training Epoch: 5 [1536/9494]	Loss: 0.6719	LR: 0.100000
Training Epoch: 5 [1792/9494]	Loss: 0.6679	LR: 0.100000
Training Epoch: 5 [2048/9494]	Loss: 0.6581	LR: 0.100000
Training Epoch: 5 [2304/9494]	Loss: 0.6721	LR: 0.100000
Training Epoch: 5 [2560/9494]	Loss: 0.6692	LR: 0.100000
Training Epoch: 5 [2816/9494]	Loss: 0.6657	LR: 0.100000
Training Epoch: 5 [3072/9494]	Loss: 0.6992	LR: 0.100000
Training Epoch: 5 [3328/9494]	Loss: 0.6708	LR: 0.100000
Training Epoch: 5 [3584/9494]	Loss: 0.6792	LR: 0.100000
Training Epoch: 5 [3840/9494]	Loss: 0.7005	LR: 0.100000
Training Epoch: 5 [4096/9494]	Loss: 0.6732	LR: 0.100000
Training Epoch: 5 [4352/9494]	Loss: 0.6691	LR: 0.100000
Training Epoch: 5 [4608/9494]	Loss: 0.6898	LR: 0.100000
Training Epoch: 5 [4864/9494]	Loss: 0.6701	LR: 0.100000
Training Epoch: 5 [5120/9494]	Loss: 0.6466	LR: 0.100000
Training Epoch: 5 [5376/9494]	Loss: 0.7013	LR: 0.100000
Training Epoch: 5 [5632/9494]	Loss: 0.7017	LR: 0.100000
Training Epoch: 5 [5888/9494]	Loss: 0.6748	LR: 0.100000
Training Epoch: 5 [6144/9494]	Loss: 0.6544	LR: 0.100000
Training Epoch: 5 [6400/9494]	Loss: 0.6516	LR: 0.100000
Training Epoch: 5 [6656/9494]	Loss: 0.6683	LR: 0.100000
Training Epoch: 5 [6912/9494]	Loss: 0.6685	LR: 0.100000
Training Epoch: 5 [7168/9494]	Loss: 0.6969	LR: 0.100000
Training Epoch: 5 [7424/9494]	Loss: 0.6904	LR: 0.100000
Training Epoch: 5 [7680/9494]	Loss: 0.6602	LR: 0.100000
Training Epoch: 5 [7936/9494]	Loss: 0.6518	LR: 0.100000
Training Epoch: 5 [8192/9494]	Loss: 0.6407	LR: 0.100000
Training Epoch: 5 [8448/9494]	Loss: 0.6723	LR: 0.100000
Training Epoch: 5 [8704/9494]	Loss: 0.6873	LR: 0.100000
Training Epoch: 5 [8960/9494]	Loss: 0.6444	LR: 0.100000
Training Epoch: 5 [9216/9494]	Loss: 0.6588	LR: 0.100000
Training Epoch: 5 [9472/9494]	Loss: 0.6525	LR: 0.100000
Training Epoch: 5 [9494/9494]	Loss: 0.5452	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6699, Train Accuracy: 0.5917
Epoch 5 training time consumed: 137.95s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0034, Accuracy: 0.5317, Time consumed:7.93s
Training Epoch: 6 [256/9494]	Loss: 0.6608	LR: 0.100000
Training Epoch: 6 [512/9494]	Loss: 0.6814	LR: 0.100000
Training Epoch: 6 [768/9494]	Loss: 0.6399	LR: 0.100000
Training Epoch: 6 [1024/9494]	Loss: 0.6998	LR: 0.100000
Training Epoch: 6 [1280/9494]	Loss: 0.6480	LR: 0.100000
Training Epoch: 6 [1536/9494]	Loss: 0.6661	LR: 0.100000
Training Epoch: 6 [1792/9494]	Loss: 0.6526	LR: 0.100000
Training Epoch: 6 [2048/9494]	Loss: 0.6711	LR: 0.100000
Training Epoch: 6 [2304/9494]	Loss: 0.6536	LR: 0.100000
Training Epoch: 6 [2560/9494]	Loss: 0.6420	LR: 0.100000
Training Epoch: 6 [2816/9494]	Loss: 0.6653	LR: 0.100000
Training Epoch: 6 [3072/9494]	Loss: 0.6560	LR: 0.100000
Training Epoch: 6 [3328/9494]	Loss: 0.6249	LR: 0.100000
Training Epoch: 6 [3584/9494]	Loss: 0.6585	LR: 0.100000
Training Epoch: 6 [3840/9494]	Loss: 0.6606	LR: 0.100000
Training Epoch: 6 [4096/9494]	Loss: 0.6580	LR: 0.100000
Training Epoch: 6 [4352/9494]	Loss: 0.6437	LR: 0.100000
Training Epoch: 6 [4608/9494]	Loss: 0.6318	LR: 0.100000
Training Epoch: 6 [4864/9494]	Loss: 0.6165	LR: 0.100000
Training Epoch: 6 [5120/9494]	Loss: 0.6373	LR: 0.100000
Training Epoch: 6 [5376/9494]	Loss: 0.6210	LR: 0.100000
Training Epoch: 6 [5632/9494]	Loss: 0.6498	LR: 0.100000
Training Epoch: 6 [5888/9494]	Loss: 0.6545	LR: 0.100000
Training Epoch: 6 [6144/9494]	Loss: 0.6168	LR: 0.100000
Training Epoch: 6 [6400/9494]	Loss: 0.6910	LR: 0.100000
Training Epoch: 6 [6656/9494]	Loss: 0.6387	LR: 0.100000
Training Epoch: 6 [6912/9494]	Loss: 0.5986	LR: 0.100000
Training Epoch: 6 [7168/9494]	Loss: 0.7048	LR: 0.100000
Training Epoch: 6 [7424/9494]	Loss: 0.6560	LR: 0.100000
Training Epoch: 6 [7680/9494]	Loss: 0.6463	LR: 0.100000
Training Epoch: 6 [7936/9494]	Loss: 0.6373	LR: 0.100000
Training Epoch: 6 [8192/9494]	Loss: 0.6242	LR: 0.100000
Training Epoch: 6 [8448/9494]	Loss: 0.6252	LR: 0.100000
Training Epoch: 6 [8704/9494]	Loss: 0.6183	LR: 0.100000
Training Epoch: 6 [8960/9494]	Loss: 0.6004	LR: 0.100000
Training Epoch: 6 [9216/9494]	Loss: 0.6289	LR: 0.100000
Training Epoch: 6 [9472/9494]	Loss: 0.5911	LR: 0.100000
Training Epoch: 6 [9494/9494]	Loss: 0.4978	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6448, Train Accuracy: 0.6350
Epoch 6 training time consumed: 137.56s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0031, Accuracy: 0.5564, Time consumed:7.90s
Training Epoch: 7 [256/9494]	Loss: 0.6685	LR: 0.100000
Training Epoch: 7 [512/9494]	Loss: 0.7263	LR: 0.100000
Training Epoch: 7 [768/9494]	Loss: 0.5763	LR: 0.100000
Training Epoch: 7 [1024/9494]	Loss: 0.5605	LR: 0.100000
Training Epoch: 7 [1280/9494]	Loss: 0.6131	LR: 0.100000
Training Epoch: 7 [1536/9494]	Loss: 0.6432	LR: 0.100000
Training Epoch: 7 [1792/9494]	Loss: 0.5869	LR: 0.100000
Training Epoch: 7 [2048/9494]	Loss: 0.6530	LR: 0.100000
Training Epoch: 7 [2304/9494]	Loss: 0.5956	LR: 0.100000
Training Epoch: 7 [2560/9494]	Loss: 0.6115	LR: 0.100000
Training Epoch: 7 [2816/9494]	Loss: 0.6048	LR: 0.100000
Training Epoch: 7 [3072/9494]	Loss: 0.5787	LR: 0.100000
Training Epoch: 7 [3328/9494]	Loss: 0.6520	LR: 0.100000
Training Epoch: 7 [3584/9494]	Loss: 0.6028	LR: 0.100000
Training Epoch: 7 [3840/9494]	Loss: 0.6051	LR: 0.100000
Training Epoch: 7 [4096/9494]	Loss: 0.6041	LR: 0.100000
Training Epoch: 7 [4352/9494]	Loss: 0.6321	LR: 0.100000
Training Epoch: 7 [4608/9494]	Loss: 0.5879	LR: 0.100000
Training Epoch: 7 [4864/9494]	Loss: 0.6180	LR: 0.100000
Training Epoch: 7 [5120/9494]	Loss: 0.5695	LR: 0.100000
Training Epoch: 7 [5376/9494]	Loss: 0.5592	LR: 0.100000
Training Epoch: 7 [5632/9494]	Loss: 0.5733	LR: 0.100000
Training Epoch: 7 [5888/9494]	Loss: 0.5776	LR: 0.100000
Training Epoch: 7 [6144/9494]	Loss: 0.5747	LR: 0.100000
Training Epoch: 7 [6400/9494]	Loss: 0.6570	LR: 0.100000
Training Epoch: 7 [6656/9494]	Loss: 0.5050	LR: 0.100000
Training Epoch: 7 [6912/9494]	Loss: 0.5766	LR: 0.100000
Training Epoch: 7 [7168/9494]	Loss: 0.5635	LR: 0.100000
Training Epoch: 7 [7424/9494]	Loss: 0.5878	LR: 0.100000
Training Epoch: 7 [7680/9494]	Loss: 0.6011	LR: 0.100000
Training Epoch: 7 [7936/9494]	Loss: 0.6222	LR: 0.100000
Training Epoch: 7 [8192/9494]	Loss: 0.6304	LR: 0.100000
Training Epoch: 7 [8448/9494]	Loss: 0.5530	LR: 0.100000
Training Epoch: 7 [8704/9494]	Loss: 0.5853	LR: 0.100000
Training Epoch: 7 [8960/9494]	Loss: 0.6311	LR: 0.100000
Training Epoch: 7 [9216/9494]	Loss: 0.6009	LR: 0.100000
Training Epoch: 7 [9472/9494]	Loss: 0.5433	LR: 0.100000
Training Epoch: 7 [9494/9494]	Loss: 0.7500	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6012, Train Accuracy: 0.6798
Epoch 7 training time consumed: 137.25s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0031, Accuracy: 0.5937, Time consumed:8.18s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-7-best.pth
Training Epoch: 8 [256/9494]	Loss: 0.5640	LR: 0.100000
Training Epoch: 8 [512/9494]	Loss: 0.7013	LR: 0.100000
Training Epoch: 8 [768/9494]	Loss: 0.6698	LR: 0.100000
Training Epoch: 8 [1024/9494]	Loss: 0.6149	LR: 0.100000
Training Epoch: 8 [1280/9494]	Loss: 0.6328	LR: 0.100000
Training Epoch: 8 [1536/9494]	Loss: 0.6295	LR: 0.100000
Training Epoch: 8 [1792/9494]	Loss: 0.6160	LR: 0.100000
Training Epoch: 8 [2048/9494]	Loss: 0.6582	LR: 0.100000
Training Epoch: 8 [2304/9494]	Loss: 0.6881	LR: 0.100000
Training Epoch: 8 [2560/9494]	Loss: 0.6351	LR: 0.100000
Training Epoch: 8 [2816/9494]	Loss: 0.6002	LR: 0.100000
Training Epoch: 8 [3072/9494]	Loss: 0.6120	LR: 0.100000
Training Epoch: 8 [3328/9494]	Loss: 0.5982	LR: 0.100000
Training Epoch: 8 [3584/9494]	Loss: 0.5999	LR: 0.100000
Training Epoch: 8 [3840/9494]	Loss: 0.6357	LR: 0.100000
Training Epoch: 8 [4096/9494]	Loss: 0.5572	LR: 0.100000
Training Epoch: 8 [4352/9494]	Loss: 0.5731	LR: 0.100000
Training Epoch: 8 [4608/9494]	Loss: 0.5978	LR: 0.100000
Training Epoch: 8 [4864/9494]	Loss: 0.6054	LR: 0.100000
Training Epoch: 8 [5120/9494]	Loss: 0.5828	LR: 0.100000
Training Epoch: 8 [5376/9494]	Loss: 0.6053	LR: 0.100000
Training Epoch: 8 [5632/9494]	Loss: 0.5169	LR: 0.100000
Training Epoch: 8 [5888/9494]	Loss: 0.5942	LR: 0.100000
Training Epoch: 8 [6144/9494]	Loss: 0.6096	LR: 0.100000
Training Epoch: 8 [6400/9494]	Loss: 0.5307	LR: 0.100000
Training Epoch: 8 [6656/9494]	Loss: 0.6362	LR: 0.100000
Training Epoch: 8 [6912/9494]	Loss: 0.5809	LR: 0.100000
Training Epoch: 8 [7168/9494]	Loss: 0.5373	LR: 0.100000
Training Epoch: 8 [7424/9494]	Loss: 0.5275	LR: 0.100000
Training Epoch: 8 [7680/9494]	Loss: 0.5326	LR: 0.100000
Training Epoch: 8 [7936/9494]	Loss: 0.5965	LR: 0.100000
Training Epoch: 8 [8192/9494]	Loss: 0.5254	LR: 0.100000
Training Epoch: 8 [8448/9494]	Loss: 0.5260	LR: 0.100000
Training Epoch: 8 [8704/9494]	Loss: 0.5569	LR: 0.100000
Training Epoch: 8 [8960/9494]	Loss: 0.5653	LR: 0.100000
Training Epoch: 8 [9216/9494]	Loss: 0.5371	LR: 0.100000
Training Epoch: 8 [9472/9494]	Loss: 0.5347	LR: 0.100000
Training Epoch: 8 [9494/9494]	Loss: 0.5465	LR: 0.100000
Epoch 8 - Average Train Loss: 0.5914, Train Accuracy: 0.6884
Epoch 8 training time consumed: 137.37s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0036, Accuracy: 0.5952, Time consumed:7.97s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-8-best.pth
Training Epoch: 9 [256/9494]	Loss: 0.5613	LR: 0.100000
Training Epoch: 9 [512/9494]	Loss: 0.6105	LR: 0.100000
Training Epoch: 9 [768/9494]	Loss: 0.6020	LR: 0.100000
Training Epoch: 9 [1024/9494]	Loss: 0.6007	LR: 0.100000
Training Epoch: 9 [1280/9494]	Loss: 0.5736	LR: 0.100000
Training Epoch: 9 [1536/9494]	Loss: 0.6020	LR: 0.100000
Training Epoch: 9 [1792/9494]	Loss: 0.5836	LR: 0.100000
Training Epoch: 9 [2048/9494]	Loss: 0.5501	LR: 0.100000
Training Epoch: 9 [2304/9494]	Loss: 0.5226	LR: 0.100000
Training Epoch: 9 [2560/9494]	Loss: 0.5217	LR: 0.100000
Training Epoch: 9 [2816/9494]	Loss: 0.5333	LR: 0.100000
Training Epoch: 9 [3072/9494]	Loss: 0.5343	LR: 0.100000
Training Epoch: 9 [3328/9494]	Loss: 0.5172	LR: 0.100000
Training Epoch: 9 [3584/9494]	Loss: 0.5357	LR: 0.100000
Training Epoch: 9 [3840/9494]	Loss: 0.5737	LR: 0.100000
Training Epoch: 9 [4096/9494]	Loss: 0.5815	LR: 0.100000
Training Epoch: 9 [4352/9494]	Loss: 0.5025	LR: 0.100000
Training Epoch: 9 [4608/9494]	Loss: 0.5129	LR: 0.100000
Training Epoch: 9 [4864/9494]	Loss: 0.4940	LR: 0.100000
Training Epoch: 9 [5120/9494]	Loss: 0.5029	LR: 0.100000
Training Epoch: 9 [5376/9494]	Loss: 0.4689	LR: 0.100000
Training Epoch: 9 [5632/9494]	Loss: 0.5472	LR: 0.100000
Training Epoch: 9 [5888/9494]	Loss: 0.5232	LR: 0.100000
Training Epoch: 9 [6144/9494]	Loss: 0.5283	LR: 0.100000
Training Epoch: 9 [6400/9494]	Loss: 0.4604	LR: 0.100000
Training Epoch: 9 [6656/9494]	Loss: 0.4331	LR: 0.100000
Training Epoch: 9 [6912/9494]	Loss: 0.4414	LR: 0.100000
Training Epoch: 9 [7168/9494]	Loss: 0.4814	LR: 0.100000
Training Epoch: 9 [7424/9494]	Loss: 0.5115	LR: 0.100000
Training Epoch: 9 [7680/9494]	Loss: 0.4513	LR: 0.100000
Training Epoch: 9 [7936/9494]	Loss: 0.4816	LR: 0.100000
Training Epoch: 9 [8192/9494]	Loss: 0.4663	LR: 0.100000
Training Epoch: 9 [8448/9494]	Loss: 0.5372	LR: 0.100000
Training Epoch: 9 [8704/9494]	Loss: 0.4871	LR: 0.100000
Training Epoch: 9 [8960/9494]	Loss: 0.5504	LR: 0.100000
Training Epoch: 9 [9216/9494]	Loss: 0.5382	LR: 0.100000
Training Epoch: 9 [9472/9494]	Loss: 0.4574	LR: 0.100000
Training Epoch: 9 [9494/9494]	Loss: 0.4230	LR: 0.100000
Epoch 9 - Average Train Loss: 0.5236, Train Accuracy: 0.7472
Epoch 9 training time consumed: 137.67s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0050, Accuracy: 0.5550, Time consumed:7.93s
Training Epoch: 10 [256/9494]	Loss: 0.5385	LR: 0.020000
Training Epoch: 10 [512/9494]	Loss: 0.5566	LR: 0.020000
Training Epoch: 10 [768/9494]	Loss: 0.4931	LR: 0.020000
Training Epoch: 10 [1024/9494]	Loss: 0.5305	LR: 0.020000
Training Epoch: 10 [1280/9494]	Loss: 0.5157	LR: 0.020000
Training Epoch: 10 [1536/9494]	Loss: 0.4238	LR: 0.020000
Training Epoch: 10 [1792/9494]	Loss: 0.4491	LR: 0.020000
Training Epoch: 10 [2048/9494]	Loss: 0.4538	LR: 0.020000
Training Epoch: 10 [2304/9494]	Loss: 0.4517	LR: 0.020000
Training Epoch: 10 [2560/9494]	Loss: 0.4541	LR: 0.020000
Training Epoch: 10 [2816/9494]	Loss: 0.4173	LR: 0.020000
Training Epoch: 10 [3072/9494]	Loss: 0.4246	LR: 0.020000
Training Epoch: 10 [3328/9494]	Loss: 0.4425	LR: 0.020000
Training Epoch: 10 [3584/9494]	Loss: 0.4751	LR: 0.020000
Training Epoch: 10 [3840/9494]	Loss: 0.4128	LR: 0.020000
Training Epoch: 10 [4096/9494]	Loss: 0.3728	LR: 0.020000
Training Epoch: 10 [4352/9494]	Loss: 0.5072	LR: 0.020000
Training Epoch: 10 [4608/9494]	Loss: 0.4610	LR: 0.020000
Training Epoch: 10 [4864/9494]	Loss: 0.4370	LR: 0.020000
Training Epoch: 10 [5120/9494]	Loss: 0.4642	LR: 0.020000
Training Epoch: 10 [5376/9494]	Loss: 0.4645	LR: 0.020000
Training Epoch: 10 [5632/9494]	Loss: 0.4588	LR: 0.020000
Training Epoch: 10 [5888/9494]	Loss: 0.4463	LR: 0.020000
Training Epoch: 10 [6144/9494]	Loss: 0.4480	LR: 0.020000
Training Epoch: 10 [6400/9494]	Loss: 0.4384	LR: 0.020000
Training Epoch: 10 [6656/9494]	Loss: 0.4264	LR: 0.020000
Training Epoch: 10 [6912/9494]	Loss: 0.4070	LR: 0.020000
Training Epoch: 10 [7168/9494]	Loss: 0.3717	LR: 0.020000
Training Epoch: 10 [7424/9494]	Loss: 0.3939	LR: 0.020000
Training Epoch: 10 [7680/9494]	Loss: 0.3966	LR: 0.020000
Training Epoch: 10 [7936/9494]	Loss: 0.4349	LR: 0.020000
Training Epoch: 10 [8192/9494]	Loss: 0.3938	LR: 0.020000
Training Epoch: 10 [8448/9494]	Loss: 0.4304	LR: 0.020000
Training Epoch: 10 [8704/9494]	Loss: 0.3556	LR: 0.020000
Training Epoch: 10 [8960/9494]	Loss: 0.3341	LR: 0.020000
Training Epoch: 10 [9216/9494]	Loss: 0.4519	LR: 0.020000
Training Epoch: 10 [9472/9494]	Loss: 0.3857	LR: 0.020000
Training Epoch: 10 [9494/9494]	Loss: 0.5417	LR: 0.020000
Epoch 10 - Average Train Loss: 0.4413, Train Accuracy: 0.7982
Epoch 10 training time consumed: 137.48s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0017, Accuracy: 0.8228, Time consumed:7.91s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-10-best.pth
Training Epoch: 11 [256/9494]	Loss: 0.4303	LR: 0.020000
Training Epoch: 11 [512/9494]	Loss: 0.3591	LR: 0.020000
Training Epoch: 11 [768/9494]	Loss: 0.4594	LR: 0.020000
Training Epoch: 11 [1024/9494]	Loss: 0.4073	LR: 0.020000
Training Epoch: 11 [1280/9494]	Loss: 0.4101	LR: 0.020000
Training Epoch: 11 [1536/9494]	Loss: 0.4407	LR: 0.020000
Training Epoch: 11 [1792/9494]	Loss: 0.3585	LR: 0.020000
Training Epoch: 11 [2048/9494]	Loss: 0.3926	LR: 0.020000
Training Epoch: 11 [2304/9494]	Loss: 0.4079	LR: 0.020000
Training Epoch: 11 [2560/9494]	Loss: 0.3657	LR: 0.020000
Training Epoch: 11 [2816/9494]	Loss: 0.4416	LR: 0.020000
Training Epoch: 11 [3072/9494]	Loss: 0.4037	LR: 0.020000
Training Epoch: 11 [3328/9494]	Loss: 0.4268	LR: 0.020000
Training Epoch: 11 [3584/9494]	Loss: 0.4094	LR: 0.020000
Training Epoch: 11 [3840/9494]	Loss: 0.3955	LR: 0.020000
Training Epoch: 11 [4096/9494]	Loss: 0.4106	LR: 0.020000
Training Epoch: 11 [4352/9494]	Loss: 0.3920	LR: 0.020000
Training Epoch: 11 [4608/9494]	Loss: 0.4505	LR: 0.020000
Training Epoch: 11 [4864/9494]	Loss: 0.4112	LR: 0.020000
Training Epoch: 11 [5120/9494]	Loss: 0.4332	LR: 0.020000
Training Epoch: 11 [5376/9494]	Loss: 0.3819	LR: 0.020000
Training Epoch: 11 [5632/9494]	Loss: 0.3662	LR: 0.020000
Training Epoch: 11 [5888/9494]	Loss: 0.3485	LR: 0.020000
Training Epoch: 11 [6144/9494]	Loss: 0.3863	LR: 0.020000
Training Epoch: 11 [6400/9494]	Loss: 0.3791	LR: 0.020000
Training Epoch: 11 [6656/9494]	Loss: 0.4482	LR: 0.020000
Training Epoch: 11 [6912/9494]	Loss: 0.4279	LR: 0.020000
Training Epoch: 11 [7168/9494]	Loss: 0.3620	LR: 0.020000
Training Epoch: 11 [7424/9494]	Loss: 0.4396	LR: 0.020000
Training Epoch: 11 [7680/9494]	Loss: 0.3984	LR: 0.020000
Training Epoch: 11 [7936/9494]	Loss: 0.4271	LR: 0.020000
Training Epoch: 11 [8192/9494]	Loss: 0.4173	LR: 0.020000
Training Epoch: 11 [8448/9494]	Loss: 0.3794	LR: 0.020000
Training Epoch: 11 [8704/9494]	Loss: 0.4202	LR: 0.020000
Training Epoch: 11 [8960/9494]	Loss: 0.4650	LR: 0.020000
Training Epoch: 11 [9216/9494]	Loss: 0.4550	LR: 0.020000
Training Epoch: 11 [9472/9494]	Loss: 0.3201	LR: 0.020000
Training Epoch: 11 [9494/9494]	Loss: 0.3881	LR: 0.020000
Epoch 11 - Average Train Loss: 0.4061, Train Accuracy: 0.8173
Epoch 11 training time consumed: 136.97s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0017, Accuracy: 0.8426, Time consumed:7.98s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-11-best.pth
Training Epoch: 12 [256/9494]	Loss: 0.3760	LR: 0.020000
Training Epoch: 12 [512/9494]	Loss: 0.4435	LR: 0.020000
Training Epoch: 12 [768/9494]	Loss: 0.3651	LR: 0.020000
Training Epoch: 12 [1024/9494]	Loss: 0.3229	LR: 0.020000
Training Epoch: 12 [1280/9494]	Loss: 0.3945	LR: 0.020000
Training Epoch: 12 [1536/9494]	Loss: 0.3645	LR: 0.020000
Training Epoch: 12 [1792/9494]	Loss: 0.3702	LR: 0.020000
Training Epoch: 12 [2048/9494]	Loss: 0.3498	LR: 0.020000
Training Epoch: 12 [2304/9494]	Loss: 0.3362	LR: 0.020000
Training Epoch: 12 [2560/9494]	Loss: 0.3597	LR: 0.020000
Training Epoch: 12 [2816/9494]	Loss: 0.3522	LR: 0.020000
Training Epoch: 12 [3072/9494]	Loss: 0.3333	LR: 0.020000
Training Epoch: 12 [3328/9494]	Loss: 0.3880	LR: 0.020000
Training Epoch: 12 [3584/9494]	Loss: 0.3618	LR: 0.020000
Training Epoch: 12 [3840/9494]	Loss: 0.4260	LR: 0.020000
Training Epoch: 12 [4096/9494]	Loss: 0.3904	LR: 0.020000
Training Epoch: 12 [4352/9494]	Loss: 0.3892	LR: 0.020000
Training Epoch: 12 [4608/9494]	Loss: 0.3684	LR: 0.020000
Training Epoch: 12 [4864/9494]	Loss: 0.3293	LR: 0.020000
Training Epoch: 12 [5120/9494]	Loss: 0.3716	LR: 0.020000
Training Epoch: 12 [5376/9494]	Loss: 0.3464	LR: 0.020000
Training Epoch: 12 [5632/9494]	Loss: 0.3614	LR: 0.020000
Training Epoch: 12 [5888/9494]	Loss: 0.3028	LR: 0.020000
Training Epoch: 12 [6144/9494]	Loss: 0.3781	LR: 0.020000
Training Epoch: 12 [6400/9494]	Loss: 0.4183	LR: 0.020000
Training Epoch: 12 [6656/9494]	Loss: 0.4386	LR: 0.020000
Training Epoch: 12 [6912/9494]	Loss: 0.3345	LR: 0.020000
Training Epoch: 12 [7168/9494]	Loss: 0.4279	LR: 0.020000
Training Epoch: 12 [7424/9494]	Loss: 0.3880	LR: 0.020000
Training Epoch: 12 [7680/9494]	Loss: 0.2904	LR: 0.020000
Training Epoch: 12 [7936/9494]	Loss: 0.3889	LR: 0.020000
Training Epoch: 12 [8192/9494]	Loss: 0.4106	LR: 0.020000
Training Epoch: 12 [8448/9494]	Loss: 0.3834	LR: 0.020000
Training Epoch: 12 [8704/9494]	Loss: 0.4002	LR: 0.020000
Training Epoch: 12 [8960/9494]	Loss: 0.4488	LR: 0.020000
Training Epoch: 12 [9216/9494]	Loss: 0.3820	LR: 0.020000
Training Epoch: 12 [9472/9494]	Loss: 0.3585	LR: 0.020000
Training Epoch: 12 [9494/9494]	Loss: 0.1520	LR: 0.020000
Epoch 12 - Average Train Loss: 0.3739, Train Accuracy: 0.8347
Epoch 12 training time consumed: 137.24s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0017, Accuracy: 0.8392, Time consumed:8.06s
Training Epoch: 13 [256/9494]	Loss: 0.3360	LR: 0.020000
Training Epoch: 13 [512/9494]	Loss: 0.2986	LR: 0.020000
Training Epoch: 13 [768/9494]	Loss: 0.3248	LR: 0.020000
Training Epoch: 13 [1024/9494]	Loss: 0.3491	LR: 0.020000
Training Epoch: 13 [1280/9494]	Loss: 0.3204	LR: 0.020000
Training Epoch: 13 [1536/9494]	Loss: 0.3250	LR: 0.020000
Training Epoch: 13 [1792/9494]	Loss: 0.3612	LR: 0.020000
Training Epoch: 13 [2048/9494]	Loss: 0.3387	LR: 0.020000
Training Epoch: 13 [2304/9494]	Loss: 0.3553	LR: 0.020000
Training Epoch: 13 [2560/9494]	Loss: 0.3078	LR: 0.020000
Training Epoch: 13 [2816/9494]	Loss: 0.3815	LR: 0.020000
Training Epoch: 13 [3072/9494]	Loss: 0.2832	LR: 0.020000
Training Epoch: 13 [3328/9494]	Loss: 0.3569	LR: 0.020000
Training Epoch: 13 [3584/9494]	Loss: 0.3175	LR: 0.020000
Training Epoch: 13 [3840/9494]	Loss: 0.3257	LR: 0.020000
Training Epoch: 13 [4096/9494]	Loss: 0.3508	LR: 0.020000
Training Epoch: 13 [4352/9494]	Loss: 0.3699	LR: 0.020000
Training Epoch: 13 [4608/9494]	Loss: 0.3548	LR: 0.020000
Training Epoch: 13 [4864/9494]	Loss: 0.3340	LR: 0.020000
Training Epoch: 13 [5120/9494]	Loss: 0.4357	LR: 0.020000
Training Epoch: 13 [5376/9494]	Loss: 0.3290	LR: 0.020000
Training Epoch: 13 [5632/9494]	Loss: 0.3751	LR: 0.020000
Training Epoch: 13 [5888/9494]	Loss: 0.3357	LR: 0.020000
Training Epoch: 13 [6144/9494]	Loss: 0.3412	LR: 0.020000
Training Epoch: 13 [6400/9494]	Loss: 0.2779	LR: 0.020000
Training Epoch: 13 [6656/9494]	Loss: 0.3789	LR: 0.020000
Training Epoch: 13 [6912/9494]	Loss: 0.3381	LR: 0.020000
Training Epoch: 13 [7168/9494]	Loss: 0.2819	LR: 0.020000
Training Epoch: 13 [7424/9494]	Loss: 0.3715	LR: 0.020000
Training Epoch: 13 [7680/9494]	Loss: 0.3456	LR: 0.020000
Training Epoch: 13 [7936/9494]	Loss: 0.3890	LR: 0.020000
Training Epoch: 13 [8192/9494]	Loss: 0.2596	LR: 0.020000
Training Epoch: 13 [8448/9494]	Loss: 0.3262	LR: 0.020000
Training Epoch: 13 [8704/9494]	Loss: 0.3774	LR: 0.020000
Training Epoch: 13 [8960/9494]	Loss: 0.3808	LR: 0.020000
Training Epoch: 13 [9216/9494]	Loss: 0.3216	LR: 0.020000
Training Epoch: 13 [9472/9494]	Loss: 0.3176	LR: 0.020000
Training Epoch: 13 [9494/9494]	Loss: 0.6081	LR: 0.020000
Epoch 13 - Average Train Loss: 0.3405, Train Accuracy: 0.8526
Epoch 13 training time consumed: 137.17s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0018, Accuracy: 0.8223, Time consumed:8.08s
Training Epoch: 14 [256/9494]	Loss: 0.3770	LR: 0.020000
Training Epoch: 14 [512/9494]	Loss: 0.4383	LR: 0.020000
Training Epoch: 14 [768/9494]	Loss: 0.4053	LR: 0.020000
Training Epoch: 14 [1024/9494]	Loss: 0.4239	LR: 0.020000
Training Epoch: 14 [1280/9494]	Loss: 0.4485	LR: 0.020000
Training Epoch: 14 [1536/9494]	Loss: 0.3623	LR: 0.020000
Training Epoch: 14 [1792/9494]	Loss: 0.3774	LR: 0.020000
Training Epoch: 14 [2048/9494]	Loss: 0.4125	LR: 0.020000
Training Epoch: 14 [2304/9494]	Loss: 0.3897	LR: 0.020000
Training Epoch: 14 [2560/9494]	Loss: 0.4347	LR: 0.020000
Training Epoch: 14 [2816/9494]	Loss: 0.3558	LR: 0.020000
Training Epoch: 14 [3072/9494]	Loss: 0.3560	LR: 0.020000
Training Epoch: 14 [3328/9494]	Loss: 0.3007	LR: 0.020000
Training Epoch: 14 [3584/9494]	Loss: 0.3534	LR: 0.020000
Training Epoch: 14 [3840/9494]	Loss: 0.3343	LR: 0.020000
Training Epoch: 14 [4096/9494]	Loss: 0.3652	LR: 0.020000
Training Epoch: 14 [4352/9494]	Loss: 0.3079	LR: 0.020000
Training Epoch: 14 [4608/9494]	Loss: 0.3793	LR: 0.020000
Training Epoch: 14 [4864/9494]	Loss: 0.3317	LR: 0.020000
Training Epoch: 14 [5120/9494]	Loss: 0.3620	LR: 0.020000
Training Epoch: 14 [5376/9494]	Loss: 0.3754	LR: 0.020000
Training Epoch: 14 [5632/9494]	Loss: 0.3547	LR: 0.020000
Training Epoch: 14 [5888/9494]	Loss: 0.3345	LR: 0.020000
Training Epoch: 14 [6144/9494]	Loss: 0.3219	LR: 0.020000
Training Epoch: 14 [6400/9494]	Loss: 0.3462	LR: 0.020000
Training Epoch: 14 [6656/9494]	Loss: 0.3323	LR: 0.020000
Training Epoch: 14 [6912/9494]	Loss: 0.3802	LR: 0.020000
Training Epoch: 14 [7168/9494]	Loss: 0.3359	LR: 0.020000
Training Epoch: 14 [7424/9494]	Loss: 0.2899	LR: 0.020000
Training Epoch: 14 [7680/9494]	Loss: 0.3293	LR: 0.020000
Training Epoch: 14 [7936/9494]	Loss: 0.3227	LR: 0.020000
Training Epoch: 14 [8192/9494]	Loss: 0.3066	LR: 0.020000
Training Epoch: 14 [8448/9494]	Loss: 0.3626	LR: 0.020000
Training Epoch: 14 [8704/9494]	Loss: 0.3293	LR: 0.020000
Training Epoch: 14 [8960/9494]	Loss: 0.2536	LR: 0.020000
Training Epoch: 14 [9216/9494]	Loss: 0.3026	LR: 0.020000
Training Epoch: 14 [9472/9494]	Loss: 0.3185	LR: 0.020000
Training Epoch: 14 [9494/9494]	Loss: 0.2181	LR: 0.020000
Epoch 14 - Average Train Loss: 0.3541, Train Accuracy: 0.8472
Epoch 14 training time consumed: 137.01s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0016, Accuracy: 0.8528, Time consumed:7.97s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-14-best.pth
Training Epoch: 15 [256/9494]	Loss: 0.3264	LR: 0.020000
Training Epoch: 15 [512/9494]	Loss: 0.2711	LR: 0.020000
Training Epoch: 15 [768/9494]	Loss: 0.2783	LR: 0.020000
Training Epoch: 15 [1024/9494]	Loss: 0.3073	LR: 0.020000
Training Epoch: 15 [1280/9494]	Loss: 0.3092	LR: 0.020000
Training Epoch: 15 [1536/9494]	Loss: 0.2723	LR: 0.020000
Training Epoch: 15 [1792/9494]	Loss: 0.2902	LR: 0.020000
Training Epoch: 15 [2048/9494]	Loss: 0.2917	LR: 0.020000
Training Epoch: 15 [2304/9494]	Loss: 0.4369	LR: 0.020000
Training Epoch: 15 [2560/9494]	Loss: 0.2618	LR: 0.020000
Training Epoch: 15 [2816/9494]	Loss: 0.2727	LR: 0.020000
Training Epoch: 15 [3072/9494]	Loss: 0.2888	LR: 0.020000
Training Epoch: 15 [3328/9494]	Loss: 0.4089	LR: 0.020000
Training Epoch: 15 [3584/9494]	Loss: 0.2507	LR: 0.020000
Training Epoch: 15 [3840/9494]	Loss: 0.3678	LR: 0.020000
Training Epoch: 15 [4096/9494]	Loss: 0.3229	LR: 0.020000
Training Epoch: 15 [4352/9494]	Loss: 0.2965	LR: 0.020000
Training Epoch: 15 [4608/9494]	Loss: 0.3300	LR: 0.020000
Training Epoch: 15 [4864/9494]	Loss: 0.2660	LR: 0.020000
Training Epoch: 15 [5120/9494]	Loss: 0.3597	LR: 0.020000
Training Epoch: 15 [5376/9494]	Loss: 0.2653	LR: 0.020000
Training Epoch: 15 [5632/9494]	Loss: 0.2670	LR: 0.020000
Training Epoch: 15 [5888/9494]	Loss: 0.2859	LR: 0.020000
Training Epoch: 15 [6144/9494]	Loss: 0.3271	LR: 0.020000
Training Epoch: 15 [6400/9494]	Loss: 0.2574	LR: 0.020000
Training Epoch: 15 [6656/9494]	Loss: 0.3415	LR: 0.020000
Training Epoch: 15 [6912/9494]	Loss: 0.2879	LR: 0.020000
Training Epoch: 15 [7168/9494]	Loss: 0.2799	LR: 0.020000
Training Epoch: 15 [7424/9494]	Loss: 0.3582	LR: 0.020000
Training Epoch: 15 [7680/9494]	Loss: 0.3142	LR: 0.020000
Training Epoch: 15 [7936/9494]	Loss: 0.2663	LR: 0.020000
Training Epoch: 15 [8192/9494]	Loss: 0.2310	LR: 0.020000
Training Epoch: 15 [8448/9494]	Loss: 0.2430	LR: 0.020000
Training Epoch: 15 [8704/9494]	Loss: 0.2888	LR: 0.020000
Training Epoch: 15 [8960/9494]	Loss: 0.3280	LR: 0.020000
Training Epoch: 15 [9216/9494]	Loss: 0.3328	LR: 0.020000
Training Epoch: 15 [9472/9494]	Loss: 0.2450	LR: 0.020000
Training Epoch: 15 [9494/9494]	Loss: 0.1953	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3005, Train Accuracy: 0.8718
Epoch 15 training time consumed: 137.03s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0014, Accuracy: 0.8634, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-15-best.pth
Training Epoch: 16 [256/9494]	Loss: 0.3251	LR: 0.020000
Training Epoch: 16 [512/9494]	Loss: 0.2604	LR: 0.020000
Training Epoch: 16 [768/9494]	Loss: 0.2210	LR: 0.020000
Training Epoch: 16 [1024/9494]	Loss: 0.2106	LR: 0.020000
Training Epoch: 16 [1280/9494]	Loss: 0.3181	LR: 0.020000
Training Epoch: 16 [1536/9494]	Loss: 0.2425	LR: 0.020000
Training Epoch: 16 [1792/9494]	Loss: 0.2699	LR: 0.020000
Training Epoch: 16 [2048/9494]	Loss: 0.2375	LR: 0.020000
Training Epoch: 16 [2304/9494]	Loss: 0.3147	LR: 0.020000
Training Epoch: 16 [2560/9494]	Loss: 0.2694	LR: 0.020000
Training Epoch: 16 [2816/9494]	Loss: 0.2751	LR: 0.020000
Training Epoch: 16 [3072/9494]	Loss: 0.2238	LR: 0.020000
Training Epoch: 16 [3328/9494]	Loss: 0.2655	LR: 0.020000
Training Epoch: 16 [3584/9494]	Loss: 0.3317	LR: 0.020000
Training Epoch: 16 [3840/9494]	Loss: 0.2677	LR: 0.020000
Training Epoch: 16 [4096/9494]	Loss: 0.2788	LR: 0.020000
Training Epoch: 16 [4352/9494]	Loss: 0.2493	LR: 0.020000
Training Epoch: 16 [4608/9494]	Loss: 0.2443	LR: 0.020000
Training Epoch: 16 [4864/9494]	Loss: 0.2406	LR: 0.020000
Training Epoch: 16 [5120/9494]	Loss: 0.2623	LR: 0.020000
Training Epoch: 16 [5376/9494]	Loss: 0.2131	LR: 0.020000
Training Epoch: 16 [5632/9494]	Loss: 0.2698	LR: 0.020000
Training Epoch: 16 [5888/9494]	Loss: 0.2423	LR: 0.020000
Training Epoch: 16 [6144/9494]	Loss: 0.2799	LR: 0.020000
Training Epoch: 16 [6400/9494]	Loss: 0.2645	LR: 0.020000
Training Epoch: 16 [6656/9494]	Loss: 0.2919	LR: 0.020000
Training Epoch: 16 [6912/9494]	Loss: 0.3122	LR: 0.020000
Training Epoch: 16 [7168/9494]	Loss: 0.2853	LR: 0.020000
Training Epoch: 16 [7424/9494]	Loss: 0.2859	LR: 0.020000
Training Epoch: 16 [7680/9494]	Loss: 0.3641	LR: 0.020000
Training Epoch: 16 [7936/9494]	Loss: 0.3241	LR: 0.020000
Training Epoch: 16 [8192/9494]	Loss: 0.2852	LR: 0.020000
Training Epoch: 16 [8448/9494]	Loss: 0.2819	LR: 0.020000
Training Epoch: 16 [8704/9494]	Loss: 0.2127	LR: 0.020000
Training Epoch: 16 [8960/9494]	Loss: 0.2649	LR: 0.020000
Training Epoch: 16 [9216/9494]	Loss: 0.2698	LR: 0.020000
Training Epoch: 16 [9472/9494]	Loss: 0.3448	LR: 0.020000
Training Epoch: 16 [9494/9494]	Loss: 0.2011	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2728, Train Accuracy: 0.8841
Epoch 16 training time consumed: 136.74s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0011, Accuracy: 0.8915, Time consumed:7.96s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-16-best.pth
Training Epoch: 17 [256/9494]	Loss: 0.2980	LR: 0.020000
Training Epoch: 17 [512/9494]	Loss: 0.2102	LR: 0.020000
Training Epoch: 17 [768/9494]	Loss: 0.2620	LR: 0.020000
Training Epoch: 17 [1024/9494]	Loss: 0.2268	LR: 0.020000
Training Epoch: 17 [1280/9494]	Loss: 0.2738	LR: 0.020000
Training Epoch: 17 [1536/9494]	Loss: 0.2671	LR: 0.020000
Training Epoch: 17 [1792/9494]	Loss: 0.2537	LR: 0.020000
Training Epoch: 17 [2048/9494]	Loss: 0.3097	LR: 0.020000
Training Epoch: 17 [2304/9494]	Loss: 0.2398	LR: 0.020000
Training Epoch: 17 [2560/9494]	Loss: 0.2353	LR: 0.020000
Training Epoch: 17 [2816/9494]	Loss: 0.2437	LR: 0.020000
Training Epoch: 17 [3072/9494]	Loss: 0.2186	LR: 0.020000
Training Epoch: 17 [3328/9494]	Loss: 0.2251	LR: 0.020000
Training Epoch: 17 [3584/9494]	Loss: 0.2798	LR: 0.020000
Training Epoch: 17 [3840/9494]	Loss: 0.3023	LR: 0.020000
Training Epoch: 17 [4096/9494]	Loss: 0.3036	LR: 0.020000
Training Epoch: 17 [4352/9494]	Loss: 0.1906	LR: 0.020000
Training Epoch: 17 [4608/9494]	Loss: 0.3144	LR: 0.020000
Training Epoch: 17 [4864/9494]	Loss: 0.2555	LR: 0.020000
Training Epoch: 17 [5120/9494]	Loss: 0.2332	LR: 0.020000
Training Epoch: 17 [5376/9494]	Loss: 0.2388	LR: 0.020000
Training Epoch: 17 [5632/9494]	Loss: 0.2227	LR: 0.020000
Training Epoch: 17 [5888/9494]	Loss: 0.2097	LR: 0.020000
Training Epoch: 17 [6144/9494]	Loss: 0.2675	LR: 0.020000
Training Epoch: 17 [6400/9494]	Loss: 0.3178	LR: 0.020000
Training Epoch: 17 [6656/9494]	Loss: 0.2667	LR: 0.020000
Training Epoch: 17 [6912/9494]	Loss: 0.2710	LR: 0.020000
Training Epoch: 17 [7168/9494]	Loss: 0.2696	LR: 0.020000
Training Epoch: 17 [7424/9494]	Loss: 0.2923	LR: 0.020000
Training Epoch: 17 [7680/9494]	Loss: 0.2604	LR: 0.020000
Training Epoch: 17 [7936/9494]	Loss: 0.2399	LR: 0.020000
Training Epoch: 17 [8192/9494]	Loss: 0.3123	LR: 0.020000
Training Epoch: 17 [8448/9494]	Loss: 0.2798	LR: 0.020000
Training Epoch: 17 [8704/9494]	Loss: 0.2868	LR: 0.020000
Training Epoch: 17 [8960/9494]	Loss: 0.3023	LR: 0.020000
Training Epoch: 17 [9216/9494]	Loss: 0.2639	LR: 0.020000
Training Epoch: 17 [9472/9494]	Loss: 0.2092	LR: 0.020000
Training Epoch: 17 [9494/9494]	Loss: 0.3033	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2610, Train Accuracy: 0.8911
Epoch 17 training time consumed: 137.67s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0011, Accuracy: 0.8896, Time consumed:8.26s
Training Epoch: 18 [256/9494]	Loss: 0.2498	LR: 0.020000
Training Epoch: 18 [512/9494]	Loss: 0.2771	LR: 0.020000
Training Epoch: 18 [768/9494]	Loss: 0.2614	LR: 0.020000
Training Epoch: 18 [1024/9494]	Loss: 0.3252	LR: 0.020000
Training Epoch: 18 [1280/9494]	Loss: 0.2585	LR: 0.020000
Training Epoch: 18 [1536/9494]	Loss: 0.2537	LR: 0.020000
Training Epoch: 18 [1792/9494]	Loss: 0.2997	LR: 0.020000
Training Epoch: 18 [2048/9494]	Loss: 0.2337	LR: 0.020000
Training Epoch: 18 [2304/9494]	Loss: 0.2315	LR: 0.020000
Training Epoch: 18 [2560/9494]	Loss: 0.2737	LR: 0.020000
Training Epoch: 18 [2816/9494]	Loss: 0.3257	LR: 0.020000
Training Epoch: 18 [3072/9494]	Loss: 0.2753	LR: 0.020000
Training Epoch: 18 [3328/9494]	Loss: 0.2422	LR: 0.020000
Training Epoch: 18 [3584/9494]	Loss: 0.2350	LR: 0.020000
Training Epoch: 18 [3840/9494]	Loss: 0.2187	LR: 0.020000
Training Epoch: 18 [4096/9494]	Loss: 0.2113	LR: 0.020000
Training Epoch: 18 [4352/9494]	Loss: 0.2287	LR: 0.020000
Training Epoch: 18 [4608/9494]	Loss: 0.2001	LR: 0.020000
Training Epoch: 18 [4864/9494]	Loss: 0.2426	LR: 0.020000
Training Epoch: 18 [5120/9494]	Loss: 0.1988	LR: 0.020000
Training Epoch: 18 [5376/9494]	Loss: 0.1857	LR: 0.020000
Training Epoch: 18 [5632/9494]	Loss: 0.2299	LR: 0.020000
Training Epoch: 18 [5888/9494]	Loss: 0.2349	LR: 0.020000
Training Epoch: 18 [6144/9494]	Loss: 0.3406	LR: 0.020000
Training Epoch: 18 [6400/9494]	Loss: 0.2409	LR: 0.020000
Training Epoch: 18 [6656/9494]	Loss: 0.2266	LR: 0.020000
Training Epoch: 18 [6912/9494]	Loss: 0.2102	LR: 0.020000
Training Epoch: 18 [7168/9494]	Loss: 0.2138	LR: 0.020000
Training Epoch: 18 [7424/9494]	Loss: 0.2160	LR: 0.020000
Training Epoch: 18 [7680/9494]	Loss: 0.2500	LR: 0.020000
Training Epoch: 18 [7936/9494]	Loss: 0.2426	LR: 0.020000
Training Epoch: 18 [8192/9494]	Loss: 0.2460	LR: 0.020000
Training Epoch: 18 [8448/9494]	Loss: 0.1998	LR: 0.020000
Training Epoch: 18 [8704/9494]	Loss: 0.2593	LR: 0.020000
Training Epoch: 18 [8960/9494]	Loss: 0.2263	LR: 0.020000
Training Epoch: 18 [9216/9494]	Loss: 0.2313	LR: 0.020000
Training Epoch: 18 [9472/9494]	Loss: 0.2140	LR: 0.020000
Training Epoch: 18 [9494/9494]	Loss: 0.1845	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2434, Train Accuracy: 0.8992
Epoch 18 training time consumed: 137.97s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0017, Accuracy: 0.8586, Time consumed:8.20s
Training Epoch: 19 [256/9494]	Loss: 0.1744	LR: 0.020000
Training Epoch: 19 [512/9494]	Loss: 0.3289	LR: 0.020000
Training Epoch: 19 [768/9494]	Loss: 0.2485	LR: 0.020000
Training Epoch: 19 [1024/9494]	Loss: 0.2480	LR: 0.020000
Training Epoch: 19 [1280/9494]	Loss: 0.2226	LR: 0.020000
Training Epoch: 19 [1536/9494]	Loss: 0.2320	LR: 0.020000
Training Epoch: 19 [1792/9494]	Loss: 0.1868	LR: 0.020000
Training Epoch: 19 [2048/9494]	Loss: 0.3130	LR: 0.020000
Training Epoch: 19 [2304/9494]	Loss: 0.1956	LR: 0.020000
Training Epoch: 19 [2560/9494]	Loss: 0.2485	LR: 0.020000
Training Epoch: 19 [2816/9494]	Loss: 0.2051	LR: 0.020000
Training Epoch: 19 [3072/9494]	Loss: 0.2347	LR: 0.020000
Training Epoch: 19 [3328/9494]	Loss: 0.1932	LR: 0.020000
Training Epoch: 19 [3584/9494]	Loss: 0.1882	LR: 0.020000
Training Epoch: 19 [3840/9494]	Loss: 0.2285	LR: 0.020000
Training Epoch: 19 [4096/9494]	Loss: 0.2671	LR: 0.020000
Training Epoch: 19 [4352/9494]	Loss: 0.2471	LR: 0.020000
Training Epoch: 19 [4608/9494]	Loss: 0.2184	LR: 0.020000
Training Epoch: 19 [4864/9494]	Loss: 0.1683	LR: 0.020000
Training Epoch: 19 [5120/9494]	Loss: 0.2385	LR: 0.020000
Training Epoch: 19 [5376/9494]	Loss: 0.1904	LR: 0.020000
Training Epoch: 19 [5632/9494]	Loss: 0.1715	LR: 0.020000
Training Epoch: 19 [5888/9494]	Loss: 0.2513	LR: 0.020000
Training Epoch: 19 [6144/9494]	Loss: 0.2097	LR: 0.020000
Training Epoch: 19 [6400/9494]	Loss: 0.1872	LR: 0.020000
Training Epoch: 19 [6656/9494]	Loss: 0.2911	LR: 0.020000
Training Epoch: 19 [6912/9494]	Loss: 0.1955	LR: 0.020000
Training Epoch: 19 [7168/9494]	Loss: 0.2106	LR: 0.020000
Training Epoch: 19 [7424/9494]	Loss: 0.1948	LR: 0.020000
Training Epoch: 19 [7680/9494]	Loss: 0.1636	LR: 0.020000
Training Epoch: 19 [7936/9494]	Loss: 0.2161	LR: 0.020000
Training Epoch: 19 [8192/9494]	Loss: 0.1909	LR: 0.020000
Training Epoch: 19 [8448/9494]	Loss: 0.2046	LR: 0.020000
Training Epoch: 19 [8704/9494]	Loss: 0.2024	LR: 0.020000
Training Epoch: 19 [8960/9494]	Loss: 0.2660	LR: 0.020000
Training Epoch: 19 [9216/9494]	Loss: 0.2056	LR: 0.020000
Training Epoch: 19 [9472/9494]	Loss: 0.1860	LR: 0.020000
Training Epoch: 19 [9494/9494]	Loss: 0.1007	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2193, Train Accuracy: 0.9089
Epoch 19 training time consumed: 137.46s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0010, Accuracy: 0.9075, Time consumed:8.18s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-19-best.pth
Training Epoch: 20 [256/9494]	Loss: 0.1929	LR: 0.004000
Training Epoch: 20 [512/9494]	Loss: 0.1991	LR: 0.004000
Training Epoch: 20 [768/9494]	Loss: 0.1964	LR: 0.004000
Training Epoch: 20 [1024/9494]	Loss: 0.2369	LR: 0.004000
Training Epoch: 20 [1280/9494]	Loss: 0.1824	LR: 0.004000
Training Epoch: 20 [1536/9494]	Loss: 0.2033	LR: 0.004000
Training Epoch: 20 [1792/9494]	Loss: 0.1841	LR: 0.004000
Training Epoch: 20 [2048/9494]	Loss: 0.1938	LR: 0.004000
Training Epoch: 20 [2304/9494]	Loss: 0.1754	LR: 0.004000
Training Epoch: 20 [2560/9494]	Loss: 0.2057	LR: 0.004000
Training Epoch: 20 [2816/9494]	Loss: 0.2239	LR: 0.004000
Training Epoch: 20 [3072/9494]	Loss: 0.1888	LR: 0.004000
Training Epoch: 20 [3328/9494]	Loss: 0.2022	LR: 0.004000
Training Epoch: 20 [3584/9494]	Loss: 0.2320	LR: 0.004000
Training Epoch: 20 [3840/9494]	Loss: 0.1759	LR: 0.004000
Training Epoch: 20 [4096/9494]	Loss: 0.1614	LR: 0.004000
Training Epoch: 20 [4352/9494]	Loss: 0.2136	LR: 0.004000
Training Epoch: 20 [4608/9494]	Loss: 0.2636	LR: 0.004000
Training Epoch: 20 [4864/9494]	Loss: 0.1530	LR: 0.004000
Training Epoch: 20 [5120/9494]	Loss: 0.1795	LR: 0.004000
Training Epoch: 20 [5376/9494]	Loss: 0.1968	LR: 0.004000
Training Epoch: 20 [5632/9494]	Loss: 0.2052	LR: 0.004000
Training Epoch: 20 [5888/9494]	Loss: 0.1534	LR: 0.004000
Training Epoch: 20 [6144/9494]	Loss: 0.1724	LR: 0.004000
Training Epoch: 20 [6400/9494]	Loss: 0.1823	LR: 0.004000
Training Epoch: 20 [6656/9494]	Loss: 0.2133	LR: 0.004000
Training Epoch: 20 [6912/9494]	Loss: 0.1645	LR: 0.004000
Training Epoch: 20 [7168/9494]	Loss: 0.1914	LR: 0.004000
Training Epoch: 20 [7424/9494]	Loss: 0.1976	LR: 0.004000
Training Epoch: 20 [7680/9494]	Loss: 0.2065	LR: 0.004000
Training Epoch: 20 [7936/9494]	Loss: 0.1854	LR: 0.004000
Training Epoch: 20 [8192/9494]	Loss: 0.1820	LR: 0.004000
Training Epoch: 20 [8448/9494]	Loss: 0.1420	LR: 0.004000
Training Epoch: 20 [8704/9494]	Loss: 0.1653	LR: 0.004000
Training Epoch: 20 [8960/9494]	Loss: 0.1540	LR: 0.004000
Training Epoch: 20 [9216/9494]	Loss: 0.1874	LR: 0.004000
Training Epoch: 20 [9472/9494]	Loss: 0.1350	LR: 0.004000
Training Epoch: 20 [9494/9494]	Loss: 0.0448	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1888, Train Accuracy: 0.9225
Epoch 20 training time consumed: 137.57s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0007, Accuracy: 0.9366, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-20-best.pth
Training Epoch: 21 [256/9494]	Loss: 0.2089	LR: 0.004000
Training Epoch: 21 [512/9494]	Loss: 0.1530	LR: 0.004000
Training Epoch: 21 [768/9494]	Loss: 0.1668	LR: 0.004000
Training Epoch: 21 [1024/9494]	Loss: 0.1684	LR: 0.004000
Training Epoch: 21 [1280/9494]	Loss: 0.1500	LR: 0.004000
Training Epoch: 21 [1536/9494]	Loss: 0.1725	LR: 0.004000
Training Epoch: 21 [1792/9494]	Loss: 0.1515	LR: 0.004000
Training Epoch: 21 [2048/9494]	Loss: 0.1588	LR: 0.004000
Training Epoch: 21 [2304/9494]	Loss: 0.1884	LR: 0.004000
Training Epoch: 21 [2560/9494]	Loss: 0.2000	LR: 0.004000
Training Epoch: 21 [2816/9494]	Loss: 0.1498	LR: 0.004000
Training Epoch: 21 [3072/9494]	Loss: 0.1732	LR: 0.004000
Training Epoch: 21 [3328/9494]	Loss: 0.1922	LR: 0.004000
Training Epoch: 21 [3584/9494]	Loss: 0.2045	LR: 0.004000
Training Epoch: 21 [3840/9494]	Loss: 0.1752	LR: 0.004000
Training Epoch: 21 [4096/9494]	Loss: 0.1615	LR: 0.004000
Training Epoch: 21 [4352/9494]	Loss: 0.1689	LR: 0.004000
Training Epoch: 21 [4608/9494]	Loss: 0.1583	LR: 0.004000
Training Epoch: 21 [4864/9494]	Loss: 0.1490	LR: 0.004000
Training Epoch: 21 [5120/9494]	Loss: 0.1637	LR: 0.004000
Training Epoch: 21 [5376/9494]	Loss: 0.1585	LR: 0.004000
Training Epoch: 21 [5632/9494]	Loss: 0.1970	LR: 0.004000
Training Epoch: 21 [5888/9494]	Loss: 0.2136	LR: 0.004000
Training Epoch: 21 [6144/9494]	Loss: 0.1499	LR: 0.004000
Training Epoch: 21 [6400/9494]	Loss: 0.1553	LR: 0.004000
Training Epoch: 21 [6656/9494]	Loss: 0.1697	LR: 0.004000
Training Epoch: 21 [6912/9494]	Loss: 0.1506	LR: 0.004000
Training Epoch: 21 [7168/9494]	Loss: 0.1296	LR: 0.004000
Training Epoch: 21 [7424/9494]	Loss: 0.1711	LR: 0.004000
Training Epoch: 21 [7680/9494]	Loss: 0.2433	LR: 0.004000
Training Epoch: 21 [7936/9494]	Loss: 0.1705	LR: 0.004000
Training Epoch: 21 [8192/9494]	Loss: 0.1715	LR: 0.004000
Training Epoch: 21 [8448/9494]	Loss: 0.1455	LR: 0.004000
Training Epoch: 21 [8704/9494]	Loss: 0.1543	LR: 0.004000
Training Epoch: 21 [8960/9494]	Loss: 0.1628	LR: 0.004000
Training Epoch: 21 [9216/9494]	Loss: 0.1843	LR: 0.004000
Training Epoch: 21 [9472/9494]	Loss: 0.1902	LR: 0.004000
Training Epoch: 21 [9494/9494]	Loss: 0.1793	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1712, Train Accuracy: 0.9295
Epoch 21 training time consumed: 137.65s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0007, Accuracy: 0.9278, Time consumed:8.09s
Training Epoch: 22 [256/9494]	Loss: 0.1547	LR: 0.004000
Training Epoch: 22 [512/9494]	Loss: 0.1884	LR: 0.004000
Training Epoch: 22 [768/9494]	Loss: 0.1710	LR: 0.004000
Training Epoch: 22 [1024/9494]	Loss: 0.1600	LR: 0.004000
Training Epoch: 22 [1280/9494]	Loss: 0.2364	LR: 0.004000
Training Epoch: 22 [1536/9494]	Loss: 0.2383	LR: 0.004000
Training Epoch: 22 [1792/9494]	Loss: 0.1368	LR: 0.004000
Training Epoch: 22 [2048/9494]	Loss: 0.1893	LR: 0.004000
Training Epoch: 22 [2304/9494]	Loss: 0.1850	LR: 0.004000
Training Epoch: 22 [2560/9494]	Loss: 0.2562	LR: 0.004000
Training Epoch: 22 [2816/9494]	Loss: 0.1883	LR: 0.004000
Training Epoch: 22 [3072/9494]	Loss: 0.1929	LR: 0.004000
Training Epoch: 22 [3328/9494]	Loss: 0.1772	LR: 0.004000
Training Epoch: 22 [3584/9494]	Loss: 0.1646	LR: 0.004000
Training Epoch: 22 [3840/9494]	Loss: 0.1812	LR: 0.004000
Training Epoch: 22 [4096/9494]	Loss: 0.1769	LR: 0.004000
Training Epoch: 22 [4352/9494]	Loss: 0.1642	LR: 0.004000
Training Epoch: 22 [4608/9494]	Loss: 0.1817	LR: 0.004000
Training Epoch: 22 [4864/9494]	Loss: 0.1640	LR: 0.004000
Training Epoch: 22 [5120/9494]	Loss: 0.2273	LR: 0.004000
Training Epoch: 22 [5376/9494]	Loss: 0.1662	LR: 0.004000
Training Epoch: 22 [5632/9494]	Loss: 0.1585	LR: 0.004000
Training Epoch: 22 [5888/9494]	Loss: 0.1937	LR: 0.004000
Training Epoch: 22 [6144/9494]	Loss: 0.1400	LR: 0.004000
Training Epoch: 22 [6400/9494]	Loss: 0.1934	LR: 0.004000
Training Epoch: 22 [6656/9494]	Loss: 0.2267	LR: 0.004000
Training Epoch: 22 [6912/9494]	Loss: 0.1583	LR: 0.004000
Training Epoch: 22 [7168/9494]	Loss: 0.1469	LR: 0.004000
Training Epoch: 22 [7424/9494]	Loss: 0.1699	LR: 0.004000
Training Epoch: 22 [7680/9494]	Loss: 0.1851	LR: 0.004000
Training Epoch: 22 [7936/9494]	Loss: 0.1672	LR: 0.004000
Training Epoch: 22 [8192/9494]	Loss: 0.1944	LR: 0.004000
Training Epoch: 22 [8448/9494]	Loss: 0.1679	LR: 0.004000
Training Epoch: 22 [8704/9494]	Loss: 0.1612	LR: 0.004000
Training Epoch: 22 [8960/9494]	Loss: 0.1303	LR: 0.004000
Training Epoch: 22 [9216/9494]	Loss: 0.1662	LR: 0.004000
Training Epoch: 22 [9472/9494]	Loss: 0.1623	LR: 0.004000
Training Epoch: 22 [9494/9494]	Loss: 0.0925	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1788, Train Accuracy: 0.9283
Epoch 22 training time consumed: 137.67s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0007, Accuracy: 0.9346, Time consumed:8.20s
Training Epoch: 23 [256/9494]	Loss: 0.1582	LR: 0.004000
Training Epoch: 23 [512/9494]	Loss: 0.2006	LR: 0.004000
Training Epoch: 23 [768/9494]	Loss: 0.1681	LR: 0.004000
Training Epoch: 23 [1024/9494]	Loss: 0.1110	LR: 0.004000
Training Epoch: 23 [1280/9494]	Loss: 0.1242	LR: 0.004000
Training Epoch: 23 [1536/9494]	Loss: 0.1797	LR: 0.004000
Training Epoch: 23 [1792/9494]	Loss: 0.2023	LR: 0.004000
Training Epoch: 23 [2048/9494]	Loss: 0.1823	LR: 0.004000
Training Epoch: 23 [2304/9494]	Loss: 0.1779	LR: 0.004000
Training Epoch: 23 [2560/9494]	Loss: 0.1941	LR: 0.004000
Training Epoch: 23 [2816/9494]	Loss: 0.2014	LR: 0.004000
Training Epoch: 23 [3072/9494]	Loss: 0.1462	LR: 0.004000
Training Epoch: 23 [3328/9494]	Loss: 0.2165	LR: 0.004000
Training Epoch: 23 [3584/9494]	Loss: 0.1816	LR: 0.004000
Training Epoch: 23 [3840/9494]	Loss: 0.1538	LR: 0.004000
Training Epoch: 23 [4096/9494]	Loss: 0.1508	LR: 0.004000
Training Epoch: 23 [4352/9494]	Loss: 0.1644	LR: 0.004000
Training Epoch: 23 [4608/9494]	Loss: 0.1139	LR: 0.004000
Training Epoch: 23 [4864/9494]	Loss: 0.1889	LR: 0.004000
Training Epoch: 23 [5120/9494]	Loss: 0.1704	LR: 0.004000
Training Epoch: 23 [5376/9494]	Loss: 0.1161	LR: 0.004000
Training Epoch: 23 [5632/9494]	Loss: 0.2147	LR: 0.004000
Training Epoch: 23 [5888/9494]	Loss: 0.1773	LR: 0.004000
Training Epoch: 23 [6144/9494]	Loss: 0.1424	LR: 0.004000
Training Epoch: 23 [6400/9494]	Loss: 0.1267	LR: 0.004000
Training Epoch: 23 [6656/9494]	Loss: 0.1569	LR: 0.004000
Training Epoch: 23 [6912/9494]	Loss: 0.1535	LR: 0.004000
Training Epoch: 23 [7168/9494]	Loss: 0.1181	LR: 0.004000
Training Epoch: 23 [7424/9494]	Loss: 0.1820	LR: 0.004000
Training Epoch: 23 [7680/9494]	Loss: 0.1348	LR: 0.004000
Training Epoch: 23 [7936/9494]	Loss: 0.1468	LR: 0.004000
Training Epoch: 23 [8192/9494]	Loss: 0.1362	LR: 0.004000
Training Epoch: 23 [8448/9494]	Loss: 0.1587	LR: 0.004000
Training Epoch: 23 [8704/9494]	Loss: 0.1871	LR: 0.004000
Training Epoch: 23 [8960/9494]	Loss: 0.1612	LR: 0.004000
Training Epoch: 23 [9216/9494]	Loss: 0.1452	LR: 0.004000
Training Epoch: 23 [9472/9494]	Loss: 0.1671	LR: 0.004000
Training Epoch: 23 [9494/9494]	Loss: 0.0790	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1623, Train Accuracy: 0.9359
Epoch 23 training time consumed: 137.32s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0007, Accuracy: 0.9337, Time consumed:8.15s
Training Epoch: 24 [256/9494]	Loss: 0.1186	LR: 0.004000
Training Epoch: 24 [512/9494]	Loss: 0.1316	LR: 0.004000
Training Epoch: 24 [768/9494]	Loss: 0.1272	LR: 0.004000
Training Epoch: 24 [1024/9494]	Loss: 0.1486	LR: 0.004000
Training Epoch: 24 [1280/9494]	Loss: 0.1610	LR: 0.004000
Training Epoch: 24 [1536/9494]	Loss: 0.1881	LR: 0.004000
Training Epoch: 24 [1792/9494]	Loss: 0.1827	LR: 0.004000
Training Epoch: 24 [2048/9494]	Loss: 0.1773	LR: 0.004000
Training Epoch: 24 [2304/9494]	Loss: 0.1957	LR: 0.004000
Training Epoch: 24 [2560/9494]	Loss: 0.1551	LR: 0.004000
Training Epoch: 24 [2816/9494]	Loss: 0.1571	LR: 0.004000
Training Epoch: 24 [3072/9494]	Loss: 0.1928	LR: 0.004000
Training Epoch: 24 [3328/9494]	Loss: 0.1302	LR: 0.004000
Training Epoch: 24 [3584/9494]	Loss: 0.1185	LR: 0.004000
Training Epoch: 24 [3840/9494]	Loss: 0.2220	LR: 0.004000
Training Epoch: 24 [4096/9494]	Loss: 0.1778	LR: 0.004000
Training Epoch: 24 [4352/9494]	Loss: 0.1625	LR: 0.004000
Training Epoch: 24 [4608/9494]	Loss: 0.2030	LR: 0.004000
Training Epoch: 24 [4864/9494]	Loss: 0.1740	LR: 0.004000
Training Epoch: 24 [5120/9494]	Loss: 0.1962	LR: 0.004000
Training Epoch: 24 [5376/9494]	Loss: 0.1724	LR: 0.004000
Training Epoch: 24 [5632/9494]	Loss: 0.1480	LR: 0.004000
Training Epoch: 24 [5888/9494]	Loss: 0.1668	LR: 0.004000
Training Epoch: 24 [6144/9494]	Loss: 0.1473	LR: 0.004000
Training Epoch: 24 [6400/9494]	Loss: 0.2149	LR: 0.004000
Training Epoch: 24 [6656/9494]	Loss: 0.1730	LR: 0.004000
Training Epoch: 24 [6912/9494]	Loss: 0.1711	LR: 0.004000
Training Epoch: 24 [7168/9494]	Loss: 0.1695	LR: 0.004000
Training Epoch: 24 [7424/9494]	Loss: 0.1615	LR: 0.004000
Training Epoch: 24 [7680/9494]	Loss: 0.1582	LR: 0.004000
Training Epoch: 24 [7936/9494]	Loss: 0.1377	LR: 0.004000
Training Epoch: 24 [8192/9494]	Loss: 0.1527	LR: 0.004000
Training Epoch: 24 [8448/9494]	Loss: 0.1563	LR: 0.004000
Training Epoch: 24 [8704/9494]	Loss: 0.2380	LR: 0.004000
Training Epoch: 24 [8960/9494]	Loss: 0.1272	LR: 0.004000
Training Epoch: 24 [9216/9494]	Loss: 0.1279	LR: 0.004000
Training Epoch: 24 [9472/9494]	Loss: 0.1656	LR: 0.004000
Training Epoch: 24 [9494/9494]	Loss: 0.0570	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1648, Train Accuracy: 0.9354
Epoch 24 training time consumed: 137.64s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0007, Accuracy: 0.9395, Time consumed:8.17s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-24-best.pth
Training Epoch: 25 [256/9494]	Loss: 0.1632	LR: 0.004000
Training Epoch: 25 [512/9494]	Loss: 0.1495	LR: 0.004000
Training Epoch: 25 [768/9494]	Loss: 0.1894	LR: 0.004000
Training Epoch: 25 [1024/9494]	Loss: 0.1157	LR: 0.004000
Training Epoch: 25 [1280/9494]	Loss: 0.1573	LR: 0.004000
Training Epoch: 25 [1536/9494]	Loss: 0.1438	LR: 0.004000
Training Epoch: 25 [1792/9494]	Loss: 0.1418	LR: 0.004000
Training Epoch: 25 [2048/9494]	Loss: 0.1521	LR: 0.004000
Training Epoch: 25 [2304/9494]	Loss: 0.1818	LR: 0.004000
Training Epoch: 25 [2560/9494]	Loss: 0.1114	LR: 0.004000
Training Epoch: 25 [2816/9494]	Loss: 0.1829	LR: 0.004000
Training Epoch: 25 [3072/9494]	Loss: 0.1511	LR: 0.004000
Training Epoch: 25 [3328/9494]	Loss: 0.1228	LR: 0.004000
Training Epoch: 25 [3584/9494]	Loss: 0.1392	LR: 0.004000
Training Epoch: 25 [3840/9494]	Loss: 0.1823	LR: 0.004000
Training Epoch: 25 [4096/9494]	Loss: 0.1556	LR: 0.004000
Training Epoch: 25 [4352/9494]	Loss: 0.1094	LR: 0.004000
Training Epoch: 25 [4608/9494]	Loss: 0.1748	LR: 0.004000
Training Epoch: 25 [4864/9494]	Loss: 0.0884	LR: 0.004000
Training Epoch: 25 [5120/9494]	Loss: 0.1644	LR: 0.004000
Training Epoch: 25 [5376/9494]	Loss: 0.1267	LR: 0.004000
Training Epoch: 25 [5632/9494]	Loss: 0.1645	LR: 0.004000
Training Epoch: 25 [5888/9494]	Loss: 0.1855	LR: 0.004000
Training Epoch: 25 [6144/9494]	Loss: 0.1509	LR: 0.004000
Training Epoch: 25 [6400/9494]	Loss: 0.1334	LR: 0.004000
Training Epoch: 25 [6656/9494]	Loss: 0.1552	LR: 0.004000
Training Epoch: 25 [6912/9494]	Loss: 0.1472	LR: 0.004000
Training Epoch: 25 [7168/9494]	Loss: 0.1401	LR: 0.004000
Training Epoch: 25 [7424/9494]	Loss: 0.1746	LR: 0.004000
Training Epoch: 25 [7680/9494]	Loss: 0.1124	LR: 0.004000
Training Epoch: 25 [7936/9494]	Loss: 0.1108	LR: 0.004000
Training Epoch: 25 [8192/9494]	Loss: 0.1397	LR: 0.004000
Training Epoch: 25 [8448/9494]	Loss: 0.1626	LR: 0.004000
Training Epoch: 25 [8704/9494]	Loss: 0.2406	LR: 0.004000
Training Epoch: 25 [8960/9494]	Loss: 0.1926	LR: 0.004000
Training Epoch: 25 [9216/9494]	Loss: 0.1676	LR: 0.004000
Training Epoch: 25 [9472/9494]	Loss: 0.1819	LR: 0.004000
Training Epoch: 25 [9494/9494]	Loss: 0.2640	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1533, Train Accuracy: 0.9350
Epoch 25 training time consumed: 137.46s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0007, Accuracy: 0.9370, Time consumed:7.91s
Training Epoch: 26 [256/9494]	Loss: 0.1656	LR: 0.004000
Training Epoch: 26 [512/9494]	Loss: 0.1599	LR: 0.004000
Training Epoch: 26 [768/9494]	Loss: 0.1675	LR: 0.004000
Training Epoch: 26 [1024/9494]	Loss: 0.1829	LR: 0.004000
Training Epoch: 26 [1280/9494]	Loss: 0.1507	LR: 0.004000
Training Epoch: 26 [1536/9494]	Loss: 0.1629	LR: 0.004000
Training Epoch: 26 [1792/9494]	Loss: 0.1724	LR: 0.004000
Training Epoch: 26 [2048/9494]	Loss: 0.1631	LR: 0.004000
Training Epoch: 26 [2304/9494]	Loss: 0.1228	LR: 0.004000
Training Epoch: 26 [2560/9494]	Loss: 0.1403	LR: 0.004000
Training Epoch: 26 [2816/9494]	Loss: 0.2211	LR: 0.004000
Training Epoch: 26 [3072/9494]	Loss: 0.1333	LR: 0.004000
Training Epoch: 26 [3328/9494]	Loss: 0.1918	LR: 0.004000
Training Epoch: 26 [3584/9494]	Loss: 0.1463	LR: 0.004000
Training Epoch: 26 [3840/9494]	Loss: 0.1467	LR: 0.004000
Training Epoch: 26 [4096/9494]	Loss: 0.1165	LR: 0.004000
Training Epoch: 26 [4352/9494]	Loss: 0.1369	LR: 0.004000
Training Epoch: 26 [4608/9494]	Loss: 0.2036	LR: 0.004000
Training Epoch: 26 [4864/9494]	Loss: 0.1213	LR: 0.004000
Training Epoch: 26 [5120/9494]	Loss: 0.1264	LR: 0.004000
Training Epoch: 26 [5376/9494]	Loss: 0.2160	LR: 0.004000
Training Epoch: 26 [5632/9494]	Loss: 0.1172	LR: 0.004000
Training Epoch: 26 [5888/9494]	Loss: 0.1431	LR: 0.004000
Training Epoch: 26 [6144/9494]	Loss: 0.1413	LR: 0.004000
Training Epoch: 26 [6400/9494]	Loss: 0.1312	LR: 0.004000
Training Epoch: 26 [6656/9494]	Loss: 0.1234	LR: 0.004000
Training Epoch: 26 [6912/9494]	Loss: 0.1453	LR: 0.004000
Training Epoch: 26 [7168/9494]	Loss: 0.1329	LR: 0.004000
Training Epoch: 26 [7424/9494]	Loss: 0.1558	LR: 0.004000
Training Epoch: 26 [7680/9494]	Loss: 0.1883	LR: 0.004000
Training Epoch: 26 [7936/9494]	Loss: 0.1687	LR: 0.004000
Training Epoch: 26 [8192/9494]	Loss: 0.1610	LR: 0.004000
Training Epoch: 26 [8448/9494]	Loss: 0.1398	LR: 0.004000
Training Epoch: 26 [8704/9494]	Loss: 0.1564	LR: 0.004000
Training Epoch: 26 [8960/9494]	Loss: 0.1463	LR: 0.004000
Training Epoch: 26 [9216/9494]	Loss: 0.1405	LR: 0.004000
Training Epoch: 26 [9472/9494]	Loss: 0.1543	LR: 0.004000
Training Epoch: 26 [9494/9494]	Loss: 0.0918	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1537, Train Accuracy: 0.9365
Epoch 26 training time consumed: 137.36s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9361, Time consumed:7.86s
Training Epoch: 27 [256/9494]	Loss: 0.1447	LR: 0.004000
Training Epoch: 27 [512/9494]	Loss: 0.1264	LR: 0.004000
Training Epoch: 27 [768/9494]	Loss: 0.1320	LR: 0.004000
Training Epoch: 27 [1024/9494]	Loss: 0.1575	LR: 0.004000
Training Epoch: 27 [1280/9494]	Loss: 0.1756	LR: 0.004000
Training Epoch: 27 [1536/9494]	Loss: 0.1062	LR: 0.004000
Training Epoch: 27 [1792/9494]	Loss: 0.1545	LR: 0.004000
Training Epoch: 27 [2048/9494]	Loss: 0.1531	LR: 0.004000
Training Epoch: 27 [2304/9494]	Loss: 0.1507	LR: 0.004000
Training Epoch: 27 [2560/9494]	Loss: 0.1809	LR: 0.004000
Training Epoch: 27 [2816/9494]	Loss: 0.1168	LR: 0.004000
Training Epoch: 27 [3072/9494]	Loss: 0.1791	LR: 0.004000
Training Epoch: 27 [3328/9494]	Loss: 0.1878	LR: 0.004000
Training Epoch: 27 [3584/9494]	Loss: 0.1908	LR: 0.004000
Training Epoch: 27 [3840/9494]	Loss: 0.1307	LR: 0.004000
Training Epoch: 27 [4096/9494]	Loss: 0.1255	LR: 0.004000
Training Epoch: 27 [4352/9494]	Loss: 0.1618	LR: 0.004000
Training Epoch: 27 [4608/9494]	Loss: 0.1509	LR: 0.004000
Training Epoch: 27 [4864/9494]	Loss: 0.1121	LR: 0.004000
Training Epoch: 27 [5120/9494]	Loss: 0.1660	LR: 0.004000
Training Epoch: 27 [5376/9494]	Loss: 0.1719	LR: 0.004000
Training Epoch: 27 [5632/9494]	Loss: 0.1748	LR: 0.004000
Training Epoch: 27 [5888/9494]	Loss: 0.1684	LR: 0.004000
Training Epoch: 27 [6144/9494]	Loss: 0.1972	LR: 0.004000
Training Epoch: 27 [6400/9494]	Loss: 0.1145	LR: 0.004000
Training Epoch: 27 [6656/9494]	Loss: 0.2083	LR: 0.004000
Training Epoch: 27 [6912/9494]	Loss: 0.1183	LR: 0.004000
Training Epoch: 27 [7168/9494]	Loss: 0.1378	LR: 0.004000
Training Epoch: 27 [7424/9494]	Loss: 0.1063	LR: 0.004000
Training Epoch: 27 [7680/9494]	Loss: 0.1685	LR: 0.004000
Training Epoch: 27 [7936/9494]	Loss: 0.1825	LR: 0.004000
Training Epoch: 27 [8192/9494]	Loss: 0.1190	LR: 0.004000
Training Epoch: 27 [8448/9494]	Loss: 0.1685	LR: 0.004000
Training Epoch: 27 [8704/9494]	Loss: 0.1857	LR: 0.004000
Training Epoch: 27 [8960/9494]	Loss: 0.1571	LR: 0.004000
Training Epoch: 27 [9216/9494]	Loss: 0.1565	LR: 0.004000
Training Epoch: 27 [9472/9494]	Loss: 0.1949	LR: 0.004000
Training Epoch: 27 [9494/9494]	Loss: 0.0202	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1546, Train Accuracy: 0.9369
Epoch 27 training time consumed: 136.96s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9375, Time consumed:8.11s
Training Epoch: 28 [256/9494]	Loss: 0.1264	LR: 0.004000
Training Epoch: 28 [512/9494]	Loss: 0.1485	LR: 0.004000
Training Epoch: 28 [768/9494]	Loss: 0.1480	LR: 0.004000
Training Epoch: 28 [1024/9494]	Loss: 0.1258	LR: 0.004000
Training Epoch: 28 [1280/9494]	Loss: 0.1643	LR: 0.004000
Training Epoch: 28 [1536/9494]	Loss: 0.1330	LR: 0.004000
Training Epoch: 28 [1792/9494]	Loss: 0.1132	LR: 0.004000
Training Epoch: 28 [2048/9494]	Loss: 0.1193	LR: 0.004000
Training Epoch: 28 [2304/9494]	Loss: 0.1506	LR: 0.004000
Training Epoch: 28 [2560/9494]	Loss: 0.2075	LR: 0.004000
Training Epoch: 28 [2816/9494]	Loss: 0.1359	LR: 0.004000
Training Epoch: 28 [3072/9494]	Loss: 0.1168	LR: 0.004000
Training Epoch: 28 [3328/9494]	Loss: 0.1479	LR: 0.004000
Training Epoch: 28 [3584/9494]	Loss: 0.1390	LR: 0.004000
Training Epoch: 28 [3840/9494]	Loss: 0.1612	LR: 0.004000
Training Epoch: 28 [4096/9494]	Loss: 0.1960	LR: 0.004000
Training Epoch: 28 [4352/9494]	Loss: 0.1155	LR: 0.004000
Training Epoch: 28 [4608/9494]	Loss: 0.1465	LR: 0.004000
Training Epoch: 28 [4864/9494]	Loss: 0.1365	LR: 0.004000
Training Epoch: 28 [5120/9494]	Loss: 0.1441	LR: 0.004000
Training Epoch: 28 [5376/9494]	Loss: 0.1467	LR: 0.004000
Training Epoch: 28 [5632/9494]	Loss: 0.1805	LR: 0.004000
Training Epoch: 28 [5888/9494]	Loss: 0.1264	LR: 0.004000
Training Epoch: 28 [6144/9494]	Loss: 0.2031	LR: 0.004000
Training Epoch: 28 [6400/9494]	Loss: 0.1546	LR: 0.004000
Training Epoch: 28 [6656/9494]	Loss: 0.1242	LR: 0.004000
Training Epoch: 28 [6912/9494]	Loss: 0.1510	LR: 0.004000
Training Epoch: 28 [7168/9494]	Loss: 0.1276	LR: 0.004000
Training Epoch: 28 [7424/9494]	Loss: 0.1635	LR: 0.004000
Training Epoch: 28 [7680/9494]	Loss: 0.1916	LR: 0.004000
Training Epoch: 28 [7936/9494]	Loss: 0.1709	LR: 0.004000
Training Epoch: 28 [8192/9494]	Loss: 0.1464	LR: 0.004000
Training Epoch: 28 [8448/9494]	Loss: 0.1195	LR: 0.004000
Training Epoch: 28 [8704/9494]	Loss: 0.1550	LR: 0.004000
Training Epoch: 28 [8960/9494]	Loss: 0.1301	LR: 0.004000
Training Epoch: 28 [9216/9494]	Loss: 0.2076	LR: 0.004000
Training Epoch: 28 [9472/9494]	Loss: 0.1392	LR: 0.004000
Training Epoch: 28 [9494/9494]	Loss: 0.0883	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1489, Train Accuracy: 0.9399
Epoch 28 training time consumed: 137.42s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0008, Accuracy: 0.9269, Time consumed:7.81s
Training Epoch: 29 [256/9494]	Loss: 0.1076	LR: 0.004000
Training Epoch: 29 [512/9494]	Loss: 0.1663	LR: 0.004000
Training Epoch: 29 [768/9494]	Loss: 0.1993	LR: 0.004000
Training Epoch: 29 [1024/9494]	Loss: 0.1498	LR: 0.004000
Training Epoch: 29 [1280/9494]	Loss: 0.1620	LR: 0.004000
Training Epoch: 29 [1536/9494]	Loss: 0.1540	LR: 0.004000
Training Epoch: 29 [1792/9494]	Loss: 0.1466	LR: 0.004000
Training Epoch: 29 [2048/9494]	Loss: 0.1295	LR: 0.004000
Training Epoch: 29 [2304/9494]	Loss: 0.1205	LR: 0.004000
Training Epoch: 29 [2560/9494]	Loss: 0.1315	LR: 0.004000
Training Epoch: 29 [2816/9494]	Loss: 0.1486	LR: 0.004000
Training Epoch: 29 [3072/9494]	Loss: 0.1808	LR: 0.004000
Training Epoch: 29 [3328/9494]	Loss: 0.1570	LR: 0.004000
Training Epoch: 29 [3584/9494]	Loss: 0.1860	LR: 0.004000
Training Epoch: 29 [3840/9494]	Loss: 0.1504	LR: 0.004000
Training Epoch: 29 [4096/9494]	Loss: 0.1366	LR: 0.004000
Training Epoch: 29 [4352/9494]	Loss: 0.1793	LR: 0.004000
Training Epoch: 29 [4608/9494]	Loss: 0.1508	LR: 0.004000
Training Epoch: 29 [4864/9494]	Loss: 0.1555	LR: 0.004000
Training Epoch: 29 [5120/9494]	Loss: 0.0907	LR: 0.004000
Training Epoch: 29 [5376/9494]	Loss: 0.1409	LR: 0.004000
Training Epoch: 29 [5632/9494]	Loss: 0.1418	LR: 0.004000
Training Epoch: 29 [5888/9494]	Loss: 0.1507	LR: 0.004000
Training Epoch: 29 [6144/9494]	Loss: 0.2306	LR: 0.004000
Training Epoch: 29 [6400/9494]	Loss: 0.1014	LR: 0.004000
Training Epoch: 29 [6656/9494]	Loss: 0.1296	LR: 0.004000
Training Epoch: 29 [6912/9494]	Loss: 0.1477	LR: 0.004000
Training Epoch: 29 [7168/9494]	Loss: 0.2021	LR: 0.004000
Training Epoch: 29 [7424/9494]	Loss: 0.1629	LR: 0.004000
Training Epoch: 29 [7680/9494]	Loss: 0.0957	LR: 0.004000
Training Epoch: 29 [7936/9494]	Loss: 0.1312	LR: 0.004000
Training Epoch: 29 [8192/9494]	Loss: 0.1272	LR: 0.004000
Training Epoch: 29 [8448/9494]	Loss: 0.1551	LR: 0.004000
Training Epoch: 29 [8704/9494]	Loss: 0.1346	LR: 0.004000
Training Epoch: 29 [8960/9494]	Loss: 0.0833	LR: 0.004000
Training Epoch: 29 [9216/9494]	Loss: 0.1375	LR: 0.004000
Training Epoch: 29 [9472/9494]	Loss: 0.1679	LR: 0.004000
Training Epoch: 29 [9494/9494]	Loss: 0.0243	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1468, Train Accuracy: 0.9393
Epoch 29 training time consumed: 137.12s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0008, Accuracy: 0.9264, Time consumed:8.04s
Training Epoch: 30 [256/9494]	Loss: 0.0912	LR: 0.004000
Training Epoch: 30 [512/9494]	Loss: 0.1290	LR: 0.004000
Training Epoch: 30 [768/9494]	Loss: 0.1477	LR: 0.004000
Training Epoch: 30 [1024/9494]	Loss: 0.1595	LR: 0.004000
Training Epoch: 30 [1280/9494]	Loss: 0.1686	LR: 0.004000
Training Epoch: 30 [1536/9494]	Loss: 0.0898	LR: 0.004000
Training Epoch: 30 [1792/9494]	Loss: 0.1146	LR: 0.004000
Training Epoch: 30 [2048/9494]	Loss: 0.1259	LR: 0.004000
Training Epoch: 30 [2304/9494]	Loss: 0.1166	LR: 0.004000
Training Epoch: 30 [2560/9494]	Loss: 0.1513	LR: 0.004000
Training Epoch: 30 [2816/9494]	Loss: 0.1987	LR: 0.004000
Training Epoch: 30 [3072/9494]	Loss: 0.1499	LR: 0.004000
Training Epoch: 30 [3328/9494]	Loss: 0.1106	LR: 0.004000
Training Epoch: 30 [3584/9494]	Loss: 0.1577	LR: 0.004000
Training Epoch: 30 [3840/9494]	Loss: 0.1685	LR: 0.004000
Training Epoch: 30 [4096/9494]	Loss: 0.1920	LR: 0.004000
Training Epoch: 30 [4352/9494]	Loss: 0.1424	LR: 0.004000
Training Epoch: 30 [4608/9494]	Loss: 0.1296	LR: 0.004000
Training Epoch: 30 [4864/9494]	Loss: 0.1360	LR: 0.004000
Training Epoch: 30 [5120/9494]	Loss: 0.1260	LR: 0.004000
Training Epoch: 30 [5376/9494]	Loss: 0.1334	LR: 0.004000
Training Epoch: 30 [5632/9494]	Loss: 0.1286	LR: 0.004000
Training Epoch: 30 [5888/9494]	Loss: 0.1428	LR: 0.004000
Training Epoch: 30 [6144/9494]	Loss: 0.0871	LR: 0.004000
Training Epoch: 30 [6400/9494]	Loss: 0.1605	LR: 0.004000
Training Epoch: 30 [6656/9494]	Loss: 0.1505	LR: 0.004000
Training Epoch: 30 [6912/9494]	Loss: 0.1452	LR: 0.004000
Training Epoch: 30 [7168/9494]	Loss: 0.1644	LR: 0.004000
Training Epoch: 30 [7424/9494]	Loss: 0.1822	LR: 0.004000
Training Epoch: 30 [7680/9494]	Loss: 0.1899	LR: 0.004000
Training Epoch: 30 [7936/9494]	Loss: 0.1729	LR: 0.004000
Training Epoch: 30 [8192/9494]	Loss: 0.1578	LR: 0.004000
Training Epoch: 30 [8448/9494]	Loss: 0.1402	LR: 0.004000
Training Epoch: 30 [8704/9494]	Loss: 0.1617	LR: 0.004000
Training Epoch: 30 [8960/9494]	Loss: 0.1191	LR: 0.004000
Training Epoch: 30 [9216/9494]	Loss: 0.1092	LR: 0.004000
Training Epoch: 30 [9472/9494]	Loss: 0.1951	LR: 0.004000
Training Epoch: 30 [9494/9494]	Loss: 0.3156	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1449, Train Accuracy: 0.9386
Epoch 30 training time consumed: 137.55s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9443, Time consumed:7.89s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_03h_43m_09s/ResNet18-MUCAC-seed5-ret100-30-best.pth
Training Epoch: 31 [256/9494]	Loss: 0.1649	LR: 0.004000
Training Epoch: 31 [512/9494]	Loss: 0.1241	LR: 0.004000
Training Epoch: 31 [768/9494]	Loss: 0.1445	LR: 0.004000
Training Epoch: 31 [1024/9494]	Loss: 0.1604	LR: 0.004000
Training Epoch: 31 [1280/9494]	Loss: 0.2391	LR: 0.004000
Training Epoch: 31 [1536/9494]	Loss: 0.1254	LR: 0.004000
Training Epoch: 31 [1792/9494]	Loss: 0.1440	LR: 0.004000
Training Epoch: 31 [2048/9494]	Loss: 0.1263	LR: 0.004000
Training Epoch: 31 [2304/9494]	Loss: 0.1521	LR: 0.004000
Training Epoch: 31 [2560/9494]	Loss: 0.1263	LR: 0.004000
Training Epoch: 31 [2816/9494]	Loss: 0.1519	LR: 0.004000
Training Epoch: 31 [3072/9494]	Loss: 0.1555	LR: 0.004000
Training Epoch: 31 [3328/9494]	Loss: 0.1085	LR: 0.004000
Training Epoch: 31 [3584/9494]	Loss: 0.1355	LR: 0.004000
Training Epoch: 31 [3840/9494]	Loss: 0.1710	LR: 0.004000
Training Epoch: 31 [4096/9494]	Loss: 0.1429	LR: 0.004000
Training Epoch: 31 [4352/9494]	Loss: 0.1294	LR: 0.004000
Training Epoch: 31 [4608/9494]	Loss: 0.1464	LR: 0.004000
Training Epoch: 31 [4864/9494]	Loss: 0.1342	LR: 0.004000
Training Epoch: 31 [5120/9494]	Loss: 0.1568	LR: 0.004000
Training Epoch: 31 [5376/9494]	Loss: 0.1193	LR: 0.004000
Training Epoch: 31 [5632/9494]	Loss: 0.1127	LR: 0.004000
Training Epoch: 31 [5888/9494]	Loss: 0.1741	LR: 0.004000
Training Epoch: 31 [6144/9494]	Loss: 0.1569	LR: 0.004000
Training Epoch: 31 [6400/9494]	Loss: 0.1541	LR: 0.004000
Training Epoch: 31 [6656/9494]	Loss: 0.1104	LR: 0.004000
Training Epoch: 31 [6912/9494]	Loss: 0.1506	LR: 0.004000
Training Epoch: 31 [7168/9494]	Loss: 0.1609	LR: 0.004000
Training Epoch: 31 [7424/9494]	Loss: 0.1301	LR: 0.004000
Training Epoch: 31 [7680/9494]	Loss: 0.0806	LR: 0.004000
Training Epoch: 31 [7936/9494]	Loss: 0.1763	LR: 0.004000
Training Epoch: 31 [8192/9494]	Loss: 0.1303	LR: 0.004000
Training Epoch: 31 [8448/9494]	Loss: 0.1602	LR: 0.004000
Training Epoch: 31 [8704/9494]	Loss: 0.1949	LR: 0.004000
Training Epoch: 31 [8960/9494]	Loss: 0.1370	LR: 0.004000
Training Epoch: 31 [9216/9494]	Loss: 0.1912	LR: 0.004000
Training Epoch: 31 [9472/9494]	Loss: 0.1212	LR: 0.004000
Training Epoch: 31 [9494/9494]	Loss: 0.2423	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1462, Train Accuracy: 0.9380
Epoch 31 training time consumed: 137.30s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0008, Accuracy: 0.9196, Time consumed:7.93s
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: 92.18495178222656
Retain Accuracy: 91.82771301269531
Zero-Retain Forget (ZRF): 0.7888602614402771
Membership Inference Attack (MIA): 0.33111954459203036
Forget vs Retain Membership Inference Attack (MIA): 0.518957345971564
Forget vs Test Membership Inference Attack (MIA): 0.5545023696682464
Test vs Retain Membership Inference Attack (MIA): 0.5363196125907991
Train vs Test Membership Inference Attack (MIA): 0.5169491525423728
Forget Set Accuracy (Df): 91.75520324707031
Method Execution Time: 5664.16 seconds
