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

📌 S Retain class distribution for seed 9:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 9:
Class 0: 527
Class 1: 527

📊 Updated class distribution:
Retain set:
  Class 0: 5679
  Class 1: 4605
Forget set:
  Class 0: 132
  Class 1: 132
./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img
./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img
⚠️ Warning: Retain train loader may not be shuffled.
Training Epoch: 1 [256/10284]	Loss: 0.6818	LR: 0.000000
Training Epoch: 1 [512/10284]	Loss: 0.7018	LR: 0.002439
Training Epoch: 1 [768/10284]	Loss: 0.6708	LR: 0.004878
Training Epoch: 1 [1024/10284]	Loss: 0.6998	LR: 0.007317
Training Epoch: 1 [1280/10284]	Loss: 0.7005	LR: 0.009756
Training Epoch: 1 [1536/10284]	Loss: 0.6967	LR: 0.012195
Training Epoch: 1 [1792/10284]	Loss: 0.6810	LR: 0.014634
Training Epoch: 1 [2048/10284]	Loss: 0.6757	LR: 0.017073
Training Epoch: 1 [2304/10284]	Loss: 0.6906	LR: 0.019512
Training Epoch: 1 [2560/10284]	Loss: 0.7546	LR: 0.021951
Training Epoch: 1 [2816/10284]	Loss: 0.8713	LR: 0.024390
Training Epoch: 1 [3072/10284]	Loss: 0.6794	LR: 0.026829
Training Epoch: 1 [3328/10284]	Loss: 0.7283	LR: 0.029268
Training Epoch: 1 [3584/10284]	Loss: 0.9395	LR: 0.031707
Training Epoch: 1 [3840/10284]	Loss: 1.7336	LR: 0.034146
Training Epoch: 1 [4096/10284]	Loss: 1.6314	LR: 0.036585
Training Epoch: 1 [4352/10284]	Loss: 0.8672	LR: 0.039024
Training Epoch: 1 [4608/10284]	Loss: 0.7555	LR: 0.041463
Training Epoch: 1 [4864/10284]	Loss: 1.4459	LR: 0.043902
Training Epoch: 1 [5120/10284]	Loss: 1.2072	LR: 0.046341
Training Epoch: 1 [5376/10284]	Loss: 0.6812	LR: 0.048780
Training Epoch: 1 [5632/10284]	Loss: 0.7546	LR: 0.051220
Training Epoch: 1 [5888/10284]	Loss: 0.7397	LR: 0.053659
Training Epoch: 1 [6144/10284]	Loss: 0.7089	LR: 0.056098
Training Epoch: 1 [6400/10284]	Loss: 0.7420	LR: 0.058537
Training Epoch: 1 [6656/10284]	Loss: 0.7108	LR: 0.060976
Training Epoch: 1 [6912/10284]	Loss: 0.7734	LR: 0.063415
Training Epoch: 1 [7168/10284]	Loss: 0.7335	LR: 0.065854
Training Epoch: 1 [7424/10284]	Loss: 0.6791	LR: 0.068293
Training Epoch: 1 [7680/10284]	Loss: 0.8781	LR: 0.070732
Training Epoch: 1 [7936/10284]	Loss: 0.9363	LR: 0.073171
Training Epoch: 1 [8192/10284]	Loss: 0.7184	LR: 0.075610
Training Epoch: 1 [8448/10284]	Loss: 0.6880	LR: 0.078049
Training Epoch: 1 [8704/10284]	Loss: 0.7440	LR: 0.080488
Training Epoch: 1 [8960/10284]	Loss: 0.7889	LR: 0.082927
Training Epoch: 1 [9216/10284]	Loss: 0.7387	LR: 0.085366
Training Epoch: 1 [9472/10284]	Loss: 0.7359	LR: 0.087805
Training Epoch: 1 [9728/10284]	Loss: 0.7701	LR: 0.090244
Training Epoch: 1 [9984/10284]	Loss: 0.8148	LR: 0.092683
Training Epoch: 1 [10240/10284]	Loss: 0.6809	LR: 0.095122
Training Epoch: 1 [10284/10284]	Loss: 0.7019	LR: 0.097561
Epoch 1 - Average Train Loss: 0.8202, Train Accuracy: 0.5317
Epoch 1 training time consumed: 356.37s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.2975, Accuracy: 0.5550, Time consumed:8.22s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-1-best.pth
Training Epoch: 2 [256/10284]	Loss: 0.7999	LR: 0.100000
Training Epoch: 2 [512/10284]	Loss: 1.2538	LR: 0.100000
Training Epoch: 2 [768/10284]	Loss: 0.7234	LR: 0.100000
Training Epoch: 2 [1024/10284]	Loss: 0.7311	LR: 0.100000
Training Epoch: 2 [1280/10284]	Loss: 0.6643	LR: 0.100000
Training Epoch: 2 [1536/10284]	Loss: 0.7256	LR: 0.100000
Training Epoch: 2 [1792/10284]	Loss: 0.7482	LR: 0.100000
Training Epoch: 2 [2048/10284]	Loss: 0.7003	LR: 0.100000
Training Epoch: 2 [2304/10284]	Loss: 0.7365	LR: 0.100000
Training Epoch: 2 [2560/10284]	Loss: 0.6825	LR: 0.100000
Training Epoch: 2 [2816/10284]	Loss: 0.6942	LR: 0.100000
Training Epoch: 2 [3072/10284]	Loss: 0.7223	LR: 0.100000
Training Epoch: 2 [3328/10284]	Loss: 0.6795	LR: 0.100000
Training Epoch: 2 [3584/10284]	Loss: 0.6971	LR: 0.100000
Training Epoch: 2 [3840/10284]	Loss: 0.7627	LR: 0.100000
Training Epoch: 2 [4096/10284]	Loss: 0.7796	LR: 0.100000
Training Epoch: 2 [4352/10284]	Loss: 0.7624	LR: 0.100000
Training Epoch: 2 [4608/10284]	Loss: 0.6944	LR: 0.100000
Training Epoch: 2 [4864/10284]	Loss: 0.6977	LR: 0.100000
Training Epoch: 2 [5120/10284]	Loss: 0.8040	LR: 0.100000
Training Epoch: 2 [5376/10284]	Loss: 0.7167	LR: 0.100000
Training Epoch: 2 [5632/10284]	Loss: 0.7846	LR: 0.100000
Training Epoch: 2 [5888/10284]	Loss: 0.6847	LR: 0.100000
Training Epoch: 2 [6144/10284]	Loss: 0.8369	LR: 0.100000
Training Epoch: 2 [6400/10284]	Loss: 0.7138	LR: 0.100000
Training Epoch: 2 [6656/10284]	Loss: 0.6781	LR: 0.100000
Training Epoch: 2 [6912/10284]	Loss: 0.7637	LR: 0.100000
Training Epoch: 2 [7168/10284]	Loss: 0.7240	LR: 0.100000
Training Epoch: 2 [7424/10284]	Loss: 0.7057	LR: 0.100000
Training Epoch: 2 [7680/10284]	Loss: 0.7149	LR: 0.100000
Training Epoch: 2 [7936/10284]	Loss: 0.6998	LR: 0.100000
Training Epoch: 2 [8192/10284]	Loss: 0.7522	LR: 0.100000
Training Epoch: 2 [8448/10284]	Loss: 0.6741	LR: 0.100000
Training Epoch: 2 [8704/10284]	Loss: 0.7182	LR: 0.100000
Training Epoch: 2 [8960/10284]	Loss: 0.6810	LR: 0.100000
Training Epoch: 2 [9216/10284]	Loss: 0.6985	LR: 0.100000
Training Epoch: 2 [9472/10284]	Loss: 0.6957	LR: 0.100000
Training Epoch: 2 [9728/10284]	Loss: 0.7129	LR: 0.100000
Training Epoch: 2 [9984/10284]	Loss: 0.6812	LR: 0.100000
Training Epoch: 2 [10240/10284]	Loss: 0.6721	LR: 0.100000
Training Epoch: 2 [10284/10284]	Loss: 0.6948	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7340, Train Accuracy: 0.5423
Epoch 2 training time consumed: 154.48s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0030, Accuracy: 0.5835, Time consumed:8.28s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-2-best.pth
Training Epoch: 3 [256/10284]	Loss: 0.6829	LR: 0.100000
Training Epoch: 3 [512/10284]	Loss: 0.7392	LR: 0.100000
Training Epoch: 3 [768/10284]	Loss: 0.7100	LR: 0.100000
Training Epoch: 3 [1024/10284]	Loss: 0.6722	LR: 0.100000
Training Epoch: 3 [1280/10284]	Loss: 0.7292	LR: 0.100000
Training Epoch: 3 [1536/10284]	Loss: 0.7265	LR: 0.100000
Training Epoch: 3 [1792/10284]	Loss: 0.6934	LR: 0.100000
Training Epoch: 3 [2048/10284]	Loss: 0.7598	LR: 0.100000
Training Epoch: 3 [2304/10284]	Loss: 0.7297	LR: 0.100000
Training Epoch: 3 [2560/10284]	Loss: 0.7071	LR: 0.100000
Training Epoch: 3 [2816/10284]	Loss: 0.6975	LR: 0.100000
Training Epoch: 3 [3072/10284]	Loss: 0.8577	LR: 0.100000
Training Epoch: 3 [3328/10284]	Loss: 0.7156	LR: 0.100000
Training Epoch: 3 [3584/10284]	Loss: 0.7449	LR: 0.100000
Training Epoch: 3 [3840/10284]	Loss: 0.6505	LR: 0.100000
Training Epoch: 3 [4096/10284]	Loss: 0.7595	LR: 0.100000
Training Epoch: 3 [4352/10284]	Loss: 0.7025	LR: 0.100000
Training Epoch: 3 [4608/10284]	Loss: 0.7719	LR: 0.100000
Training Epoch: 3 [4864/10284]	Loss: 0.6894	LR: 0.100000
Training Epoch: 3 [5120/10284]	Loss: 0.6830	LR: 0.100000
Training Epoch: 3 [5376/10284]	Loss: 0.7043	LR: 0.100000
Training Epoch: 3 [5632/10284]	Loss: 0.6470	LR: 0.100000
Training Epoch: 3 [5888/10284]	Loss: 0.6749	LR: 0.100000
Training Epoch: 3 [6144/10284]	Loss: 0.7036	LR: 0.100000
Training Epoch: 3 [6400/10284]	Loss: 0.6791	LR: 0.100000
Training Epoch: 3 [6656/10284]	Loss: 0.6862	LR: 0.100000
Training Epoch: 3 [6912/10284]	Loss: 0.6630	LR: 0.100000
Training Epoch: 3 [7168/10284]	Loss: 0.6645	LR: 0.100000
Training Epoch: 3 [7424/10284]	Loss: 0.6782	LR: 0.100000
Training Epoch: 3 [7680/10284]	Loss: 0.6559	LR: 0.100000
Training Epoch: 3 [7936/10284]	Loss: 0.6538	LR: 0.100000
Training Epoch: 3 [8192/10284]	Loss: 0.6779	LR: 0.100000
Training Epoch: 3 [8448/10284]	Loss: 0.6645	LR: 0.100000
Training Epoch: 3 [8704/10284]	Loss: 0.6537	LR: 0.100000
Training Epoch: 3 [8960/10284]	Loss: 0.6720	LR: 0.100000
Training Epoch: 3 [9216/10284]	Loss: 0.6658	LR: 0.100000
Training Epoch: 3 [9472/10284]	Loss: 0.6521	LR: 0.100000
Training Epoch: 3 [9728/10284]	Loss: 0.6721	LR: 0.100000
Training Epoch: 3 [9984/10284]	Loss: 0.6732	LR: 0.100000
Training Epoch: 3 [10240/10284]	Loss: 0.6407	LR: 0.100000
Training Epoch: 3 [10284/10284]	Loss: 0.7268	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6953, Train Accuracy: 0.5899
Epoch 3 training time consumed: 153.26s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0031, Accuracy: 0.5506, Time consumed:8.17s
Training Epoch: 4 [256/10284]	Loss: 0.7251	LR: 0.100000
Training Epoch: 4 [512/10284]	Loss: 0.7255	LR: 0.100000
Training Epoch: 4 [768/10284]	Loss: 0.6951	LR: 0.100000
Training Epoch: 4 [1024/10284]	Loss: 0.6807	LR: 0.100000
Training Epoch: 4 [1280/10284]	Loss: 0.6835	LR: 0.100000
Training Epoch: 4 [1536/10284]	Loss: 0.7022	LR: 0.100000
Training Epoch: 4 [1792/10284]	Loss: 0.6841	LR: 0.100000
Training Epoch: 4 [2048/10284]	Loss: 0.6991	LR: 0.100000
Training Epoch: 4 [2304/10284]	Loss: 0.7207	LR: 0.100000
Training Epoch: 4 [2560/10284]	Loss: 0.6787	LR: 0.100000
Training Epoch: 4 [2816/10284]	Loss: 0.6723	LR: 0.100000
Training Epoch: 4 [3072/10284]	Loss: 0.6959	LR: 0.100000
Training Epoch: 4 [3328/10284]	Loss: 0.6823	LR: 0.100000
Training Epoch: 4 [3584/10284]	Loss: 0.6893	LR: 0.100000
Training Epoch: 4 [3840/10284]	Loss: 0.7763	LR: 0.100000
Training Epoch: 4 [4096/10284]	Loss: 0.6860	LR: 0.100000
Training Epoch: 4 [4352/10284]	Loss: 0.6838	LR: 0.100000
Training Epoch: 4 [4608/10284]	Loss: 0.7328	LR: 0.100000
Training Epoch: 4 [4864/10284]	Loss: 0.7118	LR: 0.100000
Training Epoch: 4 [5120/10284]	Loss: 0.7225	LR: 0.100000
Training Epoch: 4 [5376/10284]	Loss: 0.6461	LR: 0.100000
Training Epoch: 4 [5632/10284]	Loss: 0.6949	LR: 0.100000
Training Epoch: 4 [5888/10284]	Loss: 0.7253	LR: 0.100000
Training Epoch: 4 [6144/10284]	Loss: 0.6946	LR: 0.100000
Training Epoch: 4 [6400/10284]	Loss: 0.7563	LR: 0.100000
Training Epoch: 4 [6656/10284]	Loss: 0.6880	LR: 0.100000
Training Epoch: 4 [6912/10284]	Loss: 0.7329	LR: 0.100000
Training Epoch: 4 [7168/10284]	Loss: 0.7060	LR: 0.100000
Training Epoch: 4 [7424/10284]	Loss: 0.7518	LR: 0.100000
Training Epoch: 4 [7680/10284]	Loss: 0.7402	LR: 0.100000
Training Epoch: 4 [7936/10284]	Loss: 0.7154	LR: 0.100000
Training Epoch: 4 [8192/10284]	Loss: 0.6989	LR: 0.100000
Training Epoch: 4 [8448/10284]	Loss: 0.7243	LR: 0.100000
Training Epoch: 4 [8704/10284]	Loss: 0.7558	LR: 0.100000
Training Epoch: 4 [8960/10284]	Loss: 0.7065	LR: 0.100000
Training Epoch: 4 [9216/10284]	Loss: 0.6874	LR: 0.100000
Training Epoch: 4 [9472/10284]	Loss: 0.6685	LR: 0.100000
Training Epoch: 4 [9728/10284]	Loss: 0.6687	LR: 0.100000
Training Epoch: 4 [9984/10284]	Loss: 0.7382	LR: 0.100000
Training Epoch: 4 [10240/10284]	Loss: 0.6933	LR: 0.100000
Training Epoch: 4 [10284/10284]	Loss: 0.6263	LR: 0.100000
Epoch 4 - Average Train Loss: 0.7057, Train Accuracy: 0.5481
Epoch 4 training time consumed: 153.26s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0030, Accuracy: 0.5617, Time consumed:8.07s
Training Epoch: 5 [256/10284]	Loss: 0.6628	LR: 0.100000
Training Epoch: 5 [512/10284]	Loss: 0.6690	LR: 0.100000
Training Epoch: 5 [768/10284]	Loss: 0.6641	LR: 0.100000
Training Epoch: 5 [1024/10284]	Loss: 0.6768	LR: 0.100000
Training Epoch: 5 [1280/10284]	Loss: 0.6833	LR: 0.100000
Training Epoch: 5 [1536/10284]	Loss: 0.6762	LR: 0.100000
Training Epoch: 5 [1792/10284]	Loss: 0.6880	LR: 0.100000
Training Epoch: 5 [2048/10284]	Loss: 0.6794	LR: 0.100000
Training Epoch: 5 [2304/10284]	Loss: 0.6804	LR: 0.100000
Training Epoch: 5 [2560/10284]	Loss: 0.6739	LR: 0.100000
Training Epoch: 5 [2816/10284]	Loss: 0.6942	LR: 0.100000
Training Epoch: 5 [3072/10284]	Loss: 0.6803	LR: 0.100000
Training Epoch: 5 [3328/10284]	Loss: 0.6690	LR: 0.100000
Training Epoch: 5 [3584/10284]	Loss: 0.6787	LR: 0.100000
Training Epoch: 5 [3840/10284]	Loss: 0.6856	LR: 0.100000
Training Epoch: 5 [4096/10284]	Loss: 0.6771	LR: 0.100000
Training Epoch: 5 [4352/10284]	Loss: 0.6887	LR: 0.100000
Training Epoch: 5 [4608/10284]	Loss: 0.7097	LR: 0.100000
Training Epoch: 5 [4864/10284]	Loss: 0.6850	LR: 0.100000
Training Epoch: 5 [5120/10284]	Loss: 0.6859	LR: 0.100000
Training Epoch: 5 [5376/10284]	Loss: 0.6793	LR: 0.100000
Training Epoch: 5 [5632/10284]	Loss: 0.6904	LR: 0.100000
Training Epoch: 5 [5888/10284]	Loss: 0.6653	LR: 0.100000
Training Epoch: 5 [6144/10284]	Loss: 0.6890	LR: 0.100000
Training Epoch: 5 [6400/10284]	Loss: 0.6820	LR: 0.100000
Training Epoch: 5 [6656/10284]	Loss: 0.6859	LR: 0.100000
Training Epoch: 5 [6912/10284]	Loss: 0.6874	LR: 0.100000
Training Epoch: 5 [7168/10284]	Loss: 0.6759	LR: 0.100000
Training Epoch: 5 [7424/10284]	Loss: 0.6736	LR: 0.100000
Training Epoch: 5 [7680/10284]	Loss: 0.6775	LR: 0.100000
Training Epoch: 5 [7936/10284]	Loss: 0.6782	LR: 0.100000
Training Epoch: 5 [8192/10284]	Loss: 0.6790	LR: 0.100000
Training Epoch: 5 [8448/10284]	Loss: 0.6444	LR: 0.100000
Training Epoch: 5 [8704/10284]	Loss: 0.6994	LR: 0.100000
Training Epoch: 5 [8960/10284]	Loss: 0.6738	LR: 0.100000
Training Epoch: 5 [9216/10284]	Loss: 0.6855	LR: 0.100000
Training Epoch: 5 [9472/10284]	Loss: 0.6680	LR: 0.100000
Training Epoch: 5 [9728/10284]	Loss: 0.6869	LR: 0.100000
Training Epoch: 5 [9984/10284]	Loss: 0.6396	LR: 0.100000
Training Epoch: 5 [10240/10284]	Loss: 0.6922	LR: 0.100000
Training Epoch: 5 [10284/10284]	Loss: 0.6263	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6788, Train Accuracy: 0.5721
Epoch 5 training time consumed: 152.99s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0030, Accuracy: 0.5831, Time consumed:8.31s
Training Epoch: 6 [256/10284]	Loss: 0.6140	LR: 0.100000
Training Epoch: 6 [512/10284]	Loss: 0.6878	LR: 0.100000
Training Epoch: 6 [768/10284]	Loss: 0.6554	LR: 0.100000
Training Epoch: 6 [1024/10284]	Loss: 0.6544	LR: 0.100000
Training Epoch: 6 [1280/10284]	Loss: 0.6627	LR: 0.100000
Training Epoch: 6 [1536/10284]	Loss: 0.6840	LR: 0.100000
Training Epoch: 6 [1792/10284]	Loss: 0.6750	LR: 0.100000
Training Epoch: 6 [2048/10284]	Loss: 0.6692	LR: 0.100000
Training Epoch: 6 [2304/10284]	Loss: 0.6781	LR: 0.100000
Training Epoch: 6 [2560/10284]	Loss: 0.6784	LR: 0.100000
Training Epoch: 6 [2816/10284]	Loss: 0.6622	LR: 0.100000
Training Epoch: 6 [3072/10284]	Loss: 0.6686	LR: 0.100000
Training Epoch: 6 [3328/10284]	Loss: 0.6743	LR: 0.100000
Training Epoch: 6 [3584/10284]	Loss: 0.6419	LR: 0.100000
Training Epoch: 6 [3840/10284]	Loss: 0.6582	LR: 0.100000
Training Epoch: 6 [4096/10284]	Loss: 0.6330	LR: 0.100000
Training Epoch: 6 [4352/10284]	Loss: 0.6682	LR: 0.100000
Training Epoch: 6 [4608/10284]	Loss: 0.6791	LR: 0.100000
Training Epoch: 6 [4864/10284]	Loss: 0.6536	LR: 0.100000
Training Epoch: 6 [5120/10284]	Loss: 0.6393	LR: 0.100000
Training Epoch: 6 [5376/10284]	Loss: 0.6686	LR: 0.100000
Training Epoch: 6 [5632/10284]	Loss: 0.6440	LR: 0.100000
Training Epoch: 6 [5888/10284]	Loss: 0.6721	LR: 0.100000
Training Epoch: 6 [6144/10284]	Loss: 0.6553	LR: 0.100000
Training Epoch: 6 [6400/10284]	Loss: 0.6984	LR: 0.100000
Training Epoch: 6 [6656/10284]	Loss: 0.6908	LR: 0.100000
Training Epoch: 6 [6912/10284]	Loss: 0.6911	LR: 0.100000
Training Epoch: 6 [7168/10284]	Loss: 0.6771	LR: 0.100000
Training Epoch: 6 [7424/10284]	Loss: 0.6896	LR: 0.100000
Training Epoch: 6 [7680/10284]	Loss: 0.6418	LR: 0.100000
Training Epoch: 6 [7936/10284]	Loss: 0.6633	LR: 0.100000
Training Epoch: 6 [8192/10284]	Loss: 0.6810	LR: 0.100000
Training Epoch: 6 [8448/10284]	Loss: 0.6757	LR: 0.100000
Training Epoch: 6 [8704/10284]	Loss: 0.6712	LR: 0.100000
Training Epoch: 6 [8960/10284]	Loss: 0.6251	LR: 0.100000
Training Epoch: 6 [9216/10284]	Loss: 0.6761	LR: 0.100000
Training Epoch: 6 [9472/10284]	Loss: 0.6700	LR: 0.100000
Training Epoch: 6 [9728/10284]	Loss: 0.6743	LR: 0.100000
Training Epoch: 6 [9984/10284]	Loss: 0.6968	LR: 0.100000
Training Epoch: 6 [10240/10284]	Loss: 0.6254	LR: 0.100000
Training Epoch: 6 [10284/10284]	Loss: 0.7021	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6658, Train Accuracy: 0.6042
Epoch 6 training time consumed: 153.28s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0030, Accuracy: 0.5758, Time consumed:8.32s
Training Epoch: 7 [256/10284]	Loss: 0.6770	LR: 0.100000
Training Epoch: 7 [512/10284]	Loss: 0.6770	LR: 0.100000
Training Epoch: 7 [768/10284]	Loss: 0.6668	LR: 0.100000
Training Epoch: 7 [1024/10284]	Loss: 0.6724	LR: 0.100000
Training Epoch: 7 [1280/10284]	Loss: 0.6251	LR: 0.100000
Training Epoch: 7 [1536/10284]	Loss: 0.6356	LR: 0.100000
Training Epoch: 7 [1792/10284]	Loss: 0.6766	LR: 0.100000
Training Epoch: 7 [2048/10284]	Loss: 0.6803	LR: 0.100000
Training Epoch: 7 [2304/10284]	Loss: 0.6292	LR: 0.100000
Training Epoch: 7 [2560/10284]	Loss: 0.6319	LR: 0.100000
Training Epoch: 7 [2816/10284]	Loss: 0.6290	LR: 0.100000
Training Epoch: 7 [3072/10284]	Loss: 0.6263	LR: 0.100000
Training Epoch: 7 [3328/10284]	Loss: 0.6585	LR: 0.100000
Training Epoch: 7 [3584/10284]	Loss: 0.6513	LR: 0.100000
Training Epoch: 7 [3840/10284]	Loss: 0.6035	LR: 0.100000
Training Epoch: 7 [4096/10284]	Loss: 0.6566	LR: 0.100000
Training Epoch: 7 [4352/10284]	Loss: 0.6439	LR: 0.100000
Training Epoch: 7 [4608/10284]	Loss: 0.5991	LR: 0.100000
Training Epoch: 7 [4864/10284]	Loss: 0.6054	LR: 0.100000
Training Epoch: 7 [5120/10284]	Loss: 0.6331	LR: 0.100000
Training Epoch: 7 [5376/10284]	Loss: 0.6478	LR: 0.100000
Training Epoch: 7 [5632/10284]	Loss: 0.6462	LR: 0.100000
Training Epoch: 7 [5888/10284]	Loss: 0.6303	LR: 0.100000
Training Epoch: 7 [6144/10284]	Loss: 0.6262	LR: 0.100000
Training Epoch: 7 [6400/10284]	Loss: 0.6186	LR: 0.100000
Training Epoch: 7 [6656/10284]	Loss: 0.6440	LR: 0.100000
Training Epoch: 7 [6912/10284]	Loss: 0.6064	LR: 0.100000
Training Epoch: 7 [7168/10284]	Loss: 0.6449	LR: 0.100000
Training Epoch: 7 [7424/10284]	Loss: 0.6243	LR: 0.100000
Training Epoch: 7 [7680/10284]	Loss: 0.6162	LR: 0.100000
Training Epoch: 7 [7936/10284]	Loss: 0.6261	LR: 0.100000
Training Epoch: 7 [8192/10284]	Loss: 0.5927	LR: 0.100000
Training Epoch: 7 [8448/10284]	Loss: 0.5791	LR: 0.100000
Training Epoch: 7 [8704/10284]	Loss: 0.6022	LR: 0.100000
Training Epoch: 7 [8960/10284]	Loss: 0.6276	LR: 0.100000
Training Epoch: 7 [9216/10284]	Loss: 0.6120	LR: 0.100000
Training Epoch: 7 [9472/10284]	Loss: 0.6028	LR: 0.100000
Training Epoch: 7 [9728/10284]	Loss: 0.5615	LR: 0.100000
Training Epoch: 7 [9984/10284]	Loss: 0.6848	LR: 0.100000
Training Epoch: 7 [10240/10284]	Loss: 0.6117	LR: 0.100000
Training Epoch: 7 [10284/10284]	Loss: 0.5639	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6318, Train Accuracy: 0.6447
Epoch 7 training time consumed: 153.69s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0029, Accuracy: 0.6223, Time consumed:8.52s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-7-best.pth
Training Epoch: 8 [256/10284]	Loss: 0.6956	LR: 0.100000
Training Epoch: 8 [512/10284]	Loss: 0.6007	LR: 0.100000
Training Epoch: 8 [768/10284]	Loss: 0.6224	LR: 0.100000
Training Epoch: 8 [1024/10284]	Loss: 0.5760	LR: 0.100000
Training Epoch: 8 [1280/10284]	Loss: 0.6604	LR: 0.100000
Training Epoch: 8 [1536/10284]	Loss: 0.6153	LR: 0.100000
Training Epoch: 8 [1792/10284]	Loss: 0.5731	LR: 0.100000
Training Epoch: 8 [2048/10284]	Loss: 0.6144	LR: 0.100000
Training Epoch: 8 [2304/10284]	Loss: 0.5744	LR: 0.100000
Training Epoch: 8 [2560/10284]	Loss: 0.6227	LR: 0.100000
Training Epoch: 8 [2816/10284]	Loss: 0.6189	LR: 0.100000
Training Epoch: 8 [3072/10284]	Loss: 0.6122	LR: 0.100000
Training Epoch: 8 [3328/10284]	Loss: 0.5639	LR: 0.100000
Training Epoch: 8 [3584/10284]	Loss: 0.5874	LR: 0.100000
Training Epoch: 8 [3840/10284]	Loss: 0.5352	LR: 0.100000
Training Epoch: 8 [4096/10284]	Loss: 0.5748	LR: 0.100000
Training Epoch: 8 [4352/10284]	Loss: 0.6154	LR: 0.100000
Training Epoch: 8 [4608/10284]	Loss: 0.6473	LR: 0.100000
Training Epoch: 8 [4864/10284]	Loss: 0.5630	LR: 0.100000
Training Epoch: 8 [5120/10284]	Loss: 0.6338	LR: 0.100000
Training Epoch: 8 [5376/10284]	Loss: 0.5762	LR: 0.100000
Training Epoch: 8 [5632/10284]	Loss: 0.5620	LR: 0.100000
Training Epoch: 8 [5888/10284]	Loss: 0.5559	LR: 0.100000
Training Epoch: 8 [6144/10284]	Loss: 0.5941	LR: 0.100000
Training Epoch: 8 [6400/10284]	Loss: 0.5413	LR: 0.100000
Training Epoch: 8 [6656/10284]	Loss: 0.5396	LR: 0.100000
Training Epoch: 8 [6912/10284]	Loss: 0.5651	LR: 0.100000
Training Epoch: 8 [7168/10284]	Loss: 0.5791	LR: 0.100000
Training Epoch: 8 [7424/10284]	Loss: 0.5241	LR: 0.100000
Training Epoch: 8 [7680/10284]	Loss: 0.6042	LR: 0.100000
Training Epoch: 8 [7936/10284]	Loss: 0.5624	LR: 0.100000
Training Epoch: 8 [8192/10284]	Loss: 0.5278	LR: 0.100000
Training Epoch: 8 [8448/10284]	Loss: 0.5731	LR: 0.100000
Training Epoch: 8 [8704/10284]	Loss: 0.5845	LR: 0.100000
Training Epoch: 8 [8960/10284]	Loss: 0.5674	LR: 0.100000
Training Epoch: 8 [9216/10284]	Loss: 0.5519	LR: 0.100000
Training Epoch: 8 [9472/10284]	Loss: 0.5618	LR: 0.100000
Training Epoch: 8 [9728/10284]	Loss: 0.6099	LR: 0.100000
Training Epoch: 8 [9984/10284]	Loss: 0.5638	LR: 0.100000
Training Epoch: 8 [10240/10284]	Loss: 0.5444	LR: 0.100000
Training Epoch: 8 [10284/10284]	Loss: 0.5915	LR: 0.100000
Epoch 8 - Average Train Loss: 0.5849, Train Accuracy: 0.6964
Epoch 8 training time consumed: 153.80s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0025, Accuracy: 0.7172, Time consumed:8.02s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-8-best.pth
Training Epoch: 9 [256/10284]	Loss: 0.5776	LR: 0.100000
Training Epoch: 9 [512/10284]	Loss: 0.5739	LR: 0.100000
Training Epoch: 9 [768/10284]	Loss: 0.5604	LR: 0.100000
Training Epoch: 9 [1024/10284]	Loss: 0.5314	LR: 0.100000
Training Epoch: 9 [1280/10284]	Loss: 0.5540	LR: 0.100000
Training Epoch: 9 [1536/10284]	Loss: 0.5562	LR: 0.100000
Training Epoch: 9 [1792/10284]	Loss: 0.4849	LR: 0.100000
Training Epoch: 9 [2048/10284]	Loss: 0.4996	LR: 0.100000
Training Epoch: 9 [2304/10284]	Loss: 0.5187	LR: 0.100000
Training Epoch: 9 [2560/10284]	Loss: 0.5700	LR: 0.100000
Training Epoch: 9 [2816/10284]	Loss: 0.4871	LR: 0.100000
Training Epoch: 9 [3072/10284]	Loss: 0.4855	LR: 0.100000
Training Epoch: 9 [3328/10284]	Loss: 0.4920	LR: 0.100000
Training Epoch: 9 [3584/10284]	Loss: 0.5491	LR: 0.100000
Training Epoch: 9 [3840/10284]	Loss: 0.5010	LR: 0.100000
Training Epoch: 9 [4096/10284]	Loss: 0.4580	LR: 0.100000
Training Epoch: 9 [4352/10284]	Loss: 0.4739	LR: 0.100000
Training Epoch: 9 [4608/10284]	Loss: 0.5002	LR: 0.100000
Training Epoch: 9 [4864/10284]	Loss: 0.5874	LR: 0.100000
Training Epoch: 9 [5120/10284]	Loss: 0.5169	LR: 0.100000
Training Epoch: 9 [5376/10284]	Loss: 0.5561	LR: 0.100000
Training Epoch: 9 [5632/10284]	Loss: 0.4953	LR: 0.100000
Training Epoch: 9 [5888/10284]	Loss: 0.4946	LR: 0.100000
Training Epoch: 9 [6144/10284]	Loss: 0.4748	LR: 0.100000
Training Epoch: 9 [6400/10284]	Loss: 0.5043	LR: 0.100000
Training Epoch: 9 [6656/10284]	Loss: 0.4902	LR: 0.100000
Training Epoch: 9 [6912/10284]	Loss: 0.5084	LR: 0.100000
Training Epoch: 9 [7168/10284]	Loss: 0.5083	LR: 0.100000
Training Epoch: 9 [7424/10284]	Loss: 0.4975	LR: 0.100000
Training Epoch: 9 [7680/10284]	Loss: 0.5161	LR: 0.100000
Training Epoch: 9 [7936/10284]	Loss: 0.4837	LR: 0.100000
Training Epoch: 9 [8192/10284]	Loss: 0.5025	LR: 0.100000
Training Epoch: 9 [8448/10284]	Loss: 0.4382	LR: 0.100000
Training Epoch: 9 [8704/10284]	Loss: 0.4915	LR: 0.100000
Training Epoch: 9 [8960/10284]	Loss: 0.4788	LR: 0.100000
Training Epoch: 9 [9216/10284]	Loss: 0.4988	LR: 0.100000
Training Epoch: 9 [9472/10284]	Loss: 0.4018	LR: 0.100000
Training Epoch: 9 [9728/10284]	Loss: 0.4432	LR: 0.100000
Training Epoch: 9 [9984/10284]	Loss: 0.3761	LR: 0.100000
Training Epoch: 9 [10240/10284]	Loss: 0.4683	LR: 0.100000
Training Epoch: 9 [10284/10284]	Loss: 0.4723	LR: 0.100000
Epoch 9 - Average Train Loss: 0.5025, Train Accuracy: 0.7592
Epoch 9 training time consumed: 153.56s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0052, Accuracy: 0.5554, Time consumed:8.19s
Training Epoch: 10 [256/10284]	Loss: 0.4017	LR: 0.020000
Training Epoch: 10 [512/10284]	Loss: 0.4782	LR: 0.020000
Training Epoch: 10 [768/10284]	Loss: 0.3817	LR: 0.020000
Training Epoch: 10 [1024/10284]	Loss: 0.4312	LR: 0.020000
Training Epoch: 10 [1280/10284]	Loss: 0.4462	LR: 0.020000
Training Epoch: 10 [1536/10284]	Loss: 0.4430	LR: 0.020000
Training Epoch: 10 [1792/10284]	Loss: 0.4384	LR: 0.020000
Training Epoch: 10 [2048/10284]	Loss: 0.3990	LR: 0.020000
Training Epoch: 10 [2304/10284]	Loss: 0.4355	LR: 0.020000
Training Epoch: 10 [2560/10284]	Loss: 0.4470	LR: 0.020000
Training Epoch: 10 [2816/10284]	Loss: 0.4554	LR: 0.020000
Training Epoch: 10 [3072/10284]	Loss: 0.4635	LR: 0.020000
Training Epoch: 10 [3328/10284]	Loss: 0.3769	LR: 0.020000
Training Epoch: 10 [3584/10284]	Loss: 0.4278	LR: 0.020000
Training Epoch: 10 [3840/10284]	Loss: 0.3766	LR: 0.020000
Training Epoch: 10 [4096/10284]	Loss: 0.4161	LR: 0.020000
Training Epoch: 10 [4352/10284]	Loss: 0.4361	LR: 0.020000
Training Epoch: 10 [4608/10284]	Loss: 0.4282	LR: 0.020000
Training Epoch: 10 [4864/10284]	Loss: 0.4402	LR: 0.020000
Training Epoch: 10 [5120/10284]	Loss: 0.3888	LR: 0.020000
Training Epoch: 10 [5376/10284]	Loss: 0.3919	LR: 0.020000
Training Epoch: 10 [5632/10284]	Loss: 0.4317	LR: 0.020000
Training Epoch: 10 [5888/10284]	Loss: 0.4246	LR: 0.020000
Training Epoch: 10 [6144/10284]	Loss: 0.4057	LR: 0.020000
Training Epoch: 10 [6400/10284]	Loss: 0.3954	LR: 0.020000
Training Epoch: 10 [6656/10284]	Loss: 0.4087	LR: 0.020000
Training Epoch: 10 [6912/10284]	Loss: 0.3552	LR: 0.020000
Training Epoch: 10 [7168/10284]	Loss: 0.4254	LR: 0.020000
Training Epoch: 10 [7424/10284]	Loss: 0.3962	LR: 0.020000
Training Epoch: 10 [7680/10284]	Loss: 0.3893	LR: 0.020000
Training Epoch: 10 [7936/10284]	Loss: 0.3914	LR: 0.020000
Training Epoch: 10 [8192/10284]	Loss: 0.3244	LR: 0.020000
Training Epoch: 10 [8448/10284]	Loss: 0.4312	LR: 0.020000
Training Epoch: 10 [8704/10284]	Loss: 0.3627	LR: 0.020000
Training Epoch: 10 [8960/10284]	Loss: 0.3764	LR: 0.020000
Training Epoch: 10 [9216/10284]	Loss: 0.4194	LR: 0.020000
Training Epoch: 10 [9472/10284]	Loss: 0.3800	LR: 0.020000
Training Epoch: 10 [9728/10284]	Loss: 0.3683	LR: 0.020000
Training Epoch: 10 [9984/10284]	Loss: 0.3647	LR: 0.020000
Training Epoch: 10 [10240/10284]	Loss: 0.4110	LR: 0.020000
Training Epoch: 10 [10284/10284]	Loss: 0.4364	LR: 0.020000
Epoch 10 - Average Train Loss: 0.4092, Train Accuracy: 0.8159
Epoch 10 training time consumed: 153.88s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0017, Accuracy: 0.8262, Time consumed:8.31s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-10-best.pth
Training Epoch: 11 [256/10284]	Loss: 0.4158	LR: 0.020000
Training Epoch: 11 [512/10284]	Loss: 0.3804	LR: 0.020000
Training Epoch: 11 [768/10284]	Loss: 0.3996	LR: 0.020000
Training Epoch: 11 [1024/10284]	Loss: 0.3576	LR: 0.020000
Training Epoch: 11 [1280/10284]	Loss: 0.3880	LR: 0.020000
Training Epoch: 11 [1536/10284]	Loss: 0.3789	LR: 0.020000
Training Epoch: 11 [1792/10284]	Loss: 0.3681	LR: 0.020000
Training Epoch: 11 [2048/10284]	Loss: 0.4150	LR: 0.020000
Training Epoch: 11 [2304/10284]	Loss: 0.3995	LR: 0.020000
Training Epoch: 11 [2560/10284]	Loss: 0.3521	LR: 0.020000
Training Epoch: 11 [2816/10284]	Loss: 0.3352	LR: 0.020000
Training Epoch: 11 [3072/10284]	Loss: 0.3544	LR: 0.020000
Training Epoch: 11 [3328/10284]	Loss: 0.3799	LR: 0.020000
Training Epoch: 11 [3584/10284]	Loss: 0.3440	LR: 0.020000
Training Epoch: 11 [3840/10284]	Loss: 0.3549	LR: 0.020000
Training Epoch: 11 [4096/10284]	Loss: 0.3446	LR: 0.020000
Training Epoch: 11 [4352/10284]	Loss: 0.3333	LR: 0.020000
Training Epoch: 11 [4608/10284]	Loss: 0.3706	LR: 0.020000
Training Epoch: 11 [4864/10284]	Loss: 0.4439	LR: 0.020000
Training Epoch: 11 [5120/10284]	Loss: 0.3339	LR: 0.020000
Training Epoch: 11 [5376/10284]	Loss: 0.3567	LR: 0.020000
Training Epoch: 11 [5632/10284]	Loss: 0.4085	LR: 0.020000
Training Epoch: 11 [5888/10284]	Loss: 0.3333	LR: 0.020000
Training Epoch: 11 [6144/10284]	Loss: 0.3041	LR: 0.020000
Training Epoch: 11 [6400/10284]	Loss: 0.3224	LR: 0.020000
Training Epoch: 11 [6656/10284]	Loss: 0.3636	LR: 0.020000
Training Epoch: 11 [6912/10284]	Loss: 0.3480	LR: 0.020000
Training Epoch: 11 [7168/10284]	Loss: 0.3566	LR: 0.020000
Training Epoch: 11 [7424/10284]	Loss: 0.3422	LR: 0.020000
Training Epoch: 11 [7680/10284]	Loss: 0.3579	LR: 0.020000
Training Epoch: 11 [7936/10284]	Loss: 0.3342	LR: 0.020000
Training Epoch: 11 [8192/10284]	Loss: 0.3424	LR: 0.020000
Training Epoch: 11 [8448/10284]	Loss: 0.3598	LR: 0.020000
Training Epoch: 11 [8704/10284]	Loss: 0.3047	LR: 0.020000
Training Epoch: 11 [8960/10284]	Loss: 0.3111	LR: 0.020000
Training Epoch: 11 [9216/10284]	Loss: 0.3703	LR: 0.020000
Training Epoch: 11 [9472/10284]	Loss: 0.3627	LR: 0.020000
Training Epoch: 11 [9728/10284]	Loss: 0.3254	LR: 0.020000
Training Epoch: 11 [9984/10284]	Loss: 0.3328	LR: 0.020000
Training Epoch: 11 [10240/10284]	Loss: 0.3280	LR: 0.020000
Training Epoch: 11 [10284/10284]	Loss: 0.6534	LR: 0.020000
Epoch 11 - Average Train Loss: 0.3591, Train Accuracy: 0.8450
Epoch 11 training time consumed: 153.30s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0015, Accuracy: 0.8576, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-11-best.pth
Training Epoch: 12 [256/10284]	Loss: 0.3797	LR: 0.020000
Training Epoch: 12 [512/10284]	Loss: 0.3223	LR: 0.020000
Training Epoch: 12 [768/10284]	Loss: 0.3386	LR: 0.020000
Training Epoch: 12 [1024/10284]	Loss: 0.3357	LR: 0.020000
Training Epoch: 12 [1280/10284]	Loss: 0.3217	LR: 0.020000
Training Epoch: 12 [1536/10284]	Loss: 0.3002	LR: 0.020000
Training Epoch: 12 [1792/10284]	Loss: 0.3345	LR: 0.020000
Training Epoch: 12 [2048/10284]	Loss: 0.3232	LR: 0.020000
Training Epoch: 12 [2304/10284]	Loss: 0.3289	LR: 0.020000
Training Epoch: 12 [2560/10284]	Loss: 0.3379	LR: 0.020000
Training Epoch: 12 [2816/10284]	Loss: 0.3200	LR: 0.020000
Training Epoch: 12 [3072/10284]	Loss: 0.3886	LR: 0.020000
Training Epoch: 12 [3328/10284]	Loss: 0.2853	LR: 0.020000
Training Epoch: 12 [3584/10284]	Loss: 0.3469	LR: 0.020000
Training Epoch: 12 [3840/10284]	Loss: 0.3236	LR: 0.020000
Training Epoch: 12 [4096/10284]	Loss: 0.2983	LR: 0.020000
Training Epoch: 12 [4352/10284]	Loss: 0.3858	LR: 0.020000
Training Epoch: 12 [4608/10284]	Loss: 0.3126	LR: 0.020000
Training Epoch: 12 [4864/10284]	Loss: 0.4214	LR: 0.020000
Training Epoch: 12 [5120/10284]	Loss: 0.3577	LR: 0.020000
Training Epoch: 12 [5376/10284]	Loss: 0.2918	LR: 0.020000
Training Epoch: 12 [5632/10284]	Loss: 0.3503	LR: 0.020000
Training Epoch: 12 [5888/10284]	Loss: 0.3567	LR: 0.020000
Training Epoch: 12 [6144/10284]	Loss: 0.3562	LR: 0.020000
Training Epoch: 12 [6400/10284]	Loss: 0.3094	LR: 0.020000
Training Epoch: 12 [6656/10284]	Loss: 0.2560	LR: 0.020000
Training Epoch: 12 [6912/10284]	Loss: 0.3204	LR: 0.020000
Training Epoch: 12 [7168/10284]	Loss: 0.3541	LR: 0.020000
Training Epoch: 12 [7424/10284]	Loss: 0.3050	LR: 0.020000
Training Epoch: 12 [7680/10284]	Loss: 0.3360	LR: 0.020000
Training Epoch: 12 [7936/10284]	Loss: 0.2751	LR: 0.020000
Training Epoch: 12 [8192/10284]	Loss: 0.2913	LR: 0.020000
Training Epoch: 12 [8448/10284]	Loss: 0.3106	LR: 0.020000
Training Epoch: 12 [8704/10284]	Loss: 0.3056	LR: 0.020000
Training Epoch: 12 [8960/10284]	Loss: 0.2744	LR: 0.020000
Training Epoch: 12 [9216/10284]	Loss: 0.3240	LR: 0.020000
Training Epoch: 12 [9472/10284]	Loss: 0.3203	LR: 0.020000
Training Epoch: 12 [9728/10284]	Loss: 0.3188	LR: 0.020000
Training Epoch: 12 [9984/10284]	Loss: 0.3264	LR: 0.020000
Training Epoch: 12 [10240/10284]	Loss: 0.3488	LR: 0.020000
Training Epoch: 12 [10284/10284]	Loss: 0.3838	LR: 0.020000
Epoch 12 - Average Train Loss: 0.3276, Train Accuracy: 0.8575
Epoch 12 training time consumed: 153.78s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0013, Accuracy: 0.8799, Time consumed:8.27s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-12-best.pth
Training Epoch: 13 [256/10284]	Loss: 0.2834	LR: 0.020000
Training Epoch: 13 [512/10284]	Loss: 0.3304	LR: 0.020000
Training Epoch: 13 [768/10284]	Loss: 0.3371	LR: 0.020000
Training Epoch: 13 [1024/10284]	Loss: 0.3357	LR: 0.020000
Training Epoch: 13 [1280/10284]	Loss: 0.3597	LR: 0.020000
Training Epoch: 13 [1536/10284]	Loss: 0.3257	LR: 0.020000
Training Epoch: 13 [1792/10284]	Loss: 0.2754	LR: 0.020000
Training Epoch: 13 [2048/10284]	Loss: 0.3870	LR: 0.020000
Training Epoch: 13 [2304/10284]	Loss: 0.2776	LR: 0.020000
Training Epoch: 13 [2560/10284]	Loss: 0.2488	LR: 0.020000
Training Epoch: 13 [2816/10284]	Loss: 0.3148	LR: 0.020000
Training Epoch: 13 [3072/10284]	Loss: 0.3320	LR: 0.020000
Training Epoch: 13 [3328/10284]	Loss: 0.2706	LR: 0.020000
Training Epoch: 13 [3584/10284]	Loss: 0.2547	LR: 0.020000
Training Epoch: 13 [3840/10284]	Loss: 0.3438	LR: 0.020000
Training Epoch: 13 [4096/10284]	Loss: 0.2695	LR: 0.020000
Training Epoch: 13 [4352/10284]	Loss: 0.2788	LR: 0.020000
Training Epoch: 13 [4608/10284]	Loss: 0.2484	LR: 0.020000
Training Epoch: 13 [4864/10284]	Loss: 0.2526	LR: 0.020000
Training Epoch: 13 [5120/10284]	Loss: 0.2930	LR: 0.020000
Training Epoch: 13 [5376/10284]	Loss: 0.2852	LR: 0.020000
Training Epoch: 13 [5632/10284]	Loss: 0.2749	LR: 0.020000
Training Epoch: 13 [5888/10284]	Loss: 0.3070	LR: 0.020000
Training Epoch: 13 [6144/10284]	Loss: 0.2918	LR: 0.020000
Training Epoch: 13 [6400/10284]	Loss: 0.2503	LR: 0.020000
Training Epoch: 13 [6656/10284]	Loss: 0.2985	LR: 0.020000
Training Epoch: 13 [6912/10284]	Loss: 0.2885	LR: 0.020000
Training Epoch: 13 [7168/10284]	Loss: 0.2278	LR: 0.020000
Training Epoch: 13 [7424/10284]	Loss: 0.2484	LR: 0.020000
Training Epoch: 13 [7680/10284]	Loss: 0.2474	LR: 0.020000
Training Epoch: 13 [7936/10284]	Loss: 0.2816	LR: 0.020000
Training Epoch: 13 [8192/10284]	Loss: 0.3494	LR: 0.020000
Training Epoch: 13 [8448/10284]	Loss: 0.2581	LR: 0.020000
Training Epoch: 13 [8704/10284]	Loss: 0.2491	LR: 0.020000
Training Epoch: 13 [8960/10284]	Loss: 0.2075	LR: 0.020000
Training Epoch: 13 [9216/10284]	Loss: 0.3290	LR: 0.020000
Training Epoch: 13 [9472/10284]	Loss: 0.2608	LR: 0.020000
Training Epoch: 13 [9728/10284]	Loss: 0.3385	LR: 0.020000
Training Epoch: 13 [9984/10284]	Loss: 0.3082	LR: 0.020000
Training Epoch: 13 [10240/10284]	Loss: 0.2320	LR: 0.020000
Training Epoch: 13 [10284/10284]	Loss: 0.1631	LR: 0.020000
Epoch 13 - Average Train Loss: 0.2883, Train Accuracy: 0.8786
Epoch 13 training time consumed: 153.84s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0031, Accuracy: 0.7017, Time consumed:8.29s
Training Epoch: 14 [256/10284]	Loss: 0.2040	LR: 0.020000
Training Epoch: 14 [512/10284]	Loss: 0.2600	LR: 0.020000
Training Epoch: 14 [768/10284]	Loss: 0.3002	LR: 0.020000
Training Epoch: 14 [1024/10284]	Loss: 0.2836	LR: 0.020000
Training Epoch: 14 [1280/10284]	Loss: 0.2461	LR: 0.020000
Training Epoch: 14 [1536/10284]	Loss: 0.3031	LR: 0.020000
Training Epoch: 14 [1792/10284]	Loss: 0.2669	LR: 0.020000
Training Epoch: 14 [2048/10284]	Loss: 0.2805	LR: 0.020000
Training Epoch: 14 [2304/10284]	Loss: 0.2751	LR: 0.020000
Training Epoch: 14 [2560/10284]	Loss: 0.2890	LR: 0.020000
Training Epoch: 14 [2816/10284]	Loss: 0.3009	LR: 0.020000
Training Epoch: 14 [3072/10284]	Loss: 0.2014	LR: 0.020000
Training Epoch: 14 [3328/10284]	Loss: 0.3285	LR: 0.020000
Training Epoch: 14 [3584/10284]	Loss: 0.2597	LR: 0.020000
Training Epoch: 14 [3840/10284]	Loss: 0.2879	LR: 0.020000
Training Epoch: 14 [4096/10284]	Loss: 0.2633	LR: 0.020000
Training Epoch: 14 [4352/10284]	Loss: 0.2695	LR: 0.020000
Training Epoch: 14 [4608/10284]	Loss: 0.3304	LR: 0.020000
Training Epoch: 14 [4864/10284]	Loss: 0.3210	LR: 0.020000
Training Epoch: 14 [5120/10284]	Loss: 0.3079	LR: 0.020000
Training Epoch: 14 [5376/10284]	Loss: 0.2486	LR: 0.020000
Training Epoch: 14 [5632/10284]	Loss: 0.2775	LR: 0.020000
Training Epoch: 14 [5888/10284]	Loss: 0.3540	LR: 0.020000
Training Epoch: 14 [6144/10284]	Loss: 0.2117	LR: 0.020000
Training Epoch: 14 [6400/10284]	Loss: 0.3395	LR: 0.020000
Training Epoch: 14 [6656/10284]	Loss: 0.2423	LR: 0.020000
Training Epoch: 14 [6912/10284]	Loss: 0.3056	LR: 0.020000
Training Epoch: 14 [7168/10284]	Loss: 0.2879	LR: 0.020000
Training Epoch: 14 [7424/10284]	Loss: 0.2556	LR: 0.020000
Training Epoch: 14 [7680/10284]	Loss: 0.2739	LR: 0.020000
Training Epoch: 14 [7936/10284]	Loss: 0.3165	LR: 0.020000
Training Epoch: 14 [8192/10284]	Loss: 0.1812	LR: 0.020000
Training Epoch: 14 [8448/10284]	Loss: 0.3110	LR: 0.020000
Training Epoch: 14 [8704/10284]	Loss: 0.2407	LR: 0.020000
Training Epoch: 14 [8960/10284]	Loss: 0.2916	LR: 0.020000
Training Epoch: 14 [9216/10284]	Loss: 0.2176	LR: 0.020000
Training Epoch: 14 [9472/10284]	Loss: 0.2686	LR: 0.020000
Training Epoch: 14 [9728/10284]	Loss: 0.2011	LR: 0.020000
Training Epoch: 14 [9984/10284]	Loss: 0.2332	LR: 0.020000
Training Epoch: 14 [10240/10284]	Loss: 0.2137	LR: 0.020000
Training Epoch: 14 [10284/10284]	Loss: 0.1721	LR: 0.020000
Epoch 14 - Average Train Loss: 0.2708, Train Accuracy: 0.8866
Epoch 14 training time consumed: 153.49s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0013, Accuracy: 0.8838, Time consumed:8.22s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-14-best.pth
Training Epoch: 15 [256/10284]	Loss: 0.2990	LR: 0.020000
Training Epoch: 15 [512/10284]	Loss: 0.3130	LR: 0.020000
Training Epoch: 15 [768/10284]	Loss: 0.2336	LR: 0.020000
Training Epoch: 15 [1024/10284]	Loss: 0.2097	LR: 0.020000
Training Epoch: 15 [1280/10284]	Loss: 0.2377	LR: 0.020000
Training Epoch: 15 [1536/10284]	Loss: 0.1910	LR: 0.020000
Training Epoch: 15 [1792/10284]	Loss: 0.2204	LR: 0.020000
Training Epoch: 15 [2048/10284]	Loss: 0.3130	LR: 0.020000
Training Epoch: 15 [2304/10284]	Loss: 0.3035	LR: 0.020000
Training Epoch: 15 [2560/10284]	Loss: 0.2061	LR: 0.020000
Training Epoch: 15 [2816/10284]	Loss: 0.2425	LR: 0.020000
Training Epoch: 15 [3072/10284]	Loss: 0.2877	LR: 0.020000
Training Epoch: 15 [3328/10284]	Loss: 0.1927	LR: 0.020000
Training Epoch: 15 [3584/10284]	Loss: 0.1892	LR: 0.020000
Training Epoch: 15 [3840/10284]	Loss: 0.2470	LR: 0.020000
Training Epoch: 15 [4096/10284]	Loss: 0.2374	LR: 0.020000
Training Epoch: 15 [4352/10284]	Loss: 0.2220	LR: 0.020000
Training Epoch: 15 [4608/10284]	Loss: 0.2725	LR: 0.020000
Training Epoch: 15 [4864/10284]	Loss: 0.2736	LR: 0.020000
Training Epoch: 15 [5120/10284]	Loss: 0.1816	LR: 0.020000
Training Epoch: 15 [5376/10284]	Loss: 0.2111	LR: 0.020000
Training Epoch: 15 [5632/10284]	Loss: 0.2792	LR: 0.020000
Training Epoch: 15 [5888/10284]	Loss: 0.1906	LR: 0.020000
Training Epoch: 15 [6144/10284]	Loss: 0.2604	LR: 0.020000
Training Epoch: 15 [6400/10284]	Loss: 0.3382	LR: 0.020000
Training Epoch: 15 [6656/10284]	Loss: 0.2545	LR: 0.020000
Training Epoch: 15 [6912/10284]	Loss: 0.2990	LR: 0.020000
Training Epoch: 15 [7168/10284]	Loss: 0.1584	LR: 0.020000
Training Epoch: 15 [7424/10284]	Loss: 0.2651	LR: 0.020000
Training Epoch: 15 [7680/10284]	Loss: 0.2970	LR: 0.020000
Training Epoch: 15 [7936/10284]	Loss: 0.2552	LR: 0.020000
Training Epoch: 15 [8192/10284]	Loss: 0.2242	LR: 0.020000
Training Epoch: 15 [8448/10284]	Loss: 0.2675	LR: 0.020000
Training Epoch: 15 [8704/10284]	Loss: 0.2296	LR: 0.020000
Training Epoch: 15 [8960/10284]	Loss: 0.2594	LR: 0.020000
Training Epoch: 15 [9216/10284]	Loss: 0.2188	LR: 0.020000
Training Epoch: 15 [9472/10284]	Loss: 0.2446	LR: 0.020000
Training Epoch: 15 [9728/10284]	Loss: 0.2066	LR: 0.020000
Training Epoch: 15 [9984/10284]	Loss: 0.2091	LR: 0.020000
Training Epoch: 15 [10240/10284]	Loss: 0.1766	LR: 0.020000
Training Epoch: 15 [10284/10284]	Loss: 0.2888	LR: 0.020000
Epoch 15 - Average Train Loss: 0.2432, Train Accuracy: 0.8984
Epoch 15 training time consumed: 153.34s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0016, Accuracy: 0.8591, Time consumed:8.08s
Training Epoch: 16 [256/10284]	Loss: 0.2439	LR: 0.020000
Training Epoch: 16 [512/10284]	Loss: 0.2342	LR: 0.020000
Training Epoch: 16 [768/10284]	Loss: 0.3026	LR: 0.020000
Training Epoch: 16 [1024/10284]	Loss: 0.2406	LR: 0.020000
Training Epoch: 16 [1280/10284]	Loss: 0.2503	LR: 0.020000
Training Epoch: 16 [1536/10284]	Loss: 0.1703	LR: 0.020000
Training Epoch: 16 [1792/10284]	Loss: 0.1998	LR: 0.020000
Training Epoch: 16 [2048/10284]	Loss: 0.1973	LR: 0.020000
Training Epoch: 16 [2304/10284]	Loss: 0.2450	LR: 0.020000
Training Epoch: 16 [2560/10284]	Loss: 0.2224	LR: 0.020000
Training Epoch: 16 [2816/10284]	Loss: 0.1901	LR: 0.020000
Training Epoch: 16 [3072/10284]	Loss: 0.2587	LR: 0.020000
Training Epoch: 16 [3328/10284]	Loss: 0.2012	LR: 0.020000
Training Epoch: 16 [3584/10284]	Loss: 0.2479	LR: 0.020000
Training Epoch: 16 [3840/10284]	Loss: 0.1918	LR: 0.020000
Training Epoch: 16 [4096/10284]	Loss: 0.2268	LR: 0.020000
Training Epoch: 16 [4352/10284]	Loss: 0.2493	LR: 0.020000
Training Epoch: 16 [4608/10284]	Loss: 0.1958	LR: 0.020000
Training Epoch: 16 [4864/10284]	Loss: 0.2452	LR: 0.020000
Training Epoch: 16 [5120/10284]	Loss: 0.1630	LR: 0.020000
Training Epoch: 16 [5376/10284]	Loss: 0.1790	LR: 0.020000
Training Epoch: 16 [5632/10284]	Loss: 0.2219	LR: 0.020000
Training Epoch: 16 [5888/10284]	Loss: 0.2896	LR: 0.020000
Training Epoch: 16 [6144/10284]	Loss: 0.2408	LR: 0.020000
Training Epoch: 16 [6400/10284]	Loss: 0.1840	LR: 0.020000
Training Epoch: 16 [6656/10284]	Loss: 0.2290	LR: 0.020000
Training Epoch: 16 [6912/10284]	Loss: 0.1766	LR: 0.020000
Training Epoch: 16 [7168/10284]	Loss: 0.2376	LR: 0.020000
Training Epoch: 16 [7424/10284]	Loss: 0.2345	LR: 0.020000
Training Epoch: 16 [7680/10284]	Loss: 0.1909	LR: 0.020000
Training Epoch: 16 [7936/10284]	Loss: 0.1753	LR: 0.020000
Training Epoch: 16 [8192/10284]	Loss: 0.1963	LR: 0.020000
Training Epoch: 16 [8448/10284]	Loss: 0.1840	LR: 0.020000
Training Epoch: 16 [8704/10284]	Loss: 0.1982	LR: 0.020000
Training Epoch: 16 [8960/10284]	Loss: 0.1856	LR: 0.020000
Training Epoch: 16 [9216/10284]	Loss: 0.1906	LR: 0.020000
Training Epoch: 16 [9472/10284]	Loss: 0.2205	LR: 0.020000
Training Epoch: 16 [9728/10284]	Loss: 0.2868	LR: 0.020000
Training Epoch: 16 [9984/10284]	Loss: 0.1979	LR: 0.020000
Training Epoch: 16 [10240/10284]	Loss: 0.2161	LR: 0.020000
Training Epoch: 16 [10284/10284]	Loss: 0.3218	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2182, Train Accuracy: 0.9098
Epoch 16 training time consumed: 153.57s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0008, Accuracy: 0.9278, Time consumed:8.22s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-16-best.pth
Training Epoch: 17 [256/10284]	Loss: 0.1927	LR: 0.020000
Training Epoch: 17 [512/10284]	Loss: 0.2361	LR: 0.020000
Training Epoch: 17 [768/10284]	Loss: 0.2986	LR: 0.020000
Training Epoch: 17 [1024/10284]	Loss: 0.1664	LR: 0.020000
Training Epoch: 17 [1280/10284]	Loss: 0.2097	LR: 0.020000
Training Epoch: 17 [1536/10284]	Loss: 0.1417	LR: 0.020000
Training Epoch: 17 [1792/10284]	Loss: 0.2056	LR: 0.020000
Training Epoch: 17 [2048/10284]	Loss: 0.2419	LR: 0.020000
Training Epoch: 17 [2304/10284]	Loss: 0.2036	LR: 0.020000
Training Epoch: 17 [2560/10284]	Loss: 0.1693	LR: 0.020000
Training Epoch: 17 [2816/10284]	Loss: 0.2507	LR: 0.020000
Training Epoch: 17 [3072/10284]	Loss: 0.1794	LR: 0.020000
Training Epoch: 17 [3328/10284]	Loss: 0.2731	LR: 0.020000
Training Epoch: 17 [3584/10284]	Loss: 0.2213	LR: 0.020000
Training Epoch: 17 [3840/10284]	Loss: 0.2243	LR: 0.020000
Training Epoch: 17 [4096/10284]	Loss: 0.2956	LR: 0.020000
Training Epoch: 17 [4352/10284]	Loss: 0.2289	LR: 0.020000
Training Epoch: 17 [4608/10284]	Loss: 0.1665	LR: 0.020000
Training Epoch: 17 [4864/10284]	Loss: 0.1589	LR: 0.020000
Training Epoch: 17 [5120/10284]	Loss: 0.2246	LR: 0.020000
Training Epoch: 17 [5376/10284]	Loss: 0.2427	LR: 0.020000
Training Epoch: 17 [5632/10284]	Loss: 0.2377	LR: 0.020000
Training Epoch: 17 [5888/10284]	Loss: 0.2177	LR: 0.020000
Training Epoch: 17 [6144/10284]	Loss: 0.2011	LR: 0.020000
Training Epoch: 17 [6400/10284]	Loss: 0.1954	LR: 0.020000
Training Epoch: 17 [6656/10284]	Loss: 0.2555	LR: 0.020000
Training Epoch: 17 [6912/10284]	Loss: 0.2391	LR: 0.020000
Training Epoch: 17 [7168/10284]	Loss: 0.1859	LR: 0.020000
Training Epoch: 17 [7424/10284]	Loss: 0.2119	LR: 0.020000
Training Epoch: 17 [7680/10284]	Loss: 0.2276	LR: 0.020000
Training Epoch: 17 [7936/10284]	Loss: 0.2444	LR: 0.020000
Training Epoch: 17 [8192/10284]	Loss: 0.2185	LR: 0.020000
Training Epoch: 17 [8448/10284]	Loss: 0.1922	LR: 0.020000
Training Epoch: 17 [8704/10284]	Loss: 0.1964	LR: 0.020000
Training Epoch: 17 [8960/10284]	Loss: 0.2321	LR: 0.020000
Training Epoch: 17 [9216/10284]	Loss: 0.2040	LR: 0.020000
Training Epoch: 17 [9472/10284]	Loss: 0.2249	LR: 0.020000
Training Epoch: 17 [9728/10284]	Loss: 0.2122	LR: 0.020000
Training Epoch: 17 [9984/10284]	Loss: 0.1765	LR: 0.020000
Training Epoch: 17 [10240/10284]	Loss: 0.1582	LR: 0.020000
Training Epoch: 17 [10284/10284]	Loss: 0.1611	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2138, Train Accuracy: 0.9123
Epoch 17 training time consumed: 153.19s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0010, Accuracy: 0.8993, Time consumed:8.23s
Training Epoch: 18 [256/10284]	Loss: 0.1830	LR: 0.020000
Training Epoch: 18 [512/10284]	Loss: 0.2445	LR: 0.020000
Training Epoch: 18 [768/10284]	Loss: 0.1602	LR: 0.020000
Training Epoch: 18 [1024/10284]	Loss: 0.2221	LR: 0.020000
Training Epoch: 18 [1280/10284]	Loss: 0.1785	LR: 0.020000
Training Epoch: 18 [1536/10284]	Loss: 0.1676	LR: 0.020000
Training Epoch: 18 [1792/10284]	Loss: 0.1738	LR: 0.020000
Training Epoch: 18 [2048/10284]	Loss: 0.2240	LR: 0.020000
Training Epoch: 18 [2304/10284]	Loss: 0.1705	LR: 0.020000
Training Epoch: 18 [2560/10284]	Loss: 0.2407	LR: 0.020000
Training Epoch: 18 [2816/10284]	Loss: 0.2176	LR: 0.020000
Training Epoch: 18 [3072/10284]	Loss: 0.1912	LR: 0.020000
Training Epoch: 18 [3328/10284]	Loss: 0.3316	LR: 0.020000
Training Epoch: 18 [3584/10284]	Loss: 0.1725	LR: 0.020000
Training Epoch: 18 [3840/10284]	Loss: 0.2215	LR: 0.020000
Training Epoch: 18 [4096/10284]	Loss: 0.2097	LR: 0.020000
Training Epoch: 18 [4352/10284]	Loss: 0.2122	LR: 0.020000
Training Epoch: 18 [4608/10284]	Loss: 0.1893	LR: 0.020000
Training Epoch: 18 [4864/10284]	Loss: 0.1998	LR: 0.020000
Training Epoch: 18 [5120/10284]	Loss: 0.2189	LR: 0.020000
Training Epoch: 18 [5376/10284]	Loss: 0.2554	LR: 0.020000
Training Epoch: 18 [5632/10284]	Loss: 0.1855	LR: 0.020000
Training Epoch: 18 [5888/10284]	Loss: 0.2182	LR: 0.020000
Training Epoch: 18 [6144/10284]	Loss: 0.2376	LR: 0.020000
Training Epoch: 18 [6400/10284]	Loss: 0.1684	LR: 0.020000
Training Epoch: 18 [6656/10284]	Loss: 0.1781	LR: 0.020000
Training Epoch: 18 [6912/10284]	Loss: 0.2001	LR: 0.020000
Training Epoch: 18 [7168/10284]	Loss: 0.1809	LR: 0.020000
Training Epoch: 18 [7424/10284]	Loss: 0.1746	LR: 0.020000
Training Epoch: 18 [7680/10284]	Loss: 0.2293	LR: 0.020000
Training Epoch: 18 [7936/10284]	Loss: 0.2205	LR: 0.020000
Training Epoch: 18 [8192/10284]	Loss: 0.2244	LR: 0.020000
Training Epoch: 18 [8448/10284]	Loss: 0.1958	LR: 0.020000
Training Epoch: 18 [8704/10284]	Loss: 0.1736	LR: 0.020000
Training Epoch: 18 [8960/10284]	Loss: 0.2343	LR: 0.020000
Training Epoch: 18 [9216/10284]	Loss: 0.2169	LR: 0.020000
Training Epoch: 18 [9472/10284]	Loss: 0.1938	LR: 0.020000
Training Epoch: 18 [9728/10284]	Loss: 0.2164	LR: 0.020000
Training Epoch: 18 [9984/10284]	Loss: 0.1793	LR: 0.020000
Training Epoch: 18 [10240/10284]	Loss: 0.1952	LR: 0.020000
Training Epoch: 18 [10284/10284]	Loss: 0.2512	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2054, Train Accuracy: 0.9178
Epoch 18 training time consumed: 153.55s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0013, Accuracy: 0.8828, Time consumed:8.11s
Training Epoch: 19 [256/10284]	Loss: 0.2160	LR: 0.020000
Training Epoch: 19 [512/10284]	Loss: 0.2682	LR: 0.020000
Training Epoch: 19 [768/10284]	Loss: 0.2712	LR: 0.020000
Training Epoch: 19 [1024/10284]	Loss: 0.2455	LR: 0.020000
Training Epoch: 19 [1280/10284]	Loss: 0.1825	LR: 0.020000
Training Epoch: 19 [1536/10284]	Loss: 0.2213	LR: 0.020000
Training Epoch: 19 [1792/10284]	Loss: 0.2382	LR: 0.020000
Training Epoch: 19 [2048/10284]	Loss: 0.2009	LR: 0.020000
Training Epoch: 19 [2304/10284]	Loss: 0.2151	LR: 0.020000
Training Epoch: 19 [2560/10284]	Loss: 0.1910	LR: 0.020000
Training Epoch: 19 [2816/10284]	Loss: 0.1732	LR: 0.020000
Training Epoch: 19 [3072/10284]	Loss: 0.1844	LR: 0.020000
Training Epoch: 19 [3328/10284]	Loss: 0.2469	LR: 0.020000
Training Epoch: 19 [3584/10284]	Loss: 0.1436	LR: 0.020000
Training Epoch: 19 [3840/10284]	Loss: 0.1710	LR: 0.020000
Training Epoch: 19 [4096/10284]	Loss: 0.1880	LR: 0.020000
Training Epoch: 19 [4352/10284]	Loss: 0.1603	LR: 0.020000
Training Epoch: 19 [4608/10284]	Loss: 0.2081	LR: 0.020000
Training Epoch: 19 [4864/10284]	Loss: 0.1953	LR: 0.020000
Training Epoch: 19 [5120/10284]	Loss: 0.1919	LR: 0.020000
Training Epoch: 19 [5376/10284]	Loss: 0.1254	LR: 0.020000
Training Epoch: 19 [5632/10284]	Loss: 0.1844	LR: 0.020000
Training Epoch: 19 [5888/10284]	Loss: 0.1441	LR: 0.020000
Training Epoch: 19 [6144/10284]	Loss: 0.1764	LR: 0.020000
Training Epoch: 19 [6400/10284]	Loss: 0.1859	LR: 0.020000
Training Epoch: 19 [6656/10284]	Loss: 0.1661	LR: 0.020000
Training Epoch: 19 [6912/10284]	Loss: 0.2298	LR: 0.020000
Training Epoch: 19 [7168/10284]	Loss: 0.1879	LR: 0.020000
Training Epoch: 19 [7424/10284]	Loss: 0.1543	LR: 0.020000
Training Epoch: 19 [7680/10284]	Loss: 0.2064	LR: 0.020000
Training Epoch: 19 [7936/10284]	Loss: 0.2053	LR: 0.020000
Training Epoch: 19 [8192/10284]	Loss: 0.2001	LR: 0.020000
Training Epoch: 19 [8448/10284]	Loss: 0.2086	LR: 0.020000
Training Epoch: 19 [8704/10284]	Loss: 0.1453	LR: 0.020000
Training Epoch: 19 [8960/10284]	Loss: 0.2548	LR: 0.020000
Training Epoch: 19 [9216/10284]	Loss: 0.1497	LR: 0.020000
Training Epoch: 19 [9472/10284]	Loss: 0.2199	LR: 0.020000
Training Epoch: 19 [9728/10284]	Loss: 0.1574	LR: 0.020000
Training Epoch: 19 [9984/10284]	Loss: 0.1703	LR: 0.020000
Training Epoch: 19 [10240/10284]	Loss: 0.1586	LR: 0.020000
Training Epoch: 19 [10284/10284]	Loss: 0.1146	LR: 0.020000
Epoch 19 - Average Train Loss: 0.1932, Train Accuracy: 0.9218
Epoch 19 training time consumed: 153.42s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0010, Accuracy: 0.9046, Time consumed:8.13s
Training Epoch: 20 [256/10284]	Loss: 0.1321	LR: 0.004000
Training Epoch: 20 [512/10284]	Loss: 0.1367	LR: 0.004000
Training Epoch: 20 [768/10284]	Loss: 0.1523	LR: 0.004000
Training Epoch: 20 [1024/10284]	Loss: 0.1975	LR: 0.004000
Training Epoch: 20 [1280/10284]	Loss: 0.1541	LR: 0.004000
Training Epoch: 20 [1536/10284]	Loss: 0.1704	LR: 0.004000
Training Epoch: 20 [1792/10284]	Loss: 0.1578	LR: 0.004000
Training Epoch: 20 [2048/10284]	Loss: 0.2104	LR: 0.004000
Training Epoch: 20 [2304/10284]	Loss: 0.1355	LR: 0.004000
Training Epoch: 20 [2560/10284]	Loss: 0.1770	LR: 0.004000
Training Epoch: 20 [2816/10284]	Loss: 0.1996	LR: 0.004000
Training Epoch: 20 [3072/10284]	Loss: 0.1933	LR: 0.004000
Training Epoch: 20 [3328/10284]	Loss: 0.1273	LR: 0.004000
Training Epoch: 20 [3584/10284]	Loss: 0.1657	LR: 0.004000
Training Epoch: 20 [3840/10284]	Loss: 0.1663	LR: 0.004000
Training Epoch: 20 [4096/10284]	Loss: 0.1458	LR: 0.004000
Training Epoch: 20 [4352/10284]	Loss: 0.1467	LR: 0.004000
Training Epoch: 20 [4608/10284]	Loss: 0.1407	LR: 0.004000
Training Epoch: 20 [4864/10284]	Loss: 0.1664	LR: 0.004000
Training Epoch: 20 [5120/10284]	Loss: 0.1680	LR: 0.004000
Training Epoch: 20 [5376/10284]	Loss: 0.1682	LR: 0.004000
Training Epoch: 20 [5632/10284]	Loss: 0.1324	LR: 0.004000
Training Epoch: 20 [5888/10284]	Loss: 0.1799	LR: 0.004000
Training Epoch: 20 [6144/10284]	Loss: 0.2176	LR: 0.004000
Training Epoch: 20 [6400/10284]	Loss: 0.1620	LR: 0.004000
Training Epoch: 20 [6656/10284]	Loss: 0.1728	LR: 0.004000
Training Epoch: 20 [6912/10284]	Loss: 0.1423	LR: 0.004000
Training Epoch: 20 [7168/10284]	Loss: 0.1709	LR: 0.004000
Training Epoch: 20 [7424/10284]	Loss: 0.1973	LR: 0.004000
Training Epoch: 20 [7680/10284]	Loss: 0.2166	LR: 0.004000
Training Epoch: 20 [7936/10284]	Loss: 0.2319	LR: 0.004000
Training Epoch: 20 [8192/10284]	Loss: 0.1237	LR: 0.004000
Training Epoch: 20 [8448/10284]	Loss: 0.0882	LR: 0.004000
Training Epoch: 20 [8704/10284]	Loss: 0.1404	LR: 0.004000
Training Epoch: 20 [8960/10284]	Loss: 0.1071	LR: 0.004000
Training Epoch: 20 [9216/10284]	Loss: 0.1449	LR: 0.004000
Training Epoch: 20 [9472/10284]	Loss: 0.1830	LR: 0.004000
Training Epoch: 20 [9728/10284]	Loss: 0.1060	LR: 0.004000
Training Epoch: 20 [9984/10284]	Loss: 0.1224	LR: 0.004000
Training Epoch: 20 [10240/10284]	Loss: 0.1307	LR: 0.004000
Training Epoch: 20 [10284/10284]	Loss: 0.2493	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1599, Train Accuracy: 0.9324
Epoch 20 training time consumed: 153.32s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0007, Accuracy: 0.9293, Time consumed:8.18s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-20-best.pth
Training Epoch: 21 [256/10284]	Loss: 0.1438	LR: 0.004000
Training Epoch: 21 [512/10284]	Loss: 0.1536	LR: 0.004000
Training Epoch: 21 [768/10284]	Loss: 0.0965	LR: 0.004000
Training Epoch: 21 [1024/10284]	Loss: 0.1884	LR: 0.004000
Training Epoch: 21 [1280/10284]	Loss: 0.1535	LR: 0.004000
Training Epoch: 21 [1536/10284]	Loss: 0.1840	LR: 0.004000
Training Epoch: 21 [1792/10284]	Loss: 0.1289	LR: 0.004000
Training Epoch: 21 [2048/10284]	Loss: 0.1135	LR: 0.004000
Training Epoch: 21 [2304/10284]	Loss: 0.1099	LR: 0.004000
Training Epoch: 21 [2560/10284]	Loss: 0.1331	LR: 0.004000
Training Epoch: 21 [2816/10284]	Loss: 0.1920	LR: 0.004000
Training Epoch: 21 [3072/10284]	Loss: 0.1403	LR: 0.004000
Training Epoch: 21 [3328/10284]	Loss: 0.1325	LR: 0.004000
Training Epoch: 21 [3584/10284]	Loss: 0.1734	LR: 0.004000
Training Epoch: 21 [3840/10284]	Loss: 0.1500	LR: 0.004000
Training Epoch: 21 [4096/10284]	Loss: 0.1477	LR: 0.004000
Training Epoch: 21 [4352/10284]	Loss: 0.1091	LR: 0.004000
Training Epoch: 21 [4608/10284]	Loss: 0.1417	LR: 0.004000
Training Epoch: 21 [4864/10284]	Loss: 0.1652	LR: 0.004000
Training Epoch: 21 [5120/10284]	Loss: 0.1182	LR: 0.004000
Training Epoch: 21 [5376/10284]	Loss: 0.1905	LR: 0.004000
Training Epoch: 21 [5632/10284]	Loss: 0.1940	LR: 0.004000
Training Epoch: 21 [5888/10284]	Loss: 0.1635	LR: 0.004000
Training Epoch: 21 [6144/10284]	Loss: 0.1023	LR: 0.004000
Training Epoch: 21 [6400/10284]	Loss: 0.1636	LR: 0.004000
Training Epoch: 21 [6656/10284]	Loss: 0.1193	LR: 0.004000
Training Epoch: 21 [6912/10284]	Loss: 0.1133	LR: 0.004000
Training Epoch: 21 [7168/10284]	Loss: 0.1672	LR: 0.004000
Training Epoch: 21 [7424/10284]	Loss: 0.0871	LR: 0.004000
Training Epoch: 21 [7680/10284]	Loss: 0.1651	LR: 0.004000
Training Epoch: 21 [7936/10284]	Loss: 0.1249	LR: 0.004000
Training Epoch: 21 [8192/10284]	Loss: 0.1905	LR: 0.004000
Training Epoch: 21 [8448/10284]	Loss: 0.1556	LR: 0.004000
Training Epoch: 21 [8704/10284]	Loss: 0.1551	LR: 0.004000
Training Epoch: 21 [8960/10284]	Loss: 0.1552	LR: 0.004000
Training Epoch: 21 [9216/10284]	Loss: 0.1335	LR: 0.004000
Training Epoch: 21 [9472/10284]	Loss: 0.1319	LR: 0.004000
Training Epoch: 21 [9728/10284]	Loss: 0.1982	LR: 0.004000
Training Epoch: 21 [9984/10284]	Loss: 0.1534	LR: 0.004000
Training Epoch: 21 [10240/10284]	Loss: 0.1696	LR: 0.004000
Training Epoch: 21 [10284/10284]	Loss: 0.1260	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1476, Train Accuracy: 0.9390
Epoch 21 training time consumed: 153.66s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0006, Accuracy: 0.9433, Time consumed:8.27s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-21-best.pth
Training Epoch: 22 [256/10284]	Loss: 0.1420	LR: 0.004000
Training Epoch: 22 [512/10284]	Loss: 0.1538	LR: 0.004000
Training Epoch: 22 [768/10284]	Loss: 0.1852	LR: 0.004000
Training Epoch: 22 [1024/10284]	Loss: 0.1097	LR: 0.004000
Training Epoch: 22 [1280/10284]	Loss: 0.1581	LR: 0.004000
Training Epoch: 22 [1536/10284]	Loss: 0.1284	LR: 0.004000
Training Epoch: 22 [1792/10284]	Loss: 0.1452	LR: 0.004000
Training Epoch: 22 [2048/10284]	Loss: 0.1535	LR: 0.004000
Training Epoch: 22 [2304/10284]	Loss: 0.1423	LR: 0.004000
Training Epoch: 22 [2560/10284]	Loss: 0.0983	LR: 0.004000
Training Epoch: 22 [2816/10284]	Loss: 0.1362	LR: 0.004000
Training Epoch: 22 [3072/10284]	Loss: 0.1223	LR: 0.004000
Training Epoch: 22 [3328/10284]	Loss: 0.1198	LR: 0.004000
Training Epoch: 22 [3584/10284]	Loss: 0.1219	LR: 0.004000
Training Epoch: 22 [3840/10284]	Loss: 0.1538	LR: 0.004000
Training Epoch: 22 [4096/10284]	Loss: 0.1343	LR: 0.004000
Training Epoch: 22 [4352/10284]	Loss: 0.1352	LR: 0.004000
Training Epoch: 22 [4608/10284]	Loss: 0.1642	LR: 0.004000
Training Epoch: 22 [4864/10284]	Loss: 0.1699	LR: 0.004000
Training Epoch: 22 [5120/10284]	Loss: 0.1161	LR: 0.004000
Training Epoch: 22 [5376/10284]	Loss: 0.1204	LR: 0.004000
Training Epoch: 22 [5632/10284]	Loss: 0.1235	LR: 0.004000
Training Epoch: 22 [5888/10284]	Loss: 0.1794	LR: 0.004000
Training Epoch: 22 [6144/10284]	Loss: 0.1505	LR: 0.004000
Training Epoch: 22 [6400/10284]	Loss: 0.1032	LR: 0.004000
Training Epoch: 22 [6656/10284]	Loss: 0.1726	LR: 0.004000
Training Epoch: 22 [6912/10284]	Loss: 0.1832	LR: 0.004000
Training Epoch: 22 [7168/10284]	Loss: 0.1619	LR: 0.004000
Training Epoch: 22 [7424/10284]	Loss: 0.1207	LR: 0.004000
Training Epoch: 22 [7680/10284]	Loss: 0.1861	LR: 0.004000
Training Epoch: 22 [7936/10284]	Loss: 0.1531	LR: 0.004000
Training Epoch: 22 [8192/10284]	Loss: 0.1796	LR: 0.004000
Training Epoch: 22 [8448/10284]	Loss: 0.1484	LR: 0.004000
Training Epoch: 22 [8704/10284]	Loss: 0.1169	LR: 0.004000
Training Epoch: 22 [8960/10284]	Loss: 0.1483	LR: 0.004000
Training Epoch: 22 [9216/10284]	Loss: 0.1180	LR: 0.004000
Training Epoch: 22 [9472/10284]	Loss: 0.1746	LR: 0.004000
Training Epoch: 22 [9728/10284]	Loss: 0.1361	LR: 0.004000
Training Epoch: 22 [9984/10284]	Loss: 0.1379	LR: 0.004000
Training Epoch: 22 [10240/10284]	Loss: 0.1634	LR: 0.004000
Training Epoch: 22 [10284/10284]	Loss: 0.1760	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1443, Train Accuracy: 0.9407
Epoch 22 training time consumed: 153.45s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0006, Accuracy: 0.9366, Time consumed:8.15s
Training Epoch: 23 [256/10284]	Loss: 0.1578	LR: 0.004000
Training Epoch: 23 [512/10284]	Loss: 0.1065	LR: 0.004000
Training Epoch: 23 [768/10284]	Loss: 0.1807	LR: 0.004000
Training Epoch: 23 [1024/10284]	Loss: 0.1599	LR: 0.004000
Training Epoch: 23 [1280/10284]	Loss: 0.1456	LR: 0.004000
Training Epoch: 23 [1536/10284]	Loss: 0.1008	LR: 0.004000
Training Epoch: 23 [1792/10284]	Loss: 0.1642	LR: 0.004000
Training Epoch: 23 [2048/10284]	Loss: 0.1322	LR: 0.004000
Training Epoch: 23 [2304/10284]	Loss: 0.1707	LR: 0.004000
Training Epoch: 23 [2560/10284]	Loss: 0.1505	LR: 0.004000
Training Epoch: 23 [2816/10284]	Loss: 0.1377	LR: 0.004000
Training Epoch: 23 [3072/10284]	Loss: 0.1391	LR: 0.004000
Training Epoch: 23 [3328/10284]	Loss: 0.0983	LR: 0.004000
Training Epoch: 23 [3584/10284]	Loss: 0.1318	LR: 0.004000
Training Epoch: 23 [3840/10284]	Loss: 0.1378	LR: 0.004000
Training Epoch: 23 [4096/10284]	Loss: 0.1621	LR: 0.004000
Training Epoch: 23 [4352/10284]	Loss: 0.0934	LR: 0.004000
Training Epoch: 23 [4608/10284]	Loss: 0.1399	LR: 0.004000
Training Epoch: 23 [4864/10284]	Loss: 0.1317	LR: 0.004000
Training Epoch: 23 [5120/10284]	Loss: 0.1764	LR: 0.004000
Training Epoch: 23 [5376/10284]	Loss: 0.1602	LR: 0.004000
Training Epoch: 23 [5632/10284]	Loss: 0.2178	LR: 0.004000
Training Epoch: 23 [5888/10284]	Loss: 0.1665	LR: 0.004000
Training Epoch: 23 [6144/10284]	Loss: 0.1182	LR: 0.004000
Training Epoch: 23 [6400/10284]	Loss: 0.1391	LR: 0.004000
Training Epoch: 23 [6656/10284]	Loss: 0.1299	LR: 0.004000
Training Epoch: 23 [6912/10284]	Loss: 0.1128	LR: 0.004000
Training Epoch: 23 [7168/10284]	Loss: 0.1282	LR: 0.004000
Training Epoch: 23 [7424/10284]	Loss: 0.1478	LR: 0.004000
Training Epoch: 23 [7680/10284]	Loss: 0.1529	LR: 0.004000
Training Epoch: 23 [7936/10284]	Loss: 0.1675	LR: 0.004000
Training Epoch: 23 [8192/10284]	Loss: 0.1463	LR: 0.004000
Training Epoch: 23 [8448/10284]	Loss: 0.1466	LR: 0.004000
Training Epoch: 23 [8704/10284]	Loss: 0.1389	LR: 0.004000
Training Epoch: 23 [8960/10284]	Loss: 0.1396	LR: 0.004000
Training Epoch: 23 [9216/10284]	Loss: 0.1785	LR: 0.004000
Training Epoch: 23 [9472/10284]	Loss: 0.1286	LR: 0.004000
Training Epoch: 23 [9728/10284]	Loss: 0.1568	LR: 0.004000
Training Epoch: 23 [9984/10284]	Loss: 0.1858	LR: 0.004000
Training Epoch: 23 [10240/10284]	Loss: 0.1040	LR: 0.004000
Training Epoch: 23 [10284/10284]	Loss: 0.1397	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1446, Train Accuracy: 0.9406
Epoch 23 training time consumed: 153.62s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9400, Time consumed:8.10s
Training Epoch: 24 [256/10284]	Loss: 0.1522	LR: 0.004000
Training Epoch: 24 [512/10284]	Loss: 0.1428	LR: 0.004000
Training Epoch: 24 [768/10284]	Loss: 0.1345	LR: 0.004000
Training Epoch: 24 [1024/10284]	Loss: 0.1432	LR: 0.004000
Training Epoch: 24 [1280/10284]	Loss: 0.1251	LR: 0.004000
Training Epoch: 24 [1536/10284]	Loss: 0.1212	LR: 0.004000
Training Epoch: 24 [1792/10284]	Loss: 0.1600	LR: 0.004000
Training Epoch: 24 [2048/10284]	Loss: 0.1112	LR: 0.004000
Training Epoch: 24 [2304/10284]	Loss: 0.1303	LR: 0.004000
Training Epoch: 24 [2560/10284]	Loss: 0.1603	LR: 0.004000
Training Epoch: 24 [2816/10284]	Loss: 0.1122	LR: 0.004000
Training Epoch: 24 [3072/10284]	Loss: 0.1699	LR: 0.004000
Training Epoch: 24 [3328/10284]	Loss: 0.1375	LR: 0.004000
Training Epoch: 24 [3584/10284]	Loss: 0.1384	LR: 0.004000
Training Epoch: 24 [3840/10284]	Loss: 0.1918	LR: 0.004000
Training Epoch: 24 [4096/10284]	Loss: 0.1568	LR: 0.004000
Training Epoch: 24 [4352/10284]	Loss: 0.1633	LR: 0.004000
Training Epoch: 24 [4608/10284]	Loss: 0.1131	LR: 0.004000
Training Epoch: 24 [4864/10284]	Loss: 0.2022	LR: 0.004000
Training Epoch: 24 [5120/10284]	Loss: 0.1493	LR: 0.004000
Training Epoch: 24 [5376/10284]	Loss: 0.0941	LR: 0.004000
Training Epoch: 24 [5632/10284]	Loss: 0.1305	LR: 0.004000
Training Epoch: 24 [5888/10284]	Loss: 0.1081	LR: 0.004000
Training Epoch: 24 [6144/10284]	Loss: 0.1172	LR: 0.004000
Training Epoch: 24 [6400/10284]	Loss: 0.1316	LR: 0.004000
Training Epoch: 24 [6656/10284]	Loss: 0.0787	LR: 0.004000
Training Epoch: 24 [6912/10284]	Loss: 0.1433	LR: 0.004000
Training Epoch: 24 [7168/10284]	Loss: 0.1640	LR: 0.004000
Training Epoch: 24 [7424/10284]	Loss: 0.1604	LR: 0.004000
Training Epoch: 24 [7680/10284]	Loss: 0.1453	LR: 0.004000
Training Epoch: 24 [7936/10284]	Loss: 0.1819	LR: 0.004000
Training Epoch: 24 [8192/10284]	Loss: 0.1596	LR: 0.004000
Training Epoch: 24 [8448/10284]	Loss: 0.1418	LR: 0.004000
Training Epoch: 24 [8704/10284]	Loss: 0.1808	LR: 0.004000
Training Epoch: 24 [8960/10284]	Loss: 0.1607	LR: 0.004000
Training Epoch: 24 [9216/10284]	Loss: 0.1581	LR: 0.004000
Training Epoch: 24 [9472/10284]	Loss: 0.1498	LR: 0.004000
Training Epoch: 24 [9728/10284]	Loss: 0.1177	LR: 0.004000
Training Epoch: 24 [9984/10284]	Loss: 0.1518	LR: 0.004000
Training Epoch: 24 [10240/10284]	Loss: 0.1412	LR: 0.004000
Training Epoch: 24 [10284/10284]	Loss: 0.1772	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1434, Train Accuracy: 0.9422
Epoch 24 training time consumed: 153.39s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0007, Accuracy: 0.9361, Time consumed:8.40s
Training Epoch: 25 [256/10284]	Loss: 0.1200	LR: 0.004000
Training Epoch: 25 [512/10284]	Loss: 0.1455	LR: 0.004000
Training Epoch: 25 [768/10284]	Loss: 0.1264	LR: 0.004000
Training Epoch: 25 [1024/10284]	Loss: 0.1164	LR: 0.004000
Training Epoch: 25 [1280/10284]	Loss: 0.1179	LR: 0.004000
Training Epoch: 25 [1536/10284]	Loss: 0.1568	LR: 0.004000
Training Epoch: 25 [1792/10284]	Loss: 0.1461	LR: 0.004000
Training Epoch: 25 [2048/10284]	Loss: 0.1206	LR: 0.004000
Training Epoch: 25 [2304/10284]	Loss: 0.1688	LR: 0.004000
Training Epoch: 25 [2560/10284]	Loss: 0.1219	LR: 0.004000
Training Epoch: 25 [2816/10284]	Loss: 0.1660	LR: 0.004000
Training Epoch: 25 [3072/10284]	Loss: 0.1505	LR: 0.004000
Training Epoch: 25 [3328/10284]	Loss: 0.1313	LR: 0.004000
Training Epoch: 25 [3584/10284]	Loss: 0.1307	LR: 0.004000
Training Epoch: 25 [3840/10284]	Loss: 0.1021	LR: 0.004000
Training Epoch: 25 [4096/10284]	Loss: 0.0990	LR: 0.004000
Training Epoch: 25 [4352/10284]	Loss: 0.1363	LR: 0.004000
Training Epoch: 25 [4608/10284]	Loss: 0.1439	LR: 0.004000
Training Epoch: 25 [4864/10284]	Loss: 0.1482	LR: 0.004000
Training Epoch: 25 [5120/10284]	Loss: 0.0897	LR: 0.004000
Training Epoch: 25 [5376/10284]	Loss: 0.1246	LR: 0.004000
Training Epoch: 25 [5632/10284]	Loss: 0.1123	LR: 0.004000
Training Epoch: 25 [5888/10284]	Loss: 0.1730	LR: 0.004000
Training Epoch: 25 [6144/10284]	Loss: 0.1114	LR: 0.004000
Training Epoch: 25 [6400/10284]	Loss: 0.1215	LR: 0.004000
Training Epoch: 25 [6656/10284]	Loss: 0.1129	LR: 0.004000
Training Epoch: 25 [6912/10284]	Loss: 0.1584	LR: 0.004000
Training Epoch: 25 [7168/10284]	Loss: 0.1150	LR: 0.004000
Training Epoch: 25 [7424/10284]	Loss: 0.1240	LR: 0.004000
Training Epoch: 25 [7680/10284]	Loss: 0.1549	LR: 0.004000
Training Epoch: 25 [7936/10284]	Loss: 0.1497	LR: 0.004000
Training Epoch: 25 [8192/10284]	Loss: 0.1086	LR: 0.004000
Training Epoch: 25 [8448/10284]	Loss: 0.1333	LR: 0.004000
Training Epoch: 25 [8704/10284]	Loss: 0.1168	LR: 0.004000
Training Epoch: 25 [8960/10284]	Loss: 0.1498	LR: 0.004000
Training Epoch: 25 [9216/10284]	Loss: 0.1696	LR: 0.004000
Training Epoch: 25 [9472/10284]	Loss: 0.1416	LR: 0.004000
Training Epoch: 25 [9728/10284]	Loss: 0.1477	LR: 0.004000
Training Epoch: 25 [9984/10284]	Loss: 0.1407	LR: 0.004000
Training Epoch: 25 [10240/10284]	Loss: 0.1912	LR: 0.004000
Training Epoch: 25 [10284/10284]	Loss: 0.1058	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1348, Train Accuracy: 0.9456
Epoch 25 training time consumed: 153.66s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0007, Accuracy: 0.9269, Time consumed:8.15s
Training Epoch: 26 [256/10284]	Loss: 0.1752	LR: 0.004000
Training Epoch: 26 [512/10284]	Loss: 0.1475	LR: 0.004000
Training Epoch: 26 [768/10284]	Loss: 0.1632	LR: 0.004000
Training Epoch: 26 [1024/10284]	Loss: 0.0966	LR: 0.004000
Training Epoch: 26 [1280/10284]	Loss: 0.2010	LR: 0.004000
Training Epoch: 26 [1536/10284]	Loss: 0.1665	LR: 0.004000
Training Epoch: 26 [1792/10284]	Loss: 0.1295	LR: 0.004000
Training Epoch: 26 [2048/10284]	Loss: 0.1153	LR: 0.004000
Training Epoch: 26 [2304/10284]	Loss: 0.1108	LR: 0.004000
Training Epoch: 26 [2560/10284]	Loss: 0.1243	LR: 0.004000
Training Epoch: 26 [2816/10284]	Loss: 0.1779	LR: 0.004000
Training Epoch: 26 [3072/10284]	Loss: 0.1377	LR: 0.004000
Training Epoch: 26 [3328/10284]	Loss: 0.1017	LR: 0.004000
Training Epoch: 26 [3584/10284]	Loss: 0.1139	LR: 0.004000
Training Epoch: 26 [3840/10284]	Loss: 0.0723	LR: 0.004000
Training Epoch: 26 [4096/10284]	Loss: 0.1591	LR: 0.004000
Training Epoch: 26 [4352/10284]	Loss: 0.1664	LR: 0.004000
Training Epoch: 26 [4608/10284]	Loss: 0.1309	LR: 0.004000
Training Epoch: 26 [4864/10284]	Loss: 0.1373	LR: 0.004000
Training Epoch: 26 [5120/10284]	Loss: 0.1079	LR: 0.004000
Training Epoch: 26 [5376/10284]	Loss: 0.1383	LR: 0.004000
Training Epoch: 26 [5632/10284]	Loss: 0.1139	LR: 0.004000
Training Epoch: 26 [5888/10284]	Loss: 0.1868	LR: 0.004000
Training Epoch: 26 [6144/10284]	Loss: 0.0974	LR: 0.004000
Training Epoch: 26 [6400/10284]	Loss: 0.1651	LR: 0.004000
Training Epoch: 26 [6656/10284]	Loss: 0.1423	LR: 0.004000
Training Epoch: 26 [6912/10284]	Loss: 0.1518	LR: 0.004000
Training Epoch: 26 [7168/10284]	Loss: 0.1880	LR: 0.004000
Training Epoch: 26 [7424/10284]	Loss: 0.1346	LR: 0.004000
Training Epoch: 26 [7680/10284]	Loss: 0.1528	LR: 0.004000
Training Epoch: 26 [7936/10284]	Loss: 0.1761	LR: 0.004000
Training Epoch: 26 [8192/10284]	Loss: 0.1076	LR: 0.004000
Training Epoch: 26 [8448/10284]	Loss: 0.0943	LR: 0.004000
Training Epoch: 26 [8704/10284]	Loss: 0.1216	LR: 0.004000
Training Epoch: 26 [8960/10284]	Loss: 0.1689	LR: 0.004000
Training Epoch: 26 [9216/10284]	Loss: 0.1017	LR: 0.004000
Training Epoch: 26 [9472/10284]	Loss: 0.1672	LR: 0.004000
Training Epoch: 26 [9728/10284]	Loss: 0.1186	LR: 0.004000
Training Epoch: 26 [9984/10284]	Loss: 0.1187	LR: 0.004000
Training Epoch: 26 [10240/10284]	Loss: 0.1605	LR: 0.004000
Training Epoch: 26 [10284/10284]	Loss: 0.2098	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1388, Train Accuracy: 0.9425
Epoch 26 training time consumed: 153.22s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0007, Accuracy: 0.9312, Time consumed:8.36s
Training Epoch: 27 [256/10284]	Loss: 0.1333	LR: 0.004000
Training Epoch: 27 [512/10284]	Loss: 0.1096	LR: 0.004000
Training Epoch: 27 [768/10284]	Loss: 0.1222	LR: 0.004000
Training Epoch: 27 [1024/10284]	Loss: 0.1415	LR: 0.004000
Training Epoch: 27 [1280/10284]	Loss: 0.1453	LR: 0.004000
Training Epoch: 27 [1536/10284]	Loss: 0.1442	LR: 0.004000
Training Epoch: 27 [1792/10284]	Loss: 0.1742	LR: 0.004000
Training Epoch: 27 [2048/10284]	Loss: 0.0830	LR: 0.004000
Training Epoch: 27 [2304/10284]	Loss: 0.1536	LR: 0.004000
Training Epoch: 27 [2560/10284]	Loss: 0.1679	LR: 0.004000
Training Epoch: 27 [2816/10284]	Loss: 0.1511	LR: 0.004000
Training Epoch: 27 [3072/10284]	Loss: 0.1003	LR: 0.004000
Training Epoch: 27 [3328/10284]	Loss: 0.1306	LR: 0.004000
Training Epoch: 27 [3584/10284]	Loss: 0.1229	LR: 0.004000
Training Epoch: 27 [3840/10284]	Loss: 0.0957	LR: 0.004000
Training Epoch: 27 [4096/10284]	Loss: 0.1274	LR: 0.004000
Training Epoch: 27 [4352/10284]	Loss: 0.0783	LR: 0.004000
Training Epoch: 27 [4608/10284]	Loss: 0.1499	LR: 0.004000
Training Epoch: 27 [4864/10284]	Loss: 0.1514	LR: 0.004000
Training Epoch: 27 [5120/10284]	Loss: 0.1977	LR: 0.004000
Training Epoch: 27 [5376/10284]	Loss: 0.1490	LR: 0.004000
Training Epoch: 27 [5632/10284]	Loss: 0.0898	LR: 0.004000
Training Epoch: 27 [5888/10284]	Loss: 0.1387	LR: 0.004000
Training Epoch: 27 [6144/10284]	Loss: 0.1301	LR: 0.004000
Training Epoch: 27 [6400/10284]	Loss: 0.0899	LR: 0.004000
Training Epoch: 27 [6656/10284]	Loss: 0.0928	LR: 0.004000
Training Epoch: 27 [6912/10284]	Loss: 0.1500	LR: 0.004000
Training Epoch: 27 [7168/10284]	Loss: 0.2810	LR: 0.004000
Training Epoch: 27 [7424/10284]	Loss: 0.1466	LR: 0.004000
Training Epoch: 27 [7680/10284]	Loss: 0.1333	LR: 0.004000
Training Epoch: 27 [7936/10284]	Loss: 0.1877	LR: 0.004000
Training Epoch: 27 [8192/10284]	Loss: 0.1005	LR: 0.004000
Training Epoch: 27 [8448/10284]	Loss: 0.1579	LR: 0.004000
Training Epoch: 27 [8704/10284]	Loss: 0.1303	LR: 0.004000
Training Epoch: 27 [8960/10284]	Loss: 0.1041	LR: 0.004000
Training Epoch: 27 [9216/10284]	Loss: 0.1152	LR: 0.004000
Training Epoch: 27 [9472/10284]	Loss: 0.1971	LR: 0.004000
Training Epoch: 27 [9728/10284]	Loss: 0.1302	LR: 0.004000
Training Epoch: 27 [9984/10284]	Loss: 0.1017	LR: 0.004000
Training Epoch: 27 [10240/10284]	Loss: 0.1036	LR: 0.004000
Training Epoch: 27 [10284/10284]	Loss: 0.2493	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1357, Train Accuracy: 0.9436
Epoch 27 training time consumed: 152.40s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0007, Accuracy: 0.9298, Time consumed:8.08s
Training Epoch: 28 [256/10284]	Loss: 0.1713	LR: 0.004000
Training Epoch: 28 [512/10284]	Loss: 0.1466	LR: 0.004000
Training Epoch: 28 [768/10284]	Loss: 0.0940	LR: 0.004000
Training Epoch: 28 [1024/10284]	Loss: 0.2228	LR: 0.004000
Training Epoch: 28 [1280/10284]	Loss: 0.0905	LR: 0.004000
Training Epoch: 28 [1536/10284]	Loss: 0.1954	LR: 0.004000
Training Epoch: 28 [1792/10284]	Loss: 0.1317	LR: 0.004000
Training Epoch: 28 [2048/10284]	Loss: 0.1476	LR: 0.004000
Training Epoch: 28 [2304/10284]	Loss: 0.1349	LR: 0.004000
Training Epoch: 28 [2560/10284]	Loss: 0.1473	LR: 0.004000
Training Epoch: 28 [2816/10284]	Loss: 0.1100	LR: 0.004000
Training Epoch: 28 [3072/10284]	Loss: 0.1030	LR: 0.004000
Training Epoch: 28 [3328/10284]	Loss: 0.1355	LR: 0.004000
Training Epoch: 28 [3584/10284]	Loss: 0.1451	LR: 0.004000
Training Epoch: 28 [3840/10284]	Loss: 0.0960	LR: 0.004000
Training Epoch: 28 [4096/10284]	Loss: 0.1522	LR: 0.004000
Training Epoch: 28 [4352/10284]	Loss: 0.1359	LR: 0.004000
Training Epoch: 28 [4608/10284]	Loss: 0.1250	LR: 0.004000
Training Epoch: 28 [4864/10284]	Loss: 0.1379	LR: 0.004000
Training Epoch: 28 [5120/10284]	Loss: 0.1211	LR: 0.004000
Training Epoch: 28 [5376/10284]	Loss: 0.1084	LR: 0.004000
Training Epoch: 28 [5632/10284]	Loss: 0.1256	LR: 0.004000
Training Epoch: 28 [5888/10284]	Loss: 0.1502	LR: 0.004000
Training Epoch: 28 [6144/10284]	Loss: 0.1118	LR: 0.004000
Training Epoch: 28 [6400/10284]	Loss: 0.1737	LR: 0.004000
Training Epoch: 28 [6656/10284]	Loss: 0.1587	LR: 0.004000
Training Epoch: 28 [6912/10284]	Loss: 0.0897	LR: 0.004000
Training Epoch: 28 [7168/10284]	Loss: 0.1316	LR: 0.004000
Training Epoch: 28 [7424/10284]	Loss: 0.1178	LR: 0.004000
Training Epoch: 28 [7680/10284]	Loss: 0.1002	LR: 0.004000
Training Epoch: 28 [7936/10284]	Loss: 0.1068	LR: 0.004000
Training Epoch: 28 [8192/10284]	Loss: 0.1360	LR: 0.004000
Training Epoch: 28 [8448/10284]	Loss: 0.1207	LR: 0.004000
Training Epoch: 28 [8704/10284]	Loss: 0.1784	LR: 0.004000
Training Epoch: 28 [8960/10284]	Loss: 0.1487	LR: 0.004000
Training Epoch: 28 [9216/10284]	Loss: 0.1277	LR: 0.004000
Training Epoch: 28 [9472/10284]	Loss: 0.1791	LR: 0.004000
Training Epoch: 28 [9728/10284]	Loss: 0.1148	LR: 0.004000
Training Epoch: 28 [9984/10284]	Loss: 0.1111	LR: 0.004000
Training Epoch: 28 [10240/10284]	Loss: 0.1083	LR: 0.004000
Training Epoch: 28 [10284/10284]	Loss: 0.1907	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1338, Train Accuracy: 0.9448
Epoch 28 training time consumed: 152.80s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0005, Accuracy: 0.9438, Time consumed:8.13s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_02h_24m_51s/ResNet18-MUCAC-seed9-ret75-28-best.pth
Training Epoch: 29 [256/10284]	Loss: 0.1265	LR: 0.004000
Training Epoch: 29 [512/10284]	Loss: 0.1538	LR: 0.004000
Training Epoch: 29 [768/10284]	Loss: 0.1028	LR: 0.004000
Training Epoch: 29 [1024/10284]	Loss: 0.1242	LR: 0.004000
Training Epoch: 29 [1280/10284]	Loss: 0.1158	LR: 0.004000
Training Epoch: 29 [1536/10284]	Loss: 0.1422	LR: 0.004000
Training Epoch: 29 [1792/10284]	Loss: 0.1091	LR: 0.004000
Training Epoch: 29 [2048/10284]	Loss: 0.1171	LR: 0.004000
Training Epoch: 29 [2304/10284]	Loss: 0.1177	LR: 0.004000
Training Epoch: 29 [2560/10284]	Loss: 0.1410	LR: 0.004000
Training Epoch: 29 [2816/10284]	Loss: 0.1437	LR: 0.004000
Training Epoch: 29 [3072/10284]	Loss: 0.1396	LR: 0.004000
Training Epoch: 29 [3328/10284]	Loss: 0.1307	LR: 0.004000
Training Epoch: 29 [3584/10284]	Loss: 0.1596	LR: 0.004000
Training Epoch: 29 [3840/10284]	Loss: 0.1451	LR: 0.004000
Training Epoch: 29 [4096/10284]	Loss: 0.1091	LR: 0.004000
Training Epoch: 29 [4352/10284]	Loss: 0.0960	LR: 0.004000
Training Epoch: 29 [4608/10284]	Loss: 0.1272	LR: 0.004000
Training Epoch: 29 [4864/10284]	Loss: 0.1346	LR: 0.004000
Training Epoch: 29 [5120/10284]	Loss: 0.1016	LR: 0.004000
Training Epoch: 29 [5376/10284]	Loss: 0.1507	LR: 0.004000
Training Epoch: 29 [5632/10284]	Loss: 0.1345	LR: 0.004000
Training Epoch: 29 [5888/10284]	Loss: 0.0793	LR: 0.004000
Training Epoch: 29 [6144/10284]	Loss: 0.1420	LR: 0.004000
Training Epoch: 29 [6400/10284]	Loss: 0.1416	LR: 0.004000
Training Epoch: 29 [6656/10284]	Loss: 0.1195	LR: 0.004000
Training Epoch: 29 [6912/10284]	Loss: 0.1286	LR: 0.004000
Training Epoch: 29 [7168/10284]	Loss: 0.1538	LR: 0.004000
Training Epoch: 29 [7424/10284]	Loss: 0.1001	LR: 0.004000
Training Epoch: 29 [7680/10284]	Loss: 0.1587	LR: 0.004000
Training Epoch: 29 [7936/10284]	Loss: 0.1380	LR: 0.004000
Training Epoch: 29 [8192/10284]	Loss: 0.1418	LR: 0.004000
Training Epoch: 29 [8448/10284]	Loss: 0.1307	LR: 0.004000
Training Epoch: 29 [8704/10284]	Loss: 0.1241	LR: 0.004000
Training Epoch: 29 [8960/10284]	Loss: 0.1179	LR: 0.004000
Training Epoch: 29 [9216/10284]	Loss: 0.1610	LR: 0.004000
Training Epoch: 29 [9472/10284]	Loss: 0.1304	LR: 0.004000
Training Epoch: 29 [9728/10284]	Loss: 0.1005	LR: 0.004000
Training Epoch: 29 [9984/10284]	Loss: 0.0978	LR: 0.004000
Training Epoch: 29 [10240/10284]	Loss: 0.1317	LR: 0.004000
Training Epoch: 29 [10284/10284]	Loss: 0.2025	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1283, Train Accuracy: 0.9474
Epoch 29 training time consumed: 153.00s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0007, Accuracy: 0.9312, Time consumed:8.35s
Training Epoch: 30 [256/10284]	Loss: 0.1144	LR: 0.004000
Training Epoch: 30 [512/10284]	Loss: 0.1216	LR: 0.004000
Training Epoch: 30 [768/10284]	Loss: 0.1307	LR: 0.004000
Training Epoch: 30 [1024/10284]	Loss: 0.1315	LR: 0.004000
Training Epoch: 30 [1280/10284]	Loss: 0.0940	LR: 0.004000
Training Epoch: 30 [1536/10284]	Loss: 0.1388	LR: 0.004000
Training Epoch: 30 [1792/10284]	Loss: 0.1471	LR: 0.004000
Training Epoch: 30 [2048/10284]	Loss: 0.1244	LR: 0.004000
Training Epoch: 30 [2304/10284]	Loss: 0.1099	LR: 0.004000
Training Epoch: 30 [2560/10284]	Loss: 0.0882	LR: 0.004000
Training Epoch: 30 [2816/10284]	Loss: 0.0936	LR: 0.004000
Training Epoch: 30 [3072/10284]	Loss: 0.1129	LR: 0.004000
Training Epoch: 30 [3328/10284]	Loss: 0.1368	LR: 0.004000
Training Epoch: 30 [3584/10284]	Loss: 0.1400	LR: 0.004000
Training Epoch: 30 [3840/10284]	Loss: 0.1441	LR: 0.004000
Training Epoch: 30 [4096/10284]	Loss: 0.1263	LR: 0.004000
Training Epoch: 30 [4352/10284]	Loss: 0.1184	LR: 0.004000
Training Epoch: 30 [4608/10284]	Loss: 0.1336	LR: 0.004000
Training Epoch: 30 [4864/10284]	Loss: 0.1674	LR: 0.004000
Training Epoch: 30 [5120/10284]	Loss: 0.1402	LR: 0.004000
Training Epoch: 30 [5376/10284]	Loss: 0.1837	LR: 0.004000
Training Epoch: 30 [5632/10284]	Loss: 0.1811	LR: 0.004000
Training Epoch: 30 [5888/10284]	Loss: 0.1039	LR: 0.004000
Training Epoch: 30 [6144/10284]	Loss: 0.1180	LR: 0.004000
Training Epoch: 30 [6400/10284]	Loss: 0.1497	LR: 0.004000
Training Epoch: 30 [6656/10284]	Loss: 0.1292	LR: 0.004000
Training Epoch: 30 [6912/10284]	Loss: 0.1003	LR: 0.004000
Training Epoch: 30 [7168/10284]	Loss: 0.1649	LR: 0.004000
Training Epoch: 30 [7424/10284]	Loss: 0.1445	LR: 0.004000
Training Epoch: 30 [7680/10284]	Loss: 0.1659	LR: 0.004000
Training Epoch: 30 [7936/10284]	Loss: 0.1264	LR: 0.004000
Training Epoch: 30 [8192/10284]	Loss: 0.1398	LR: 0.004000
Training Epoch: 30 [8448/10284]	Loss: 0.1084	LR: 0.004000
Training Epoch: 30 [8704/10284]	Loss: 0.1297	LR: 0.004000
Training Epoch: 30 [8960/10284]	Loss: 0.1259	LR: 0.004000
Training Epoch: 30 [9216/10284]	Loss: 0.1032	LR: 0.004000
Training Epoch: 30 [9472/10284]	Loss: 0.1474	LR: 0.004000
Training Epoch: 30 [9728/10284]	Loss: 0.1565	LR: 0.004000
Training Epoch: 30 [9984/10284]	Loss: 0.1512	LR: 0.004000
Training Epoch: 30 [10240/10284]	Loss: 0.1534	LR: 0.004000
Training Epoch: 30 [10284/10284]	Loss: 0.0900	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1322, Train Accuracy: 0.9455
Epoch 30 training time consumed: 153.17s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0008, Accuracy: 0.9293, Time consumed:8.26s
Training Epoch: 31 [256/10284]	Loss: 0.1487	LR: 0.004000
Training Epoch: 31 [512/10284]	Loss: 0.0996	LR: 0.004000
Training Epoch: 31 [768/10284]	Loss: 0.1482	LR: 0.004000
Training Epoch: 31 [1024/10284]	Loss: 0.1708	LR: 0.004000
Training Epoch: 31 [1280/10284]	Loss: 0.1573	LR: 0.004000
Training Epoch: 31 [1536/10284]	Loss: 0.0995	LR: 0.004000
Training Epoch: 31 [1792/10284]	Loss: 0.1676	LR: 0.004000
Training Epoch: 31 [2048/10284]	Loss: 0.1256	LR: 0.004000
Training Epoch: 31 [2304/10284]	Loss: 0.1213	LR: 0.004000
Training Epoch: 31 [2560/10284]	Loss: 0.1805	LR: 0.004000
Training Epoch: 31 [2816/10284]	Loss: 0.0923	LR: 0.004000
Training Epoch: 31 [3072/10284]	Loss: 0.1105	LR: 0.004000
Training Epoch: 31 [3328/10284]	Loss: 0.1180	LR: 0.004000
Training Epoch: 31 [3584/10284]	Loss: 0.1538	LR: 0.004000
Training Epoch: 31 [3840/10284]	Loss: 0.1523	LR: 0.004000
Training Epoch: 31 [4096/10284]	Loss: 0.1183	LR: 0.004000
Training Epoch: 31 [4352/10284]	Loss: 0.1189	LR: 0.004000
Training Epoch: 31 [4608/10284]	Loss: 0.1604	LR: 0.004000
Training Epoch: 31 [4864/10284]	Loss: 0.1364	LR: 0.004000
Training Epoch: 31 [5120/10284]	Loss: 0.1458	LR: 0.004000
Training Epoch: 31 [5376/10284]	Loss: 0.1277	LR: 0.004000
Training Epoch: 31 [5632/10284]	Loss: 0.1277	LR: 0.004000
Training Epoch: 31 [5888/10284]	Loss: 0.1184	LR: 0.004000
Training Epoch: 31 [6144/10284]	Loss: 0.1626	LR: 0.004000
Training Epoch: 31 [6400/10284]	Loss: 0.1474	LR: 0.004000
Training Epoch: 31 [6656/10284]	Loss: 0.0888	LR: 0.004000
Training Epoch: 31 [6912/10284]	Loss: 0.1575	LR: 0.004000
Training Epoch: 31 [7168/10284]	Loss: 0.1069	LR: 0.004000
Training Epoch: 31 [7424/10284]	Loss: 0.0914	LR: 0.004000
Training Epoch: 31 [7680/10284]	Loss: 0.1069	LR: 0.004000
Training Epoch: 31 [7936/10284]	Loss: 0.1729	LR: 0.004000
Training Epoch: 31 [8192/10284]	Loss: 0.0976	LR: 0.004000
Training Epoch: 31 [8448/10284]	Loss: 0.1721	LR: 0.004000
Training Epoch: 31 [8704/10284]	Loss: 0.1221	LR: 0.004000
Training Epoch: 31 [8960/10284]	Loss: 0.1242	LR: 0.004000
Training Epoch: 31 [9216/10284]	Loss: 0.1286	LR: 0.004000
Training Epoch: 31 [9472/10284]	Loss: 0.1259	LR: 0.004000
Training Epoch: 31 [9728/10284]	Loss: 0.1423	LR: 0.004000
Training Epoch: 31 [9984/10284]	Loss: 0.1202	LR: 0.004000
Training Epoch: 31 [10240/10284]	Loss: 0.0979	LR: 0.004000
Training Epoch: 31 [10284/10284]	Loss: 0.1018	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1315, Train Accuracy: 0.9460
Epoch 31 training time consumed: 152.94s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9404, Time consumed:8.21s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  10284
Forget Train Dl:  264
Retain Valid Dl:  10284
Forget Valid Dl:  264
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 264 samples
Set1 Distribution: 264 samples
Set2 Distribution: 264 samples
Set1 Distribution: 264 samples
Set2 Distribution: 264 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 94.66146087646484
Retain Accuracy: 94.30779266357422
Zero-Retain Forget (ZRF): 0.7672780752182007
Membership Inference Attack (MIA): 0.2916666666666667
Forget vs Retain Membership Inference Attack (MIA): 0.46226415094339623
Forget vs Test Membership Inference Attack (MIA): 0.5660377358490566
Test vs Retain Membership Inference Attack (MIA): 0.5193704600484261
Train vs Test Membership Inference Attack (MIA): 0.5169491525423728
Forget Set Accuracy (Df): 90.4296875
Method Execution Time: 6215.96 seconds
