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

📌 S Retain class distribution for seed 8:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 8:
Class 0: 527
Class 1: 527

📊 Updated class distribution:
Retain set:
  Class 0: 5415
  Class 1: 4341
Forget set:
  Class 0: 396
  Class 1: 396
./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 [256/9756]	Loss: 0.7283	LR: 0.000000
Training Epoch: 1 [512/9756]	Loss: 0.7118	LR: 0.002564
Training Epoch: 1 [768/9756]	Loss: 0.7033	LR: 0.005128
Training Epoch: 1 [1024/9756]	Loss: 0.7612	LR: 0.007692
Training Epoch: 1 [1280/9756]	Loss: 0.7895	LR: 0.010256
Training Epoch: 1 [1536/9756]	Loss: 0.7176	LR: 0.012821
Training Epoch: 1 [1792/9756]	Loss: 0.8116	LR: 0.015385
Training Epoch: 1 [2048/9756]	Loss: 0.8746	LR: 0.017949
Training Epoch: 1 [2304/9756]	Loss: 0.7791	LR: 0.020513
Training Epoch: 1 [2560/9756]	Loss: 1.1917	LR: 0.023077
Training Epoch: 1 [2816/9756]	Loss: 0.6929	LR: 0.025641
Training Epoch: 1 [3072/9756]	Loss: 0.9167	LR: 0.028205
Training Epoch: 1 [3328/9756]	Loss: 1.2031	LR: 0.030769
Training Epoch: 1 [3584/9756]	Loss: 0.8007	LR: 0.033333
Training Epoch: 1 [3840/9756]	Loss: 1.0590	LR: 0.035897
Training Epoch: 1 [4096/9756]	Loss: 0.7898	LR: 0.038462
Training Epoch: 1 [4352/9756]	Loss: 0.9266	LR: 0.041026
Training Epoch: 1 [4608/9756]	Loss: 0.8033	LR: 0.043590
Training Epoch: 1 [4864/9756]	Loss: 0.7120	LR: 0.046154
Training Epoch: 1 [5120/9756]	Loss: 0.7314	LR: 0.048718
Training Epoch: 1 [5376/9756]	Loss: 0.7224	LR: 0.051282
Training Epoch: 1 [5632/9756]	Loss: 0.7082	LR: 0.053846
Training Epoch: 1 [5888/9756]	Loss: 0.6988	LR: 0.056410
Training Epoch: 1 [6144/9756]	Loss: 0.7292	LR: 0.058974
Training Epoch: 1 [6400/9756]	Loss: 0.7581	LR: 0.061538
Training Epoch: 1 [6656/9756]	Loss: 0.7000	LR: 0.064103
Training Epoch: 1 [6912/9756]	Loss: 0.8043	LR: 0.066667
Training Epoch: 1 [7168/9756]	Loss: 0.8876	LR: 0.069231
Training Epoch: 1 [7424/9756]	Loss: 0.7774	LR: 0.071795
Training Epoch: 1 [7680/9756]	Loss: 0.7600	LR: 0.074359
Training Epoch: 1 [7936/9756]	Loss: 0.8061	LR: 0.076923
Training Epoch: 1 [8192/9756]	Loss: 0.7188	LR: 0.079487
Training Epoch: 1 [8448/9756]	Loss: 0.8063	LR: 0.082051
Training Epoch: 1 [8704/9756]	Loss: 0.8716	LR: 0.084615
Training Epoch: 1 [8960/9756]	Loss: 0.7713	LR: 0.087179
Training Epoch: 1 [9216/9756]	Loss: 0.7044	LR: 0.089744
Training Epoch: 1 [9472/9756]	Loss: 0.7880	LR: 0.092308
Training Epoch: 1 [9728/9756]	Loss: 0.7995	LR: 0.094872
Training Epoch: 1 [9756/9756]	Loss: 0.7300	LR: 0.097436
Epoch 1 - Average Train Loss: 0.8028, Train Accuracy: 0.5069
Epoch 1 training time consumed: 345.57s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0083, Accuracy: 0.5540, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-1-best.pth
Training Epoch: 2 [256/9756]	Loss: 0.6945	LR: 0.100000
Training Epoch: 2 [512/9756]	Loss: 0.6955	LR: 0.100000
Training Epoch: 2 [768/9756]	Loss: 0.7175	LR: 0.100000
Training Epoch: 2 [1024/9756]	Loss: 0.7667	LR: 0.100000
Training Epoch: 2 [1280/9756]	Loss: 0.6884	LR: 0.100000
Training Epoch: 2 [1536/9756]	Loss: 0.7609	LR: 0.100000
Training Epoch: 2 [1792/9756]	Loss: 0.7167	LR: 0.100000
Training Epoch: 2 [2048/9756]	Loss: 0.7279	LR: 0.100000
Training Epoch: 2 [2304/9756]	Loss: 0.7802	LR: 0.100000
Training Epoch: 2 [2560/9756]	Loss: 0.7230	LR: 0.100000
Training Epoch: 2 [2816/9756]	Loss: 0.7785	LR: 0.100000
Training Epoch: 2 [3072/9756]	Loss: 0.6495	LR: 0.100000
Training Epoch: 2 [3328/9756]	Loss: 0.9040	LR: 0.100000
Training Epoch: 2 [3584/9756]	Loss: 0.7567	LR: 0.100000
Training Epoch: 2 [3840/9756]	Loss: 0.6927	LR: 0.100000
Training Epoch: 2 [4096/9756]	Loss: 0.8124	LR: 0.100000
Training Epoch: 2 [4352/9756]	Loss: 0.7178	LR: 0.100000
Training Epoch: 2 [4608/9756]	Loss: 0.7577	LR: 0.100000
Training Epoch: 2 [4864/9756]	Loss: 0.7577	LR: 0.100000
Training Epoch: 2 [5120/9756]	Loss: 0.7242	LR: 0.100000
Training Epoch: 2 [5376/9756]	Loss: 0.7200	LR: 0.100000
Training Epoch: 2 [5632/9756]	Loss: 0.7352	LR: 0.100000
Training Epoch: 2 [5888/9756]	Loss: 0.7892	LR: 0.100000
Training Epoch: 2 [6144/9756]	Loss: 0.8166	LR: 0.100000
Training Epoch: 2 [6400/9756]	Loss: 0.7126	LR: 0.100000
Training Epoch: 2 [6656/9756]	Loss: 0.6963	LR: 0.100000
Training Epoch: 2 [6912/9756]	Loss: 0.6664	LR: 0.100000
Training Epoch: 2 [7168/9756]	Loss: 0.7059	LR: 0.100000
Training Epoch: 2 [7424/9756]	Loss: 0.7580	LR: 0.100000
Training Epoch: 2 [7680/9756]	Loss: 0.7252	LR: 0.100000
Training Epoch: 2 [7936/9756]	Loss: 0.6516	LR: 0.100000
Training Epoch: 2 [8192/9756]	Loss: 0.7217	LR: 0.100000
Training Epoch: 2 [8448/9756]	Loss: 0.7549	LR: 0.100000
Training Epoch: 2 [8704/9756]	Loss: 1.1499	LR: 0.100000
Training Epoch: 2 [8960/9756]	Loss: 0.7347	LR: 0.100000
Training Epoch: 2 [9216/9756]	Loss: 0.7470	LR: 0.100000
Training Epoch: 2 [9472/9756]	Loss: 1.3751	LR: 0.100000
Training Epoch: 2 [9728/9756]	Loss: 1.0818	LR: 0.100000
Training Epoch: 2 [9756/9756]	Loss: 0.8152	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7729, Train Accuracy: 0.5397
Epoch 2 training time consumed: 141.95s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.1204, Accuracy: 0.4450, Time consumed:8.31s
Training Epoch: 3 [256/9756]	Loss: 0.9637	LR: 0.100000
Training Epoch: 3 [512/9756]	Loss: 1.3769	LR: 0.100000
Training Epoch: 3 [768/9756]	Loss: 0.8900	LR: 0.100000
Training Epoch: 3 [1024/9756]	Loss: 0.7171	LR: 0.100000
Training Epoch: 3 [1280/9756]	Loss: 0.7794	LR: 0.100000
Training Epoch: 3 [1536/9756]	Loss: 0.8836	LR: 0.100000
Training Epoch: 3 [1792/9756]	Loss: 0.8267	LR: 0.100000
Training Epoch: 3 [2048/9756]	Loss: 0.7066	LR: 0.100000
Training Epoch: 3 [2304/9756]	Loss: 0.8039	LR: 0.100000
Training Epoch: 3 [2560/9756]	Loss: 0.6964	LR: 0.100000
Training Epoch: 3 [2816/9756]	Loss: 0.7611	LR: 0.100000
Training Epoch: 3 [3072/9756]	Loss: 0.7626	LR: 0.100000
Training Epoch: 3 [3328/9756]	Loss: 0.6617	LR: 0.100000
Training Epoch: 3 [3584/9756]	Loss: 0.6882	LR: 0.100000
Training Epoch: 3 [3840/9756]	Loss: 0.6840	LR: 0.100000
Training Epoch: 3 [4096/9756]	Loss: 0.7207	LR: 0.100000
Training Epoch: 3 [4352/9756]	Loss: 0.6663	LR: 0.100000
Training Epoch: 3 [4608/9756]	Loss: 0.6939	LR: 0.100000
Training Epoch: 3 [4864/9756]	Loss: 0.7060	LR: 0.100000
Training Epoch: 3 [5120/9756]	Loss: 0.7000	LR: 0.100000
Training Epoch: 3 [5376/9756]	Loss: 0.6841	LR: 0.100000
Training Epoch: 3 [5632/9756]	Loss: 0.7036	LR: 0.100000
Training Epoch: 3 [5888/9756]	Loss: 0.7401	LR: 0.100000
Training Epoch: 3 [6144/9756]	Loss: 0.6786	LR: 0.100000
Training Epoch: 3 [6400/9756]	Loss: 0.6602	LR: 0.100000
Training Epoch: 3 [6656/9756]	Loss: 0.7251	LR: 0.100000
Training Epoch: 3 [6912/9756]	Loss: 0.7052	LR: 0.100000
Training Epoch: 3 [7168/9756]	Loss: 0.6966	LR: 0.100000
Training Epoch: 3 [7424/9756]	Loss: 0.7327	LR: 0.100000
Training Epoch: 3 [7680/9756]	Loss: 0.6964	LR: 0.100000
Training Epoch: 3 [7936/9756]	Loss: 0.7501	LR: 0.100000
Training Epoch: 3 [8192/9756]	Loss: 0.7044	LR: 0.100000
Training Epoch: 3 [8448/9756]	Loss: 0.6894	LR: 0.100000
Training Epoch: 3 [8704/9756]	Loss: 0.6989	LR: 0.100000
Training Epoch: 3 [8960/9756]	Loss: 0.7486	LR: 0.100000
Training Epoch: 3 [9216/9756]	Loss: 0.6871	LR: 0.100000
Training Epoch: 3 [9472/9756]	Loss: 0.6659	LR: 0.100000
Training Epoch: 3 [9728/9756]	Loss: 0.6897	LR: 0.100000
Training Epoch: 3 [9756/9756]	Loss: 0.7791	LR: 0.100000
Epoch 3 - Average Train Loss: 0.7460, Train Accuracy: 0.5315
Epoch 3 training time consumed: 141.40s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0034, Accuracy: 0.5588, Time consumed:7.97s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-3-best.pth
Training Epoch: 4 [256/9756]	Loss: 0.7226	LR: 0.100000
Training Epoch: 4 [512/9756]	Loss: 0.7052	LR: 0.100000
Training Epoch: 4 [768/9756]	Loss: 0.7046	LR: 0.100000
Training Epoch: 4 [1024/9756]	Loss: 0.7191	LR: 0.100000
Training Epoch: 4 [1280/9756]	Loss: 0.7971	LR: 0.100000
Training Epoch: 4 [1536/9756]	Loss: 0.7191	LR: 0.100000
Training Epoch: 4 [1792/9756]	Loss: 0.7184	LR: 0.100000
Training Epoch: 4 [2048/9756]	Loss: 0.6798	LR: 0.100000
Training Epoch: 4 [2304/9756]	Loss: 0.7500	LR: 0.100000
Training Epoch: 4 [2560/9756]	Loss: 0.6937	LR: 0.100000
Training Epoch: 4 [2816/9756]	Loss: 0.7649	LR: 0.100000
Training Epoch: 4 [3072/9756]	Loss: 0.7726	LR: 0.100000
Training Epoch: 4 [3328/9756]	Loss: 0.7220	LR: 0.100000
Training Epoch: 4 [3584/9756]	Loss: 0.6878	LR: 0.100000
Training Epoch: 4 [3840/9756]	Loss: 0.6997	LR: 0.100000
Training Epoch: 4 [4096/9756]	Loss: 0.7283	LR: 0.100000
Training Epoch: 4 [4352/9756]	Loss: 0.6923	LR: 0.100000
Training Epoch: 4 [4608/9756]	Loss: 0.6989	LR: 0.100000
Training Epoch: 4 [4864/9756]	Loss: 0.6720	LR: 0.100000
Training Epoch: 4 [5120/9756]	Loss: 0.7430	LR: 0.100000
Training Epoch: 4 [5376/9756]	Loss: 0.7085	LR: 0.100000
Training Epoch: 4 [5632/9756]	Loss: 0.6910	LR: 0.100000
Training Epoch: 4 [5888/9756]	Loss: 0.6708	LR: 0.100000
Training Epoch: 4 [6144/9756]	Loss: 0.7064	LR: 0.100000
Training Epoch: 4 [6400/9756]	Loss: 0.6684	LR: 0.100000
Training Epoch: 4 [6656/9756]	Loss: 0.7214	LR: 0.100000
Training Epoch: 4 [6912/9756]	Loss: 0.7014	LR: 0.100000
Training Epoch: 4 [7168/9756]	Loss: 0.6775	LR: 0.100000
Training Epoch: 4 [7424/9756]	Loss: 0.6691	LR: 0.100000
Training Epoch: 4 [7680/9756]	Loss: 0.6780	LR: 0.100000
Training Epoch: 4 [7936/9756]	Loss: 0.6469	LR: 0.100000
Training Epoch: 4 [8192/9756]	Loss: 0.6592	LR: 0.100000
Training Epoch: 4 [8448/9756]	Loss: 0.6686	LR: 0.100000
Training Epoch: 4 [8704/9756]	Loss: 0.7015	LR: 0.100000
Training Epoch: 4 [8960/9756]	Loss: 0.6696	LR: 0.100000
Training Epoch: 4 [9216/9756]	Loss: 0.6974	LR: 0.100000
Training Epoch: 4 [9472/9756]	Loss: 0.6702	LR: 0.100000
Training Epoch: 4 [9728/9756]	Loss: 0.6473	LR: 0.100000
Training Epoch: 4 [9756/9756]	Loss: 0.6267	LR: 0.100000
Epoch 4 - Average Train Loss: 0.7009, Train Accuracy: 0.5586
Epoch 4 training time consumed: 140.90s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0031, Accuracy: 0.5458, Time consumed:7.93s
Training Epoch: 5 [256/9756]	Loss: 0.6690	LR: 0.100000
Training Epoch: 5 [512/9756]	Loss: 0.7092	LR: 0.100000
Training Epoch: 5 [768/9756]	Loss: 0.6707	LR: 0.100000
Training Epoch: 5 [1024/9756]	Loss: 0.6615	LR: 0.100000
Training Epoch: 5 [1280/9756]	Loss: 0.6919	LR: 0.100000
Training Epoch: 5 [1536/9756]	Loss: 0.7087	LR: 0.100000
Training Epoch: 5 [1792/9756]	Loss: 0.6927	LR: 0.100000
Training Epoch: 5 [2048/9756]	Loss: 0.6822	LR: 0.100000
Training Epoch: 5 [2304/9756]	Loss: 0.6928	LR: 0.100000
Training Epoch: 5 [2560/9756]	Loss: 0.6728	LR: 0.100000
Training Epoch: 5 [2816/9756]	Loss: 0.7288	LR: 0.100000
Training Epoch: 5 [3072/9756]	Loss: 0.7092	LR: 0.100000
Training Epoch: 5 [3328/9756]	Loss: 0.6787	LR: 0.100000
Training Epoch: 5 [3584/9756]	Loss: 0.6935	LR: 0.100000
Training Epoch: 5 [3840/9756]	Loss: 0.6763	LR: 0.100000
Training Epoch: 5 [4096/9756]	Loss: 0.6986	LR: 0.100000
Training Epoch: 5 [4352/9756]	Loss: 0.6858	LR: 0.100000
Training Epoch: 5 [4608/9756]	Loss: 0.6775	LR: 0.100000
Training Epoch: 5 [4864/9756]	Loss: 0.7026	LR: 0.100000
Training Epoch: 5 [5120/9756]	Loss: 0.6653	LR: 0.100000
Training Epoch: 5 [5376/9756]	Loss: 0.6876	LR: 0.100000
Training Epoch: 5 [5632/9756]	Loss: 0.6857	LR: 0.100000
Training Epoch: 5 [5888/9756]	Loss: 0.6770	LR: 0.100000
Training Epoch: 5 [6144/9756]	Loss: 0.6989	LR: 0.100000
Training Epoch: 5 [6400/9756]	Loss: 0.6633	LR: 0.100000
Training Epoch: 5 [6656/9756]	Loss: 0.7065	LR: 0.100000
Training Epoch: 5 [6912/9756]	Loss: 0.6680	LR: 0.100000
Training Epoch: 5 [7168/9756]	Loss: 0.6835	LR: 0.100000
Training Epoch: 5 [7424/9756]	Loss: 0.6453	LR: 0.100000
Training Epoch: 5 [7680/9756]	Loss: 0.7045	LR: 0.100000
Training Epoch: 5 [7936/9756]	Loss: 0.6950	LR: 0.100000
Training Epoch: 5 [8192/9756]	Loss: 0.6797	LR: 0.100000
Training Epoch: 5 [8448/9756]	Loss: 0.6820	LR: 0.100000
Training Epoch: 5 [8704/9756]	Loss: 0.6785	LR: 0.100000
Training Epoch: 5 [8960/9756]	Loss: 0.6899	LR: 0.100000
Training Epoch: 5 [9216/9756]	Loss: 0.6716	LR: 0.100000
Training Epoch: 5 [9472/9756]	Loss: 0.6784	LR: 0.100000
Training Epoch: 5 [9728/9756]	Loss: 0.6768	LR: 0.100000
Training Epoch: 5 [9756/9756]	Loss: 0.6963	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6853, Train Accuracy: 0.5629
Epoch 5 training time consumed: 141.15s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0031, Accuracy: 0.5530, Time consumed:8.20s
Training Epoch: 6 [256/9756]	Loss: 0.6610	LR: 0.100000
Training Epoch: 6 [512/9756]	Loss: 0.6876	LR: 0.100000
Training Epoch: 6 [768/9756]	Loss: 0.6691	LR: 0.100000
Training Epoch: 6 [1024/9756]	Loss: 0.6803	LR: 0.100000
Training Epoch: 6 [1280/9756]	Loss: 0.6700	LR: 0.100000
Training Epoch: 6 [1536/9756]	Loss: 0.6596	LR: 0.100000
Training Epoch: 6 [1792/9756]	Loss: 0.6942	LR: 0.100000
Training Epoch: 6 [2048/9756]	Loss: 0.6533	LR: 0.100000
Training Epoch: 6 [2304/9756]	Loss: 0.6890	LR: 0.100000
Training Epoch: 6 [2560/9756]	Loss: 0.6753	LR: 0.100000
Training Epoch: 6 [2816/9756]	Loss: 0.6836	LR: 0.100000
Training Epoch: 6 [3072/9756]	Loss: 0.6390	LR: 0.100000
Training Epoch: 6 [3328/9756]	Loss: 0.6640	LR: 0.100000
Training Epoch: 6 [3584/9756]	Loss: 0.6950	LR: 0.100000
Training Epoch: 6 [3840/9756]	Loss: 0.6556	LR: 0.100000
Training Epoch: 6 [4096/9756]	Loss: 0.6899	LR: 0.100000
Training Epoch: 6 [4352/9756]	Loss: 0.6634	LR: 0.100000
Training Epoch: 6 [4608/9756]	Loss: 0.6616	LR: 0.100000
Training Epoch: 6 [4864/9756]	Loss: 0.6651	LR: 0.100000
Training Epoch: 6 [5120/9756]	Loss: 0.6560	LR: 0.100000
Training Epoch: 6 [5376/9756]	Loss: 0.6592	LR: 0.100000
Training Epoch: 6 [5632/9756]	Loss: 0.6568	LR: 0.100000
Training Epoch: 6 [5888/9756]	Loss: 0.6354	LR: 0.100000
Training Epoch: 6 [6144/9756]	Loss: 0.6762	LR: 0.100000
Training Epoch: 6 [6400/9756]	Loss: 0.6494	LR: 0.100000
Training Epoch: 6 [6656/9756]	Loss: 0.6928	LR: 0.100000
Training Epoch: 6 [6912/9756]	Loss: 0.6918	LR: 0.100000
Training Epoch: 6 [7168/9756]	Loss: 0.6879	LR: 0.100000
Training Epoch: 6 [7424/9756]	Loss: 0.6808	LR: 0.100000
Training Epoch: 6 [7680/9756]	Loss: 0.6719	LR: 0.100000
Training Epoch: 6 [7936/9756]	Loss: 0.6983	LR: 0.100000
Training Epoch: 6 [8192/9756]	Loss: 0.6945	LR: 0.100000
Training Epoch: 6 [8448/9756]	Loss: 0.6950	LR: 0.100000
Training Epoch: 6 [8704/9756]	Loss: 0.6641	LR: 0.100000
Training Epoch: 6 [8960/9756]	Loss: 0.6636	LR: 0.100000
Training Epoch: 6 [9216/9756]	Loss: 0.6799	LR: 0.100000
Training Epoch: 6 [9472/9756]	Loss: 0.6728	LR: 0.100000
Training Epoch: 6 [9728/9756]	Loss: 0.6783	LR: 0.100000
Training Epoch: 6 [9756/9756]	Loss: 0.6509	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6726, Train Accuracy: 0.5919
Epoch 6 training time consumed: 141.28s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0029, Accuracy: 0.6024, Time consumed:8.04s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-6-best.pth
Training Epoch: 7 [256/9756]	Loss: 0.6707	LR: 0.100000
Training Epoch: 7 [512/9756]	Loss: 0.6807	LR: 0.100000
Training Epoch: 7 [768/9756]	Loss: 0.6644	LR: 0.100000
Training Epoch: 7 [1024/9756]	Loss: 0.6339	LR: 0.100000
Training Epoch: 7 [1280/9756]	Loss: 0.6386	LR: 0.100000
Training Epoch: 7 [1536/9756]	Loss: 0.6626	LR: 0.100000
Training Epoch: 7 [1792/9756]	Loss: 0.6591	LR: 0.100000
Training Epoch: 7 [2048/9756]	Loss: 0.6462	LR: 0.100000
Training Epoch: 7 [2304/9756]	Loss: 0.6871	LR: 0.100000
Training Epoch: 7 [2560/9756]	Loss: 0.6752	LR: 0.100000
Training Epoch: 7 [2816/9756]	Loss: 0.6978	LR: 0.100000
Training Epoch: 7 [3072/9756]	Loss: 0.6625	LR: 0.100000
Training Epoch: 7 [3328/9756]	Loss: 0.6723	LR: 0.100000
Training Epoch: 7 [3584/9756]	Loss: 0.6650	LR: 0.100000
Training Epoch: 7 [3840/9756]	Loss: 0.6575	LR: 0.100000
Training Epoch: 7 [4096/9756]	Loss: 0.6462	LR: 0.100000
Training Epoch: 7 [4352/9756]	Loss: 0.6441	LR: 0.100000
Training Epoch: 7 [4608/9756]	Loss: 0.6587	LR: 0.100000
Training Epoch: 7 [4864/9756]	Loss: 0.6735	LR: 0.100000
Training Epoch: 7 [5120/9756]	Loss: 0.6907	LR: 0.100000
Training Epoch: 7 [5376/9756]	Loss: 0.6756	LR: 0.100000
Training Epoch: 7 [5632/9756]	Loss: 0.6543	LR: 0.100000
Training Epoch: 7 [5888/9756]	Loss: 0.6597	LR: 0.100000
Training Epoch: 7 [6144/9756]	Loss: 0.6499	LR: 0.100000
Training Epoch: 7 [6400/9756]	Loss: 0.6717	LR: 0.100000
Training Epoch: 7 [6656/9756]	Loss: 0.6700	LR: 0.100000
Training Epoch: 7 [6912/9756]	Loss: 0.6448	LR: 0.100000
Training Epoch: 7 [7168/9756]	Loss: 0.7030	LR: 0.100000
Training Epoch: 7 [7424/9756]	Loss: 0.6732	LR: 0.100000
Training Epoch: 7 [7680/9756]	Loss: 0.6723	LR: 0.100000
Training Epoch: 7 [7936/9756]	Loss: 0.6675	LR: 0.100000
Training Epoch: 7 [8192/9756]	Loss: 0.6578	LR: 0.100000
Training Epoch: 7 [8448/9756]	Loss: 0.6466	LR: 0.100000
Training Epoch: 7 [8704/9756]	Loss: 0.6513	LR: 0.100000
Training Epoch: 7 [8960/9756]	Loss: 0.6693	LR: 0.100000
Training Epoch: 7 [9216/9756]	Loss: 0.6608	LR: 0.100000
Training Epoch: 7 [9472/9756]	Loss: 0.6594	LR: 0.100000
Training Epoch: 7 [9728/9756]	Loss: 0.6660	LR: 0.100000
Training Epoch: 7 [9756/9756]	Loss: 0.6204	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6641, Train Accuracy: 0.6097
Epoch 7 training time consumed: 141.43s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0031, Accuracy: 0.5656, Time consumed:7.81s
Training Epoch: 8 [256/9756]	Loss: 0.6538	LR: 0.100000
Training Epoch: 8 [512/9756]	Loss: 0.6459	LR: 0.100000
Training Epoch: 8 [768/9756]	Loss: 0.6811	LR: 0.100000
Training Epoch: 8 [1024/9756]	Loss: 0.6589	LR: 0.100000
Training Epoch: 8 [1280/9756]	Loss: 0.6345	LR: 0.100000
Training Epoch: 8 [1536/9756]	Loss: 0.6536	LR: 0.100000
Training Epoch: 8 [1792/9756]	Loss: 0.6371	LR: 0.100000
Training Epoch: 8 [2048/9756]	Loss: 0.6608	LR: 0.100000
Training Epoch: 8 [2304/9756]	Loss: 0.6644	LR: 0.100000
Training Epoch: 8 [2560/9756]	Loss: 0.6600	LR: 0.100000
Training Epoch: 8 [2816/9756]	Loss: 0.6643	LR: 0.100000
Training Epoch: 8 [3072/9756]	Loss: 0.6640	LR: 0.100000
Training Epoch: 8 [3328/9756]	Loss: 0.6835	LR: 0.100000
Training Epoch: 8 [3584/9756]	Loss: 0.6962	LR: 0.100000
Training Epoch: 8 [3840/9756]	Loss: 0.6486	LR: 0.100000
Training Epoch: 8 [4096/9756]	Loss: 0.6573	LR: 0.100000
Training Epoch: 8 [4352/9756]	Loss: 0.6622	LR: 0.100000
Training Epoch: 8 [4608/9756]	Loss: 0.6435	LR: 0.100000
Training Epoch: 8 [4864/9756]	Loss: 0.6953	LR: 0.100000
Training Epoch: 8 [5120/9756]	Loss: 0.7040	LR: 0.100000
Training Epoch: 8 [5376/9756]	Loss: 0.6622	LR: 0.100000
Training Epoch: 8 [5632/9756]	Loss: 0.6551	LR: 0.100000
Training Epoch: 8 [5888/9756]	Loss: 0.6718	LR: 0.100000
Training Epoch: 8 [6144/9756]	Loss: 0.6457	LR: 0.100000
Training Epoch: 8 [6400/9756]	Loss: 0.6504	LR: 0.100000
Training Epoch: 8 [6656/9756]	Loss: 0.6593	LR: 0.100000
Training Epoch: 8 [6912/9756]	Loss: 0.6727	LR: 0.100000
Training Epoch: 8 [7168/9756]	Loss: 0.6605	LR: 0.100000
Training Epoch: 8 [7424/9756]	Loss: 0.6593	LR: 0.100000
Training Epoch: 8 [7680/9756]	Loss: 0.6643	LR: 0.100000
Training Epoch: 8 [7936/9756]	Loss: 0.6451	LR: 0.100000
Training Epoch: 8 [8192/9756]	Loss: 0.6426	LR: 0.100000
Training Epoch: 8 [8448/9756]	Loss: 0.6585	LR: 0.100000
Training Epoch: 8 [8704/9756]	Loss: 0.6459	LR: 0.100000
Training Epoch: 8 [8960/9756]	Loss: 0.6415	LR: 0.100000
Training Epoch: 8 [9216/9756]	Loss: 0.6813	LR: 0.100000
Training Epoch: 8 [9472/9756]	Loss: 0.6408	LR: 0.100000
Training Epoch: 8 [9728/9756]	Loss: 0.6395	LR: 0.100000
Training Epoch: 8 [9756/9756]	Loss: 0.6276	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6595, Train Accuracy: 0.6187
Epoch 8 training time consumed: 141.35s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0030, Accuracy: 0.5763, Time consumed:7.99s
Training Epoch: 9 [256/9756]	Loss: 0.6634	LR: 0.100000
Training Epoch: 9 [512/9756]	Loss: 0.7006	LR: 0.100000
Training Epoch: 9 [768/9756]	Loss: 0.6888	LR: 0.100000
Training Epoch: 9 [1024/9756]	Loss: 0.6577	LR: 0.100000
Training Epoch: 9 [1280/9756]	Loss: 0.6639	LR: 0.100000
Training Epoch: 9 [1536/9756]	Loss: 0.6552	LR: 0.100000
Training Epoch: 9 [1792/9756]	Loss: 0.6467	LR: 0.100000
Training Epoch: 9 [2048/9756]	Loss: 0.6712	LR: 0.100000
Training Epoch: 9 [2304/9756]	Loss: 0.6694	LR: 0.100000
Training Epoch: 9 [2560/9756]	Loss: 0.6490	LR: 0.100000
Training Epoch: 9 [2816/9756]	Loss: 0.6488	LR: 0.100000
Training Epoch: 9 [3072/9756]	Loss: 0.6787	LR: 0.100000
Training Epoch: 9 [3328/9756]	Loss: 0.6513	LR: 0.100000
Training Epoch: 9 [3584/9756]	Loss: 0.6576	LR: 0.100000
Training Epoch: 9 [3840/9756]	Loss: 0.6171	LR: 0.100000
Training Epoch: 9 [4096/9756]	Loss: 0.6565	LR: 0.100000
Training Epoch: 9 [4352/9756]	Loss: 0.6530	LR: 0.100000
Training Epoch: 9 [4608/9756]	Loss: 0.6399	LR: 0.100000
Training Epoch: 9 [4864/9756]	Loss: 0.6257	LR: 0.100000
Training Epoch: 9 [5120/9756]	Loss: 0.6088	LR: 0.100000
Training Epoch: 9 [5376/9756]	Loss: 0.6108	LR: 0.100000
Training Epoch: 9 [5632/9756]	Loss: 0.6337	LR: 0.100000
Training Epoch: 9 [5888/9756]	Loss: 0.6340	LR: 0.100000
Training Epoch: 9 [6144/9756]	Loss: 0.6239	LR: 0.100000
Training Epoch: 9 [6400/9756]	Loss: 0.6414	LR: 0.100000
Training Epoch: 9 [6656/9756]	Loss: 0.6385	LR: 0.100000
Training Epoch: 9 [6912/9756]	Loss: 0.6327	LR: 0.100000
Training Epoch: 9 [7168/9756]	Loss: 0.6200	LR: 0.100000
Training Epoch: 9 [7424/9756]	Loss: 0.6276	LR: 0.100000
Training Epoch: 9 [7680/9756]	Loss: 0.6527	LR: 0.100000
Training Epoch: 9 [7936/9756]	Loss: 0.6060	LR: 0.100000
Training Epoch: 9 [8192/9756]	Loss: 0.6829	LR: 0.100000
Training Epoch: 9 [8448/9756]	Loss: 0.6708	LR: 0.100000
Training Epoch: 9 [8704/9756]	Loss: 0.6219	LR: 0.100000
Training Epoch: 9 [8960/9756]	Loss: 0.6130	LR: 0.100000
Training Epoch: 9 [9216/9756]	Loss: 0.5902	LR: 0.100000
Training Epoch: 9 [9472/9756]	Loss: 0.6259	LR: 0.100000
Training Epoch: 9 [9728/9756]	Loss: 0.6092	LR: 0.100000
Training Epoch: 9 [9756/9756]	Loss: 0.5697	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6429, Train Accuracy: 0.6396
Epoch 9 training time consumed: 141.40s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0028, Accuracy: 0.6305, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-9-best.pth
Training Epoch: 10 [256/9756]	Loss: 0.6171	LR: 0.020000
Training Epoch: 10 [512/9756]	Loss: 0.6306	LR: 0.020000
Training Epoch: 10 [768/9756]	Loss: 0.6142	LR: 0.020000
Training Epoch: 10 [1024/9756]	Loss: 0.5745	LR: 0.020000
Training Epoch: 10 [1280/9756]	Loss: 0.6163	LR: 0.020000
Training Epoch: 10 [1536/9756]	Loss: 0.6043	LR: 0.020000
Training Epoch: 10 [1792/9756]	Loss: 0.6019	LR: 0.020000
Training Epoch: 10 [2048/9756]	Loss: 0.6326	LR: 0.020000
Training Epoch: 10 [2304/9756]	Loss: 0.6493	LR: 0.020000
Training Epoch: 10 [2560/9756]	Loss: 0.6063	LR: 0.020000
Training Epoch: 10 [2816/9756]	Loss: 0.6305	LR: 0.020000
Training Epoch: 10 [3072/9756]	Loss: 0.6088	LR: 0.020000
Training Epoch: 10 [3328/9756]	Loss: 0.6273	LR: 0.020000
Training Epoch: 10 [3584/9756]	Loss: 0.5886	LR: 0.020000
Training Epoch: 10 [3840/9756]	Loss: 0.6252	LR: 0.020000
Training Epoch: 10 [4096/9756]	Loss: 0.6252	LR: 0.020000
Training Epoch: 10 [4352/9756]	Loss: 0.6435	LR: 0.020000
Training Epoch: 10 [4608/9756]	Loss: 0.6333	LR: 0.020000
Training Epoch: 10 [4864/9756]	Loss: 0.6078	LR: 0.020000
Training Epoch: 10 [5120/9756]	Loss: 0.6290	LR: 0.020000
Training Epoch: 10 [5376/9756]	Loss: 0.6000	LR: 0.020000
Training Epoch: 10 [5632/9756]	Loss: 0.5649	LR: 0.020000
Training Epoch: 10 [5888/9756]	Loss: 0.6381	LR: 0.020000
Training Epoch: 10 [6144/9756]	Loss: 0.5580	LR: 0.020000
Training Epoch: 10 [6400/9756]	Loss: 0.6218	LR: 0.020000
Training Epoch: 10 [6656/9756]	Loss: 0.6159	LR: 0.020000
Training Epoch: 10 [6912/9756]	Loss: 0.6192	LR: 0.020000
Training Epoch: 10 [7168/9756]	Loss: 0.5805	LR: 0.020000
Training Epoch: 10 [7424/9756]	Loss: 0.5741	LR: 0.020000
Training Epoch: 10 [7680/9756]	Loss: 0.5798	LR: 0.020000
Training Epoch: 10 [7936/9756]	Loss: 0.5679	LR: 0.020000
Training Epoch: 10 [8192/9756]	Loss: 0.6164	LR: 0.020000
Training Epoch: 10 [8448/9756]	Loss: 0.5608	LR: 0.020000
Training Epoch: 10 [8704/9756]	Loss: 0.6100	LR: 0.020000
Training Epoch: 10 [8960/9756]	Loss: 0.6358	LR: 0.020000
Training Epoch: 10 [9216/9756]	Loss: 0.6012	LR: 0.020000
Training Epoch: 10 [9472/9756]	Loss: 0.5745	LR: 0.020000
Training Epoch: 10 [9728/9756]	Loss: 0.5736	LR: 0.020000
Training Epoch: 10 [9756/9756]	Loss: 0.6363	LR: 0.020000
Epoch 10 - Average Train Loss: 0.6069, Train Accuracy: 0.6734
Epoch 10 training time consumed: 141.12s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0026, Accuracy: 0.7022, Time consumed:8.09s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-10-best.pth
Training Epoch: 11 [256/9756]	Loss: 0.5859	LR: 0.020000
Training Epoch: 11 [512/9756]	Loss: 0.5694	LR: 0.020000
Training Epoch: 11 [768/9756]	Loss: 0.6194	LR: 0.020000
Training Epoch: 11 [1024/9756]	Loss: 0.5760	LR: 0.020000
Training Epoch: 11 [1280/9756]	Loss: 0.6208	LR: 0.020000
Training Epoch: 11 [1536/9756]	Loss: 0.6369	LR: 0.020000
Training Epoch: 11 [1792/9756]	Loss: 0.5976	LR: 0.020000
Training Epoch: 11 [2048/9756]	Loss: 0.5363	LR: 0.020000
Training Epoch: 11 [2304/9756]	Loss: 0.6256	LR: 0.020000
Training Epoch: 11 [2560/9756]	Loss: 0.6015	LR: 0.020000
Training Epoch: 11 [2816/9756]	Loss: 0.6099	LR: 0.020000
Training Epoch: 11 [3072/9756]	Loss: 0.5601	LR: 0.020000
Training Epoch: 11 [3328/9756]	Loss: 0.5673	LR: 0.020000
Training Epoch: 11 [3584/9756]	Loss: 0.5714	LR: 0.020000
Training Epoch: 11 [3840/9756]	Loss: 0.5944	LR: 0.020000
Training Epoch: 11 [4096/9756]	Loss: 0.5021	LR: 0.020000
Training Epoch: 11 [4352/9756]	Loss: 0.5852	LR: 0.020000
Training Epoch: 11 [4608/9756]	Loss: 0.5921	LR: 0.020000
Training Epoch: 11 [4864/9756]	Loss: 0.5573	LR: 0.020000
Training Epoch: 11 [5120/9756]	Loss: 0.5628	LR: 0.020000
Training Epoch: 11 [5376/9756]	Loss: 0.5639	LR: 0.020000
Training Epoch: 11 [5632/9756]	Loss: 0.5443	LR: 0.020000
Training Epoch: 11 [5888/9756]	Loss: 0.5498	LR: 0.020000
Training Epoch: 11 [6144/9756]	Loss: 0.5935	LR: 0.020000
Training Epoch: 11 [6400/9756]	Loss: 0.6419	LR: 0.020000
Training Epoch: 11 [6656/9756]	Loss: 0.5618	LR: 0.020000
Training Epoch: 11 [6912/9756]	Loss: 0.5934	LR: 0.020000
Training Epoch: 11 [7168/9756]	Loss: 0.5850	LR: 0.020000
Training Epoch: 11 [7424/9756]	Loss: 0.5289	LR: 0.020000
Training Epoch: 11 [7680/9756]	Loss: 0.5546	LR: 0.020000
Training Epoch: 11 [7936/9756]	Loss: 0.5653	LR: 0.020000
Training Epoch: 11 [8192/9756]	Loss: 0.5375	LR: 0.020000
Training Epoch: 11 [8448/9756]	Loss: 0.5644	LR: 0.020000
Training Epoch: 11 [8704/9756]	Loss: 0.5642	LR: 0.020000
Training Epoch: 11 [8960/9756]	Loss: 0.5988	LR: 0.020000
Training Epoch: 11 [9216/9756]	Loss: 0.5901	LR: 0.020000
Training Epoch: 11 [9472/9756]	Loss: 0.5991	LR: 0.020000
Training Epoch: 11 [9728/9756]	Loss: 0.5773	LR: 0.020000
Training Epoch: 11 [9756/9756]	Loss: 0.6224	LR: 0.020000
Epoch 11 - Average Train Loss: 0.5787, Train Accuracy: 0.7051
Epoch 11 training time consumed: 141.76s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0025, Accuracy: 0.7153, Time consumed:7.95s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-11-best.pth
Training Epoch: 12 [256/9756]	Loss: 0.5602	LR: 0.020000
Training Epoch: 12 [512/9756]	Loss: 0.5979	LR: 0.020000
Training Epoch: 12 [768/9756]	Loss: 0.5315	LR: 0.020000
Training Epoch: 12 [1024/9756]	Loss: 0.5901	LR: 0.020000
Training Epoch: 12 [1280/9756]	Loss: 0.5499	LR: 0.020000
Training Epoch: 12 [1536/9756]	Loss: 0.5468	LR: 0.020000
Training Epoch: 12 [1792/9756]	Loss: 0.5714	LR: 0.020000
Training Epoch: 12 [2048/9756]	Loss: 0.5745	LR: 0.020000
Training Epoch: 12 [2304/9756]	Loss: 0.5198	LR: 0.020000
Training Epoch: 12 [2560/9756]	Loss: 0.5981	LR: 0.020000
Training Epoch: 12 [2816/9756]	Loss: 0.5331	LR: 0.020000
Training Epoch: 12 [3072/9756]	Loss: 0.4764	LR: 0.020000
Training Epoch: 12 [3328/9756]	Loss: 0.5407	LR: 0.020000
Training Epoch: 12 [3584/9756]	Loss: 0.5418	LR: 0.020000
Training Epoch: 12 [3840/9756]	Loss: 0.5711	LR: 0.020000
Training Epoch: 12 [4096/9756]	Loss: 0.4937	LR: 0.020000
Training Epoch: 12 [4352/9756]	Loss: 0.5638	LR: 0.020000
Training Epoch: 12 [4608/9756]	Loss: 0.5473	LR: 0.020000
Training Epoch: 12 [4864/9756]	Loss: 0.5676	LR: 0.020000
Training Epoch: 12 [5120/9756]	Loss: 0.5086	LR: 0.020000
Training Epoch: 12 [5376/9756]	Loss: 0.5324	LR: 0.020000
Training Epoch: 12 [5632/9756]	Loss: 0.5588	LR: 0.020000
Training Epoch: 12 [5888/9756]	Loss: 0.5077	LR: 0.020000
Training Epoch: 12 [6144/9756]	Loss: 0.5557	LR: 0.020000
Training Epoch: 12 [6400/9756]	Loss: 0.6416	LR: 0.020000
Training Epoch: 12 [6656/9756]	Loss: 0.5495	LR: 0.020000
Training Epoch: 12 [6912/9756]	Loss: 0.4893	LR: 0.020000
Training Epoch: 12 [7168/9756]	Loss: 0.5230	LR: 0.020000
Training Epoch: 12 [7424/9756]	Loss: 0.5286	LR: 0.020000
Training Epoch: 12 [7680/9756]	Loss: 0.5219	LR: 0.020000
Training Epoch: 12 [7936/9756]	Loss: 0.5671	LR: 0.020000
Training Epoch: 12 [8192/9756]	Loss: 0.4977	LR: 0.020000
Training Epoch: 12 [8448/9756]	Loss: 0.5390	LR: 0.020000
Training Epoch: 12 [8704/9756]	Loss: 0.5189	LR: 0.020000
Training Epoch: 12 [8960/9756]	Loss: 0.5484	LR: 0.020000
Training Epoch: 12 [9216/9756]	Loss: 0.5165	LR: 0.020000
Training Epoch: 12 [9472/9756]	Loss: 0.5440	LR: 0.020000
Training Epoch: 12 [9728/9756]	Loss: 0.5377	LR: 0.020000
Training Epoch: 12 [9756/9756]	Loss: 0.4627	LR: 0.020000
Epoch 12 - Average Train Loss: 0.5435, Train Accuracy: 0.7327
Epoch 12 training time consumed: 141.38s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0024, Accuracy: 0.7356, Time consumed:8.25s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-12-best.pth
Training Epoch: 13 [256/9756]	Loss: 0.5391	LR: 0.020000
Training Epoch: 13 [512/9756]	Loss: 0.5092	LR: 0.020000
Training Epoch: 13 [768/9756]	Loss: 0.4802	LR: 0.020000
Training Epoch: 13 [1024/9756]	Loss: 0.5256	LR: 0.020000
Training Epoch: 13 [1280/9756]	Loss: 0.4928	LR: 0.020000
Training Epoch: 13 [1536/9756]	Loss: 0.5073	LR: 0.020000
Training Epoch: 13 [1792/9756]	Loss: 0.5103	LR: 0.020000
Training Epoch: 13 [2048/9756]	Loss: 0.4794	LR: 0.020000
Training Epoch: 13 [2304/9756]	Loss: 0.4927	LR: 0.020000
Training Epoch: 13 [2560/9756]	Loss: 0.5345	LR: 0.020000
Training Epoch: 13 [2816/9756]	Loss: 0.4941	LR: 0.020000
Training Epoch: 13 [3072/9756]	Loss: 0.5044	LR: 0.020000
Training Epoch: 13 [3328/9756]	Loss: 0.5109	LR: 0.020000
Training Epoch: 13 [3584/9756]	Loss: 0.4951	LR: 0.020000
Training Epoch: 13 [3840/9756]	Loss: 0.5428	LR: 0.020000
Training Epoch: 13 [4096/9756]	Loss: 0.5218	LR: 0.020000
Training Epoch: 13 [4352/9756]	Loss: 0.5342	LR: 0.020000
Training Epoch: 13 [4608/9756]	Loss: 0.4769	LR: 0.020000
Training Epoch: 13 [4864/9756]	Loss: 0.4651	LR: 0.020000
Training Epoch: 13 [5120/9756]	Loss: 0.5080	LR: 0.020000
Training Epoch: 13 [5376/9756]	Loss: 0.5712	LR: 0.020000
Training Epoch: 13 [5632/9756]	Loss: 0.4644	LR: 0.020000
Training Epoch: 13 [5888/9756]	Loss: 0.4484	LR: 0.020000
Training Epoch: 13 [6144/9756]	Loss: 0.4922	LR: 0.020000
Training Epoch: 13 [6400/9756]	Loss: 0.5628	LR: 0.020000
Training Epoch: 13 [6656/9756]	Loss: 0.5387	LR: 0.020000
Training Epoch: 13 [6912/9756]	Loss: 0.4987	LR: 0.020000
Training Epoch: 13 [7168/9756]	Loss: 0.4573	LR: 0.020000
Training Epoch: 13 [7424/9756]	Loss: 0.5405	LR: 0.020000
Training Epoch: 13 [7680/9756]	Loss: 0.4821	LR: 0.020000
Training Epoch: 13 [7936/9756]	Loss: 0.4488	LR: 0.020000
Training Epoch: 13 [8192/9756]	Loss: 0.4525	LR: 0.020000
Training Epoch: 13 [8448/9756]	Loss: 0.4372	LR: 0.020000
Training Epoch: 13 [8704/9756]	Loss: 0.5036	LR: 0.020000
Training Epoch: 13 [8960/9756]	Loss: 0.4757	LR: 0.020000
Training Epoch: 13 [9216/9756]	Loss: 0.4952	LR: 0.020000
Training Epoch: 13 [9472/9756]	Loss: 0.4987	LR: 0.020000
Training Epoch: 13 [9728/9756]	Loss: 0.4697	LR: 0.020000
Training Epoch: 13 [9756/9756]	Loss: 0.5020	LR: 0.020000
Epoch 13 - Average Train Loss: 0.4990, Train Accuracy: 0.7595
Epoch 13 training time consumed: 141.09s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0026, Accuracy: 0.6973, Time consumed:8.07s
Training Epoch: 14 [256/9756]	Loss: 0.5100	LR: 0.020000
Training Epoch: 14 [512/9756]	Loss: 0.5354	LR: 0.020000
Training Epoch: 14 [768/9756]	Loss: 0.4930	LR: 0.020000
Training Epoch: 14 [1024/9756]	Loss: 0.5171	LR: 0.020000
Training Epoch: 14 [1280/9756]	Loss: 0.4745	LR: 0.020000
Training Epoch: 14 [1536/9756]	Loss: 0.4395	LR: 0.020000
Training Epoch: 14 [1792/9756]	Loss: 0.5098	LR: 0.020000
Training Epoch: 14 [2048/9756]	Loss: 0.5663	LR: 0.020000
Training Epoch: 14 [2304/9756]	Loss: 0.4739	LR: 0.020000
Training Epoch: 14 [2560/9756]	Loss: 0.4835	LR: 0.020000
Training Epoch: 14 [2816/9756]	Loss: 0.4829	LR: 0.020000
Training Epoch: 14 [3072/9756]	Loss: 0.4500	LR: 0.020000
Training Epoch: 14 [3328/9756]	Loss: 0.4433	LR: 0.020000
Training Epoch: 14 [3584/9756]	Loss: 0.3965	LR: 0.020000
Training Epoch: 14 [3840/9756]	Loss: 0.4425	LR: 0.020000
Training Epoch: 14 [4096/9756]	Loss: 0.4578	LR: 0.020000
Training Epoch: 14 [4352/9756]	Loss: 0.3575	LR: 0.020000
Training Epoch: 14 [4608/9756]	Loss: 0.4332	LR: 0.020000
Training Epoch: 14 [4864/9756]	Loss: 0.4062	LR: 0.020000
Training Epoch: 14 [5120/9756]	Loss: 0.4911	LR: 0.020000
Training Epoch: 14 [5376/9756]	Loss: 0.4101	LR: 0.020000
Training Epoch: 14 [5632/9756]	Loss: 0.3968	LR: 0.020000
Training Epoch: 14 [5888/9756]	Loss: 0.3862	LR: 0.020000
Training Epoch: 14 [6144/9756]	Loss: 0.3891	LR: 0.020000
Training Epoch: 14 [6400/9756]	Loss: 0.4359	LR: 0.020000
Training Epoch: 14 [6656/9756]	Loss: 0.3916	LR: 0.020000
Training Epoch: 14 [6912/9756]	Loss: 0.4123	LR: 0.020000
Training Epoch: 14 [7168/9756]	Loss: 0.3459	LR: 0.020000
Training Epoch: 14 [7424/9756]	Loss: 0.3088	LR: 0.020000
Training Epoch: 14 [7680/9756]	Loss: 0.3513	LR: 0.020000
Training Epoch: 14 [7936/9756]	Loss: 0.3542	LR: 0.020000
Training Epoch: 14 [8192/9756]	Loss: 0.3530	LR: 0.020000
Training Epoch: 14 [8448/9756]	Loss: 0.3940	LR: 0.020000
Training Epoch: 14 [8704/9756]	Loss: 0.4045	LR: 0.020000
Training Epoch: 14 [8960/9756]	Loss: 0.3830	LR: 0.020000
Training Epoch: 14 [9216/9756]	Loss: 0.3074	LR: 0.020000
Training Epoch: 14 [9472/9756]	Loss: 0.3656	LR: 0.020000
Training Epoch: 14 [9728/9756]	Loss: 0.2750	LR: 0.020000
Training Epoch: 14 [9756/9756]	Loss: 0.3709	LR: 0.020000
Epoch 14 - Average Train Loss: 0.4217, Train Accuracy: 0.8075
Epoch 14 training time consumed: 140.67s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0058, Accuracy: 0.5985, Time consumed:7.95s
Training Epoch: 15 [256/9756]	Loss: 0.3958	LR: 0.020000
Training Epoch: 15 [512/9756]	Loss: 0.4599	LR: 0.020000
Training Epoch: 15 [768/9756]	Loss: 0.4227	LR: 0.020000
Training Epoch: 15 [1024/9756]	Loss: 0.3745	LR: 0.020000
Training Epoch: 15 [1280/9756]	Loss: 0.4144	LR: 0.020000
Training Epoch: 15 [1536/9756]	Loss: 0.3962	LR: 0.020000
Training Epoch: 15 [1792/9756]	Loss: 0.3601	LR: 0.020000
Training Epoch: 15 [2048/9756]	Loss: 0.3659	LR: 0.020000
Training Epoch: 15 [2304/9756]	Loss: 0.3771	LR: 0.020000
Training Epoch: 15 [2560/9756]	Loss: 0.3684	LR: 0.020000
Training Epoch: 15 [2816/9756]	Loss: 0.3625	LR: 0.020000
Training Epoch: 15 [3072/9756]	Loss: 0.3744	LR: 0.020000
Training Epoch: 15 [3328/9756]	Loss: 0.3394	LR: 0.020000
Training Epoch: 15 [3584/9756]	Loss: 0.3919	LR: 0.020000
Training Epoch: 15 [3840/9756]	Loss: 0.4048	LR: 0.020000
Training Epoch: 15 [4096/9756]	Loss: 0.4051	LR: 0.020000
Training Epoch: 15 [4352/9756]	Loss: 0.3375	LR: 0.020000
Training Epoch: 15 [4608/9756]	Loss: 0.3666	LR: 0.020000
Training Epoch: 15 [4864/9756]	Loss: 0.3683	LR: 0.020000
Training Epoch: 15 [5120/9756]	Loss: 0.3157	LR: 0.020000
Training Epoch: 15 [5376/9756]	Loss: 0.3782	LR: 0.020000
Training Epoch: 15 [5632/9756]	Loss: 0.3212	LR: 0.020000
Training Epoch: 15 [5888/9756]	Loss: 0.3417	LR: 0.020000
Training Epoch: 15 [6144/9756]	Loss: 0.3554	LR: 0.020000
Training Epoch: 15 [6400/9756]	Loss: 0.3837	LR: 0.020000
Training Epoch: 15 [6656/9756]	Loss: 0.4367	LR: 0.020000
Training Epoch: 15 [6912/9756]	Loss: 0.3062	LR: 0.020000
Training Epoch: 15 [7168/9756]	Loss: 0.3659	LR: 0.020000
Training Epoch: 15 [7424/9756]	Loss: 0.4078	LR: 0.020000
Training Epoch: 15 [7680/9756]	Loss: 0.3287	LR: 0.020000
Training Epoch: 15 [7936/9756]	Loss: 0.3157	LR: 0.020000
Training Epoch: 15 [8192/9756]	Loss: 0.3177	LR: 0.020000
Training Epoch: 15 [8448/9756]	Loss: 0.3336	LR: 0.020000
Training Epoch: 15 [8704/9756]	Loss: 0.3016	LR: 0.020000
Training Epoch: 15 [8960/9756]	Loss: 0.2959	LR: 0.020000
Training Epoch: 15 [9216/9756]	Loss: 0.3209	LR: 0.020000
Training Epoch: 15 [9472/9756]	Loss: 0.2745	LR: 0.020000
Training Epoch: 15 [9728/9756]	Loss: 0.3190	LR: 0.020000
Training Epoch: 15 [9756/9756]	Loss: 0.1667	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3601, Train Accuracy: 0.8403
Epoch 15 training time consumed: 141.20s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0064, Accuracy: 0.5496, Time consumed:7.89s
Training Epoch: 16 [256/9756]	Loss: 0.3721	LR: 0.020000
Training Epoch: 16 [512/9756]	Loss: 0.3050	LR: 0.020000
Training Epoch: 16 [768/9756]	Loss: 0.3434	LR: 0.020000
Training Epoch: 16 [1024/9756]	Loss: 0.3151	LR: 0.020000
Training Epoch: 16 [1280/9756]	Loss: 0.2759	LR: 0.020000
Training Epoch: 16 [1536/9756]	Loss: 0.3140	LR: 0.020000
Training Epoch: 16 [1792/9756]	Loss: 0.3020	LR: 0.020000
Training Epoch: 16 [2048/9756]	Loss: 0.2775	LR: 0.020000
Training Epoch: 16 [2304/9756]	Loss: 0.2817	LR: 0.020000
Training Epoch: 16 [2560/9756]	Loss: 0.2416	LR: 0.020000
Training Epoch: 16 [2816/9756]	Loss: 0.2788	LR: 0.020000
Training Epoch: 16 [3072/9756]	Loss: 0.3294	LR: 0.020000
Training Epoch: 16 [3328/9756]	Loss: 0.2639	LR: 0.020000
Training Epoch: 16 [3584/9756]	Loss: 0.2308	LR: 0.020000
Training Epoch: 16 [3840/9756]	Loss: 0.2424	LR: 0.020000
Training Epoch: 16 [4096/9756]	Loss: 0.3584	LR: 0.020000
Training Epoch: 16 [4352/9756]	Loss: 0.1960	LR: 0.020000
Training Epoch: 16 [4608/9756]	Loss: 0.2512	LR: 0.020000
Training Epoch: 16 [4864/9756]	Loss: 0.2467	LR: 0.020000
Training Epoch: 16 [5120/9756]	Loss: 0.2161	LR: 0.020000
Training Epoch: 16 [5376/9756]	Loss: 0.2301	LR: 0.020000
Training Epoch: 16 [5632/9756]	Loss: 0.2772	LR: 0.020000
Training Epoch: 16 [5888/9756]	Loss: 0.2485	LR: 0.020000
Training Epoch: 16 [6144/9756]	Loss: 0.2737	LR: 0.020000
Training Epoch: 16 [6400/9756]	Loss: 0.2247	LR: 0.020000
Training Epoch: 16 [6656/9756]	Loss: 0.2346	LR: 0.020000
Training Epoch: 16 [6912/9756]	Loss: 0.2424	LR: 0.020000
Training Epoch: 16 [7168/9756]	Loss: 0.2693	LR: 0.020000
Training Epoch: 16 [7424/9756]	Loss: 0.1893	LR: 0.020000
Training Epoch: 16 [7680/9756]	Loss: 0.3682	LR: 0.020000
Training Epoch: 16 [7936/9756]	Loss: 0.2619	LR: 0.020000
Training Epoch: 16 [8192/9756]	Loss: 0.2870	LR: 0.020000
Training Epoch: 16 [8448/9756]	Loss: 0.2876	LR: 0.020000
Training Epoch: 16 [8704/9756]	Loss: 0.2719	LR: 0.020000
Training Epoch: 16 [8960/9756]	Loss: 0.3084	LR: 0.020000
Training Epoch: 16 [9216/9756]	Loss: 0.2599	LR: 0.020000
Training Epoch: 16 [9472/9756]	Loss: 0.2814	LR: 0.020000
Training Epoch: 16 [9728/9756]	Loss: 0.2747	LR: 0.020000
Training Epoch: 16 [9756/9756]	Loss: 0.2920	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2746, Train Accuracy: 0.8844
Epoch 16 training time consumed: 141.37s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0012, Accuracy: 0.8920, Time consumed:8.26s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-16-best.pth
Training Epoch: 17 [256/9756]	Loss: 0.2623	LR: 0.020000
Training Epoch: 17 [512/9756]	Loss: 0.3102	LR: 0.020000
Training Epoch: 17 [768/9756]	Loss: 0.3127	LR: 0.020000
Training Epoch: 17 [1024/9756]	Loss: 0.2466	LR: 0.020000
Training Epoch: 17 [1280/9756]	Loss: 0.2775	LR: 0.020000
Training Epoch: 17 [1536/9756]	Loss: 0.2867	LR: 0.020000
Training Epoch: 17 [1792/9756]	Loss: 0.2929	LR: 0.020000
Training Epoch: 17 [2048/9756]	Loss: 0.2117	LR: 0.020000
Training Epoch: 17 [2304/9756]	Loss: 0.2168	LR: 0.020000
Training Epoch: 17 [2560/9756]	Loss: 0.2114	LR: 0.020000
Training Epoch: 17 [2816/9756]	Loss: 0.2491	LR: 0.020000
Training Epoch: 17 [3072/9756]	Loss: 0.2676	LR: 0.020000
Training Epoch: 17 [3328/9756]	Loss: 0.2820	LR: 0.020000
Training Epoch: 17 [3584/9756]	Loss: 0.2068	LR: 0.020000
Training Epoch: 17 [3840/9756]	Loss: 0.2331	LR: 0.020000
Training Epoch: 17 [4096/9756]	Loss: 0.2359	LR: 0.020000
Training Epoch: 17 [4352/9756]	Loss: 0.2212	LR: 0.020000
Training Epoch: 17 [4608/9756]	Loss: 0.2233	LR: 0.020000
Training Epoch: 17 [4864/9756]	Loss: 0.2450	LR: 0.020000
Training Epoch: 17 [5120/9756]	Loss: 0.2589	LR: 0.020000
Training Epoch: 17 [5376/9756]	Loss: 0.2097	LR: 0.020000
Training Epoch: 17 [5632/9756]	Loss: 0.2656	LR: 0.020000
Training Epoch: 17 [5888/9756]	Loss: 0.2946	LR: 0.020000
Training Epoch: 17 [6144/9756]	Loss: 0.2903	LR: 0.020000
Training Epoch: 17 [6400/9756]	Loss: 0.2466	LR: 0.020000
Training Epoch: 17 [6656/9756]	Loss: 0.2368	LR: 0.020000
Training Epoch: 17 [6912/9756]	Loss: 0.2820	LR: 0.020000
Training Epoch: 17 [7168/9756]	Loss: 0.2170	LR: 0.020000
Training Epoch: 17 [7424/9756]	Loss: 0.2075	LR: 0.020000
Training Epoch: 17 [7680/9756]	Loss: 0.2817	LR: 0.020000
Training Epoch: 17 [7936/9756]	Loss: 0.2017	LR: 0.020000
Training Epoch: 17 [8192/9756]	Loss: 0.2067	LR: 0.020000
Training Epoch: 17 [8448/9756]	Loss: 0.2514	LR: 0.020000
Training Epoch: 17 [8704/9756]	Loss: 0.2216	LR: 0.020000
Training Epoch: 17 [8960/9756]	Loss: 0.2583	LR: 0.020000
Training Epoch: 17 [9216/9756]	Loss: 0.2611	LR: 0.020000
Training Epoch: 17 [9472/9756]	Loss: 0.2405	LR: 0.020000
Training Epoch: 17 [9728/9756]	Loss: 0.2794	LR: 0.020000
Training Epoch: 17 [9756/9756]	Loss: 0.2351	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2501, Train Accuracy: 0.8947
Epoch 17 training time consumed: 141.41s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0010, Accuracy: 0.8959, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-17-best.pth
Training Epoch: 18 [256/9756]	Loss: 0.2755	LR: 0.020000
Training Epoch: 18 [512/9756]	Loss: 0.2661	LR: 0.020000
Training Epoch: 18 [768/9756]	Loss: 0.2792	LR: 0.020000
Training Epoch: 18 [1024/9756]	Loss: 0.2748	LR: 0.020000
Training Epoch: 18 [1280/9756]	Loss: 0.2007	LR: 0.020000
Training Epoch: 18 [1536/9756]	Loss: 0.2389	LR: 0.020000
Training Epoch: 18 [1792/9756]	Loss: 0.2582	LR: 0.020000
Training Epoch: 18 [2048/9756]	Loss: 0.2598	LR: 0.020000
Training Epoch: 18 [2304/9756]	Loss: 0.3113	LR: 0.020000
Training Epoch: 18 [2560/9756]	Loss: 0.2120	LR: 0.020000
Training Epoch: 18 [2816/9756]	Loss: 0.2183	LR: 0.020000
Training Epoch: 18 [3072/9756]	Loss: 0.2799	LR: 0.020000
Training Epoch: 18 [3328/9756]	Loss: 0.3131	LR: 0.020000
Training Epoch: 18 [3584/9756]	Loss: 0.2678	LR: 0.020000
Training Epoch: 18 [3840/9756]	Loss: 0.2580	LR: 0.020000
Training Epoch: 18 [4096/9756]	Loss: 0.2723	LR: 0.020000
Training Epoch: 18 [4352/9756]	Loss: 0.2563	LR: 0.020000
Training Epoch: 18 [4608/9756]	Loss: 0.2819	LR: 0.020000
Training Epoch: 18 [4864/9756]	Loss: 0.1949	LR: 0.020000
Training Epoch: 18 [5120/9756]	Loss: 0.2068	LR: 0.020000
Training Epoch: 18 [5376/9756]	Loss: 0.2110	LR: 0.020000
Training Epoch: 18 [5632/9756]	Loss: 0.1992	LR: 0.020000
Training Epoch: 18 [5888/9756]	Loss: 0.2671	LR: 0.020000
Training Epoch: 18 [6144/9756]	Loss: 0.2639	LR: 0.020000
Training Epoch: 18 [6400/9756]	Loss: 0.2510	LR: 0.020000
Training Epoch: 18 [6656/9756]	Loss: 0.1905	LR: 0.020000
Training Epoch: 18 [6912/9756]	Loss: 0.1692	LR: 0.020000
Training Epoch: 18 [7168/9756]	Loss: 0.1967	LR: 0.020000
Training Epoch: 18 [7424/9756]	Loss: 0.2066	LR: 0.020000
Training Epoch: 18 [7680/9756]	Loss: 0.2559	LR: 0.020000
Training Epoch: 18 [7936/9756]	Loss: 0.2112	LR: 0.020000
Training Epoch: 18 [8192/9756]	Loss: 0.2446	LR: 0.020000
Training Epoch: 18 [8448/9756]	Loss: 0.2032	LR: 0.020000
Training Epoch: 18 [8704/9756]	Loss: 0.1538	LR: 0.020000
Training Epoch: 18 [8960/9756]	Loss: 0.1974	LR: 0.020000
Training Epoch: 18 [9216/9756]	Loss: 0.2032	LR: 0.020000
Training Epoch: 18 [9472/9756]	Loss: 0.1597	LR: 0.020000
Training Epoch: 18 [9728/9756]	Loss: 0.2606	LR: 0.020000
Training Epoch: 18 [9756/9756]	Loss: 0.2488	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2361, Train Accuracy: 0.9020
Epoch 18 training time consumed: 141.06s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0009, Accuracy: 0.9085, Time consumed:7.85s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-18-best.pth
Training Epoch: 19 [256/9756]	Loss: 0.2318	LR: 0.020000
Training Epoch: 19 [512/9756]	Loss: 0.2977	LR: 0.020000
Training Epoch: 19 [768/9756]	Loss: 0.2278	LR: 0.020000
Training Epoch: 19 [1024/9756]	Loss: 0.2426	LR: 0.020000
Training Epoch: 19 [1280/9756]	Loss: 0.2569	LR: 0.020000
Training Epoch: 19 [1536/9756]	Loss: 0.2099	LR: 0.020000
Training Epoch: 19 [1792/9756]	Loss: 0.2817	LR: 0.020000
Training Epoch: 19 [2048/9756]	Loss: 0.2470	LR: 0.020000
Training Epoch: 19 [2304/9756]	Loss: 0.2066	LR: 0.020000
Training Epoch: 19 [2560/9756]	Loss: 0.2234	LR: 0.020000
Training Epoch: 19 [2816/9756]	Loss: 0.1736	LR: 0.020000
Training Epoch: 19 [3072/9756]	Loss: 0.1498	LR: 0.020000
Training Epoch: 19 [3328/9756]	Loss: 0.2119	LR: 0.020000
Training Epoch: 19 [3584/9756]	Loss: 0.2706	LR: 0.020000
Training Epoch: 19 [3840/9756]	Loss: 0.2117	LR: 0.020000
Training Epoch: 19 [4096/9756]	Loss: 0.2202	LR: 0.020000
Training Epoch: 19 [4352/9756]	Loss: 0.2211	LR: 0.020000
Training Epoch: 19 [4608/9756]	Loss: 0.2454	LR: 0.020000
Training Epoch: 19 [4864/9756]	Loss: 0.2102	LR: 0.020000
Training Epoch: 19 [5120/9756]	Loss: 0.2025	LR: 0.020000
Training Epoch: 19 [5376/9756]	Loss: 0.2271	LR: 0.020000
Training Epoch: 19 [5632/9756]	Loss: 0.1753	LR: 0.020000
Training Epoch: 19 [5888/9756]	Loss: 0.1503	LR: 0.020000
Training Epoch: 19 [6144/9756]	Loss: 0.1432	LR: 0.020000
Training Epoch: 19 [6400/9756]	Loss: 0.2457	LR: 0.020000
Training Epoch: 19 [6656/9756]	Loss: 0.2094	LR: 0.020000
Training Epoch: 19 [6912/9756]	Loss: 0.1792	LR: 0.020000
Training Epoch: 19 [7168/9756]	Loss: 0.1789	LR: 0.020000
Training Epoch: 19 [7424/9756]	Loss: 0.2737	LR: 0.020000
Training Epoch: 19 [7680/9756]	Loss: 0.1569	LR: 0.020000
Training Epoch: 19 [7936/9756]	Loss: 0.1875	LR: 0.020000
Training Epoch: 19 [8192/9756]	Loss: 0.2454	LR: 0.020000
Training Epoch: 19 [8448/9756]	Loss: 0.2116	LR: 0.020000
Training Epoch: 19 [8704/9756]	Loss: 0.2194	LR: 0.020000
Training Epoch: 19 [8960/9756]	Loss: 0.1848	LR: 0.020000
Training Epoch: 19 [9216/9756]	Loss: 0.1995	LR: 0.020000
Training Epoch: 19 [9472/9756]	Loss: 0.2420	LR: 0.020000
Training Epoch: 19 [9728/9756]	Loss: 0.2290	LR: 0.020000
Training Epoch: 19 [9756/9756]	Loss: 0.1967	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2158, Train Accuracy: 0.9105
Epoch 19 training time consumed: 141.21s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0010, Accuracy: 0.9119, Time consumed:7.98s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-19-best.pth
Training Epoch: 20 [256/9756]	Loss: 0.1938	LR: 0.004000
Training Epoch: 20 [512/9756]	Loss: 0.2230	LR: 0.004000
Training Epoch: 20 [768/9756]	Loss: 0.2283	LR: 0.004000
Training Epoch: 20 [1024/9756]	Loss: 0.2315	LR: 0.004000
Training Epoch: 20 [1280/9756]	Loss: 0.1780	LR: 0.004000
Training Epoch: 20 [1536/9756]	Loss: 0.2026	LR: 0.004000
Training Epoch: 20 [1792/9756]	Loss: 0.2191	LR: 0.004000
Training Epoch: 20 [2048/9756]	Loss: 0.1888	LR: 0.004000
Training Epoch: 20 [2304/9756]	Loss: 0.2055	LR: 0.004000
Training Epoch: 20 [2560/9756]	Loss: 0.2257	LR: 0.004000
Training Epoch: 20 [2816/9756]	Loss: 0.1598	LR: 0.004000
Training Epoch: 20 [3072/9756]	Loss: 0.1971	LR: 0.004000
Training Epoch: 20 [3328/9756]	Loss: 0.1714	LR: 0.004000
Training Epoch: 20 [3584/9756]	Loss: 0.1871	LR: 0.004000
Training Epoch: 20 [3840/9756]	Loss: 0.1330	LR: 0.004000
Training Epoch: 20 [4096/9756]	Loss: 0.1860	LR: 0.004000
Training Epoch: 20 [4352/9756]	Loss: 0.1564	LR: 0.004000
Training Epoch: 20 [4608/9756]	Loss: 0.1968	LR: 0.004000
Training Epoch: 20 [4864/9756]	Loss: 0.2560	LR: 0.004000
Training Epoch: 20 [5120/9756]	Loss: 0.1565	LR: 0.004000
Training Epoch: 20 [5376/9756]	Loss: 0.1794	LR: 0.004000
Training Epoch: 20 [5632/9756]	Loss: 0.1894	LR: 0.004000
Training Epoch: 20 [5888/9756]	Loss: 0.1578	LR: 0.004000
Training Epoch: 20 [6144/9756]	Loss: 0.1529	LR: 0.004000
Training Epoch: 20 [6400/9756]	Loss: 0.2035	LR: 0.004000
Training Epoch: 20 [6656/9756]	Loss: 0.2224	LR: 0.004000
Training Epoch: 20 [6912/9756]	Loss: 0.1618	LR: 0.004000
Training Epoch: 20 [7168/9756]	Loss: 0.1540	LR: 0.004000
Training Epoch: 20 [7424/9756]	Loss: 0.1522	LR: 0.004000
Training Epoch: 20 [7680/9756]	Loss: 0.1879	LR: 0.004000
Training Epoch: 20 [7936/9756]	Loss: 0.1914	LR: 0.004000
Training Epoch: 20 [8192/9756]	Loss: 0.1655	LR: 0.004000
Training Epoch: 20 [8448/9756]	Loss: 0.2078	LR: 0.004000
Training Epoch: 20 [8704/9756]	Loss: 0.1686	LR: 0.004000
Training Epoch: 20 [8960/9756]	Loss: 0.1726	LR: 0.004000
Training Epoch: 20 [9216/9756]	Loss: 0.2142	LR: 0.004000
Training Epoch: 20 [9472/9756]	Loss: 0.1619	LR: 0.004000
Training Epoch: 20 [9728/9756]	Loss: 0.1970	LR: 0.004000
Training Epoch: 20 [9756/9756]	Loss: 0.2170	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1879, Train Accuracy: 0.9223
Epoch 20 training time consumed: 141.24s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0007, Accuracy: 0.9332, Time consumed:8.14s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-20-best.pth
Training Epoch: 21 [256/9756]	Loss: 0.1332	LR: 0.004000
Training Epoch: 21 [512/9756]	Loss: 0.1913	LR: 0.004000
Training Epoch: 21 [768/9756]	Loss: 0.1715	LR: 0.004000
Training Epoch: 21 [1024/9756]	Loss: 0.1964	LR: 0.004000
Training Epoch: 21 [1280/9756]	Loss: 0.1500	LR: 0.004000
Training Epoch: 21 [1536/9756]	Loss: 0.1769	LR: 0.004000
Training Epoch: 21 [1792/9756]	Loss: 0.1772	LR: 0.004000
Training Epoch: 21 [2048/9756]	Loss: 0.1591	LR: 0.004000
Training Epoch: 21 [2304/9756]	Loss: 0.1607	LR: 0.004000
Training Epoch: 21 [2560/9756]	Loss: 0.1667	LR: 0.004000
Training Epoch: 21 [2816/9756]	Loss: 0.1452	LR: 0.004000
Training Epoch: 21 [3072/9756]	Loss: 0.1485	LR: 0.004000
Training Epoch: 21 [3328/9756]	Loss: 0.2080	LR: 0.004000
Training Epoch: 21 [3584/9756]	Loss: 0.1949	LR: 0.004000
Training Epoch: 21 [3840/9756]	Loss: 0.1438	LR: 0.004000
Training Epoch: 21 [4096/9756]	Loss: 0.1261	LR: 0.004000
Training Epoch: 21 [4352/9756]	Loss: 0.1960	LR: 0.004000
Training Epoch: 21 [4608/9756]	Loss: 0.1867	LR: 0.004000
Training Epoch: 21 [4864/9756]	Loss: 0.2132	LR: 0.004000
Training Epoch: 21 [5120/9756]	Loss: 0.1633	LR: 0.004000
Training Epoch: 21 [5376/9756]	Loss: 0.1917	LR: 0.004000
Training Epoch: 21 [5632/9756]	Loss: 0.2211	LR: 0.004000
Training Epoch: 21 [5888/9756]	Loss: 0.1464	LR: 0.004000
Training Epoch: 21 [6144/9756]	Loss: 0.1497	LR: 0.004000
Training Epoch: 21 [6400/9756]	Loss: 0.1757	LR: 0.004000
Training Epoch: 21 [6656/9756]	Loss: 0.1844	LR: 0.004000
Training Epoch: 21 [6912/9756]	Loss: 0.1656	LR: 0.004000
Training Epoch: 21 [7168/9756]	Loss: 0.1608	LR: 0.004000
Training Epoch: 21 [7424/9756]	Loss: 0.1852	LR: 0.004000
Training Epoch: 21 [7680/9756]	Loss: 0.1784	LR: 0.004000
Training Epoch: 21 [7936/9756]	Loss: 0.1555	LR: 0.004000
Training Epoch: 21 [8192/9756]	Loss: 0.1802	LR: 0.004000
Training Epoch: 21 [8448/9756]	Loss: 0.2435	LR: 0.004000
Training Epoch: 21 [8704/9756]	Loss: 0.1161	LR: 0.004000
Training Epoch: 21 [8960/9756]	Loss: 0.2005	LR: 0.004000
Training Epoch: 21 [9216/9756]	Loss: 0.1898	LR: 0.004000
Training Epoch: 21 [9472/9756]	Loss: 0.1655	LR: 0.004000
Training Epoch: 21 [9728/9756]	Loss: 0.1871	LR: 0.004000
Training Epoch: 21 [9756/9756]	Loss: 0.1483	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1738, Train Accuracy: 0.9289
Epoch 21 training time consumed: 141.47s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0008, Accuracy: 0.9215, Time consumed:8.00s
Training Epoch: 22 [256/9756]	Loss: 0.1572	LR: 0.004000
Training Epoch: 22 [512/9756]	Loss: 0.1492	LR: 0.004000
Training Epoch: 22 [768/9756]	Loss: 0.2004	LR: 0.004000
Training Epoch: 22 [1024/9756]	Loss: 0.2016	LR: 0.004000
Training Epoch: 22 [1280/9756]	Loss: 0.1878	LR: 0.004000
Training Epoch: 22 [1536/9756]	Loss: 0.1558	LR: 0.004000
Training Epoch: 22 [1792/9756]	Loss: 0.1152	LR: 0.004000
Training Epoch: 22 [2048/9756]	Loss: 0.1732	LR: 0.004000
Training Epoch: 22 [2304/9756]	Loss: 0.1748	LR: 0.004000
Training Epoch: 22 [2560/9756]	Loss: 0.2339	LR: 0.004000
Training Epoch: 22 [2816/9756]	Loss: 0.1582	LR: 0.004000
Training Epoch: 22 [3072/9756]	Loss: 0.1230	LR: 0.004000
Training Epoch: 22 [3328/9756]	Loss: 0.1727	LR: 0.004000
Training Epoch: 22 [3584/9756]	Loss: 0.1331	LR: 0.004000
Training Epoch: 22 [3840/9756]	Loss: 0.1310	LR: 0.004000
Training Epoch: 22 [4096/9756]	Loss: 0.1856	LR: 0.004000
Training Epoch: 22 [4352/9756]	Loss: 0.1774	LR: 0.004000
Training Epoch: 22 [4608/9756]	Loss: 0.1808	LR: 0.004000
Training Epoch: 22 [4864/9756]	Loss: 0.1347	LR: 0.004000
Training Epoch: 22 [5120/9756]	Loss: 0.2189	LR: 0.004000
Training Epoch: 22 [5376/9756]	Loss: 0.1771	LR: 0.004000
Training Epoch: 22 [5632/9756]	Loss: 0.1651	LR: 0.004000
Training Epoch: 22 [5888/9756]	Loss: 0.1631	LR: 0.004000
Training Epoch: 22 [6144/9756]	Loss: 0.2090	LR: 0.004000
Training Epoch: 22 [6400/9756]	Loss: 0.1990	LR: 0.004000
Training Epoch: 22 [6656/9756]	Loss: 0.1910	LR: 0.004000
Training Epoch: 22 [6912/9756]	Loss: 0.1444	LR: 0.004000
Training Epoch: 22 [7168/9756]	Loss: 0.1893	LR: 0.004000
Training Epoch: 22 [7424/9756]	Loss: 0.1303	LR: 0.004000
Training Epoch: 22 [7680/9756]	Loss: 0.1516	LR: 0.004000
Training Epoch: 22 [7936/9756]	Loss: 0.1575	LR: 0.004000
Training Epoch: 22 [8192/9756]	Loss: 0.1147	LR: 0.004000
Training Epoch: 22 [8448/9756]	Loss: 0.1724	LR: 0.004000
Training Epoch: 22 [8704/9756]	Loss: 0.1965	LR: 0.004000
Training Epoch: 22 [8960/9756]	Loss: 0.1747	LR: 0.004000
Training Epoch: 22 [9216/9756]	Loss: 0.1103	LR: 0.004000
Training Epoch: 22 [9472/9756]	Loss: 0.1562	LR: 0.004000
Training Epoch: 22 [9728/9756]	Loss: 0.1274	LR: 0.004000
Training Epoch: 22 [9756/9756]	Loss: 0.0860	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1654, Train Accuracy: 0.9313
Epoch 22 training time consumed: 140.97s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0006, Accuracy: 0.9404, Time consumed:7.91s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-22-best.pth
Training Epoch: 23 [256/9756]	Loss: 0.1382	LR: 0.004000
Training Epoch: 23 [512/9756]	Loss: 0.1249	LR: 0.004000
Training Epoch: 23 [768/9756]	Loss: 0.1772	LR: 0.004000
Training Epoch: 23 [1024/9756]	Loss: 0.1636	LR: 0.004000
Training Epoch: 23 [1280/9756]	Loss: 0.1589	LR: 0.004000
Training Epoch: 23 [1536/9756]	Loss: 0.1733	LR: 0.004000
Training Epoch: 23 [1792/9756]	Loss: 0.1273	LR: 0.004000
Training Epoch: 23 [2048/9756]	Loss: 0.1511	LR: 0.004000
Training Epoch: 23 [2304/9756]	Loss: 0.1506	LR: 0.004000
Training Epoch: 23 [2560/9756]	Loss: 0.1564	LR: 0.004000
Training Epoch: 23 [2816/9756]	Loss: 0.1230	LR: 0.004000
Training Epoch: 23 [3072/9756]	Loss: 0.1406	LR: 0.004000
Training Epoch: 23 [3328/9756]	Loss: 0.1980	LR: 0.004000
Training Epoch: 23 [3584/9756]	Loss: 0.1404	LR: 0.004000
Training Epoch: 23 [3840/9756]	Loss: 0.1909	LR: 0.004000
Training Epoch: 23 [4096/9756]	Loss: 0.1386	LR: 0.004000
Training Epoch: 23 [4352/9756]	Loss: 0.2081	LR: 0.004000
Training Epoch: 23 [4608/9756]	Loss: 0.1699	LR: 0.004000
Training Epoch: 23 [4864/9756]	Loss: 0.1445	LR: 0.004000
Training Epoch: 23 [5120/9756]	Loss: 0.1682	LR: 0.004000
Training Epoch: 23 [5376/9756]	Loss: 0.1676	LR: 0.004000
Training Epoch: 23 [5632/9756]	Loss: 0.1240	LR: 0.004000
Training Epoch: 23 [5888/9756]	Loss: 0.1315	LR: 0.004000
Training Epoch: 23 [6144/9756]	Loss: 0.1703	LR: 0.004000
Training Epoch: 23 [6400/9756]	Loss: 0.1508	LR: 0.004000
Training Epoch: 23 [6656/9756]	Loss: 0.1354	LR: 0.004000
Training Epoch: 23 [6912/9756]	Loss: 0.1139	LR: 0.004000
Training Epoch: 23 [7168/9756]	Loss: 0.2114	LR: 0.004000
Training Epoch: 23 [7424/9756]	Loss: 0.1601	LR: 0.004000
Training Epoch: 23 [7680/9756]	Loss: 0.1911	LR: 0.004000
Training Epoch: 23 [7936/9756]	Loss: 0.2593	LR: 0.004000
Training Epoch: 23 [8192/9756]	Loss: 0.1868	LR: 0.004000
Training Epoch: 23 [8448/9756]	Loss: 0.1632	LR: 0.004000
Training Epoch: 23 [8704/9756]	Loss: 0.1899	LR: 0.004000
Training Epoch: 23 [8960/9756]	Loss: 0.1976	LR: 0.004000
Training Epoch: 23 [9216/9756]	Loss: 0.1383	LR: 0.004000
Training Epoch: 23 [9472/9756]	Loss: 0.1396	LR: 0.004000
Training Epoch: 23 [9728/9756]	Loss: 0.1500	LR: 0.004000
Training Epoch: 23 [9756/9756]	Loss: 0.1452	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1611, Train Accuracy: 0.9329
Epoch 23 training time consumed: 141.22s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9448, Time consumed:8.26s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-23-best.pth
Training Epoch: 24 [256/9756]	Loss: 0.2088	LR: 0.004000
Training Epoch: 24 [512/9756]	Loss: 0.1488	LR: 0.004000
Training Epoch: 24 [768/9756]	Loss: 0.1348	LR: 0.004000
Training Epoch: 24 [1024/9756]	Loss: 0.1851	LR: 0.004000
Training Epoch: 24 [1280/9756]	Loss: 0.1465	LR: 0.004000
Training Epoch: 24 [1536/9756]	Loss: 0.1711	LR: 0.004000
Training Epoch: 24 [1792/9756]	Loss: 0.1972	LR: 0.004000
Training Epoch: 24 [2048/9756]	Loss: 0.0844	LR: 0.004000
Training Epoch: 24 [2304/9756]	Loss: 0.1940	LR: 0.004000
Training Epoch: 24 [2560/9756]	Loss: 0.1777	LR: 0.004000
Training Epoch: 24 [2816/9756]	Loss: 0.1786	LR: 0.004000
Training Epoch: 24 [3072/9756]	Loss: 0.1406	LR: 0.004000
Training Epoch: 24 [3328/9756]	Loss: 0.1375	LR: 0.004000
Training Epoch: 24 [3584/9756]	Loss: 0.1734	LR: 0.004000
Training Epoch: 24 [3840/9756]	Loss: 0.1799	LR: 0.004000
Training Epoch: 24 [4096/9756]	Loss: 0.1347	LR: 0.004000
Training Epoch: 24 [4352/9756]	Loss: 0.1644	LR: 0.004000
Training Epoch: 24 [4608/9756]	Loss: 0.1223	LR: 0.004000
Training Epoch: 24 [4864/9756]	Loss: 0.1763	LR: 0.004000
Training Epoch: 24 [5120/9756]	Loss: 0.1556	LR: 0.004000
Training Epoch: 24 [5376/9756]	Loss: 0.1592	LR: 0.004000
Training Epoch: 24 [5632/9756]	Loss: 0.1358	LR: 0.004000
Training Epoch: 24 [5888/9756]	Loss: 0.1675	LR: 0.004000
Training Epoch: 24 [6144/9756]	Loss: 0.1452	LR: 0.004000
Training Epoch: 24 [6400/9756]	Loss: 0.1871	LR: 0.004000
Training Epoch: 24 [6656/9756]	Loss: 0.1081	LR: 0.004000
Training Epoch: 24 [6912/9756]	Loss: 0.1711	LR: 0.004000
Training Epoch: 24 [7168/9756]	Loss: 0.1536	LR: 0.004000
Training Epoch: 24 [7424/9756]	Loss: 0.2144	LR: 0.004000
Training Epoch: 24 [7680/9756]	Loss: 0.1853	LR: 0.004000
Training Epoch: 24 [7936/9756]	Loss: 0.1624	LR: 0.004000
Training Epoch: 24 [8192/9756]	Loss: 0.1688	LR: 0.004000
Training Epoch: 24 [8448/9756]	Loss: 0.1511	LR: 0.004000
Training Epoch: 24 [8704/9756]	Loss: 0.1245	LR: 0.004000
Training Epoch: 24 [8960/9756]	Loss: 0.1196	LR: 0.004000
Training Epoch: 24 [9216/9756]	Loss: 0.1225	LR: 0.004000
Training Epoch: 24 [9472/9756]	Loss: 0.1676	LR: 0.004000
Training Epoch: 24 [9728/9756]	Loss: 0.1503	LR: 0.004000
Training Epoch: 24 [9756/9756]	Loss: 0.1414	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1580, Train Accuracy: 0.9347
Epoch 24 training time consumed: 141.25s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0006, Accuracy: 0.9361, Time consumed:8.10s
Training Epoch: 25 [256/9756]	Loss: 0.1004	LR: 0.004000
Training Epoch: 25 [512/9756]	Loss: 0.1400	LR: 0.004000
Training Epoch: 25 [768/9756]	Loss: 0.1722	LR: 0.004000
Training Epoch: 25 [1024/9756]	Loss: 0.1610	LR: 0.004000
Training Epoch: 25 [1280/9756]	Loss: 0.1813	LR: 0.004000
Training Epoch: 25 [1536/9756]	Loss: 0.1745	LR: 0.004000
Training Epoch: 25 [1792/9756]	Loss: 0.1261	LR: 0.004000
Training Epoch: 25 [2048/9756]	Loss: 0.1150	LR: 0.004000
Training Epoch: 25 [2304/9756]	Loss: 0.1675	LR: 0.004000
Training Epoch: 25 [2560/9756]	Loss: 0.2202	LR: 0.004000
Training Epoch: 25 [2816/9756]	Loss: 0.1913	LR: 0.004000
Training Epoch: 25 [3072/9756]	Loss: 0.1110	LR: 0.004000
Training Epoch: 25 [3328/9756]	Loss: 0.1277	LR: 0.004000
Training Epoch: 25 [3584/9756]	Loss: 0.1770	LR: 0.004000
Training Epoch: 25 [3840/9756]	Loss: 0.1937	LR: 0.004000
Training Epoch: 25 [4096/9756]	Loss: 0.1811	LR: 0.004000
Training Epoch: 25 [4352/9756]	Loss: 0.1653	LR: 0.004000
Training Epoch: 25 [4608/9756]	Loss: 0.1655	LR: 0.004000
Training Epoch: 25 [4864/9756]	Loss: 0.1169	LR: 0.004000
Training Epoch: 25 [5120/9756]	Loss: 0.1586	LR: 0.004000
Training Epoch: 25 [5376/9756]	Loss: 0.1650	LR: 0.004000
Training Epoch: 25 [5632/9756]	Loss: 0.1359	LR: 0.004000
Training Epoch: 25 [5888/9756]	Loss: 0.1482	LR: 0.004000
Training Epoch: 25 [6144/9756]	Loss: 0.1749	LR: 0.004000
Training Epoch: 25 [6400/9756]	Loss: 0.1613	LR: 0.004000
Training Epoch: 25 [6656/9756]	Loss: 0.1495	LR: 0.004000
Training Epoch: 25 [6912/9756]	Loss: 0.1709	LR: 0.004000
Training Epoch: 25 [7168/9756]	Loss: 0.1481	LR: 0.004000
Training Epoch: 25 [7424/9756]	Loss: 0.1097	LR: 0.004000
Training Epoch: 25 [7680/9756]	Loss: 0.1850	LR: 0.004000
Training Epoch: 25 [7936/9756]	Loss: 0.1787	LR: 0.004000
Training Epoch: 25 [8192/9756]	Loss: 0.1190	LR: 0.004000
Training Epoch: 25 [8448/9756]	Loss: 0.1718	LR: 0.004000
Training Epoch: 25 [8704/9756]	Loss: 0.1489	LR: 0.004000
Training Epoch: 25 [8960/9756]	Loss: 0.1655	LR: 0.004000
Training Epoch: 25 [9216/9756]	Loss: 0.1367	LR: 0.004000
Training Epoch: 25 [9472/9756]	Loss: 0.1469	LR: 0.004000
Training Epoch: 25 [9728/9756]	Loss: 0.1822	LR: 0.004000
Training Epoch: 25 [9756/9756]	Loss: 0.3051	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1569, Train Accuracy: 0.9336
Epoch 25 training time consumed: 141.01s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9458, Time consumed:8.07s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_08h_24m_25s/ResNet18-MUCAC-seed8-ret25-25-best.pth
Training Epoch: 26 [256/9756]	Loss: 0.1494	LR: 0.004000
Training Epoch: 26 [512/9756]	Loss: 0.1314	LR: 0.004000
Training Epoch: 26 [768/9756]	Loss: 0.1675	LR: 0.004000
Training Epoch: 26 [1024/9756]	Loss: 0.1803	LR: 0.004000
Training Epoch: 26 [1280/9756]	Loss: 0.1357	LR: 0.004000
Training Epoch: 26 [1536/9756]	Loss: 0.1543	LR: 0.004000
Training Epoch: 26 [1792/9756]	Loss: 0.1409	LR: 0.004000
Training Epoch: 26 [2048/9756]	Loss: 0.1375	LR: 0.004000
Training Epoch: 26 [2304/9756]	Loss: 0.2015	LR: 0.004000
Training Epoch: 26 [2560/9756]	Loss: 0.2013	LR: 0.004000
Training Epoch: 26 [2816/9756]	Loss: 0.1544	LR: 0.004000
Training Epoch: 26 [3072/9756]	Loss: 0.2220	LR: 0.004000
Training Epoch: 26 [3328/9756]	Loss: 0.1496	LR: 0.004000
Training Epoch: 26 [3584/9756]	Loss: 0.1455	LR: 0.004000
Training Epoch: 26 [3840/9756]	Loss: 0.1868	LR: 0.004000
Training Epoch: 26 [4096/9756]	Loss: 0.1137	LR: 0.004000
Training Epoch: 26 [4352/9756]	Loss: 0.1195	LR: 0.004000
Training Epoch: 26 [4608/9756]	Loss: 0.1252	LR: 0.004000
Training Epoch: 26 [4864/9756]	Loss: 0.1748	LR: 0.004000
Training Epoch: 26 [5120/9756]	Loss: 0.1723	LR: 0.004000
Training Epoch: 26 [5376/9756]	Loss: 0.1380	LR: 0.004000
Training Epoch: 26 [5632/9756]	Loss: 0.1280	LR: 0.004000
Training Epoch: 26 [5888/9756]	Loss: 0.1248	LR: 0.004000
Training Epoch: 26 [6144/9756]	Loss: 0.2229	LR: 0.004000
Training Epoch: 26 [6400/9756]	Loss: 0.1494	LR: 0.004000
Training Epoch: 26 [6656/9756]	Loss: 0.1703	LR: 0.004000
Training Epoch: 26 [6912/9756]	Loss: 0.1914	LR: 0.004000
Training Epoch: 26 [7168/9756]	Loss: 0.1596	LR: 0.004000
Training Epoch: 26 [7424/9756]	Loss: 0.1497	LR: 0.004000
Training Epoch: 26 [7680/9756]	Loss: 0.1094	LR: 0.004000
Training Epoch: 26 [7936/9756]	Loss: 0.1414	LR: 0.004000
Training Epoch: 26 [8192/9756]	Loss: 0.1761	LR: 0.004000
Training Epoch: 26 [8448/9756]	Loss: 0.1332	LR: 0.004000
Training Epoch: 26 [8704/9756]	Loss: 0.2000	LR: 0.004000
Training Epoch: 26 [8960/9756]	Loss: 0.1963	LR: 0.004000
Training Epoch: 26 [9216/9756]	Loss: 0.1460	LR: 0.004000
Training Epoch: 26 [9472/9756]	Loss: 0.1786	LR: 0.004000
Training Epoch: 26 [9728/9756]	Loss: 0.1217	LR: 0.004000
Training Epoch: 26 [9756/9756]	Loss: 0.0923	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1577, Train Accuracy: 0.9345
Epoch 26 training time consumed: 141.00s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9433, Time consumed:7.90s
Training Epoch: 27 [256/9756]	Loss: 0.1416	LR: 0.004000
Training Epoch: 27 [512/9756]	Loss: 0.1202	LR: 0.004000
Training Epoch: 27 [768/9756]	Loss: 0.1396	LR: 0.004000
Training Epoch: 27 [1024/9756]	Loss: 0.1538	LR: 0.004000
Training Epoch: 27 [1280/9756]	Loss: 0.1195	LR: 0.004000
Training Epoch: 27 [1536/9756]	Loss: 0.1240	LR: 0.004000
Training Epoch: 27 [1792/9756]	Loss: 0.1431	LR: 0.004000
Training Epoch: 27 [2048/9756]	Loss: 0.1365	LR: 0.004000
Training Epoch: 27 [2304/9756]	Loss: 0.1138	LR: 0.004000
Training Epoch: 27 [2560/9756]	Loss: 0.1427	LR: 0.004000
Training Epoch: 27 [2816/9756]	Loss: 0.1573	LR: 0.004000
Training Epoch: 27 [3072/9756]	Loss: 0.1707	LR: 0.004000
Training Epoch: 27 [3328/9756]	Loss: 0.1866	LR: 0.004000
Training Epoch: 27 [3584/9756]	Loss: 0.1755	LR: 0.004000
Training Epoch: 27 [3840/9756]	Loss: 0.1610	LR: 0.004000
Training Epoch: 27 [4096/9756]	Loss: 0.1647	LR: 0.004000
Training Epoch: 27 [4352/9756]	Loss: 0.1185	LR: 0.004000
Training Epoch: 27 [4608/9756]	Loss: 0.1593	LR: 0.004000
Training Epoch: 27 [4864/9756]	Loss: 0.1224	LR: 0.004000
Training Epoch: 27 [5120/9756]	Loss: 0.1510	LR: 0.004000
Training Epoch: 27 [5376/9756]	Loss: 0.1639	LR: 0.004000
Training Epoch: 27 [5632/9756]	Loss: 0.2056	LR: 0.004000
Training Epoch: 27 [5888/9756]	Loss: 0.1948	LR: 0.004000
Training Epoch: 27 [6144/9756]	Loss: 0.1425	LR: 0.004000
Training Epoch: 27 [6400/9756]	Loss: 0.1674	LR: 0.004000
Training Epoch: 27 [6656/9756]	Loss: 0.2016	LR: 0.004000
Training Epoch: 27 [6912/9756]	Loss: 0.2276	LR: 0.004000
Training Epoch: 27 [7168/9756]	Loss: 0.1356	LR: 0.004000
Training Epoch: 27 [7424/9756]	Loss: 0.1190	LR: 0.004000
Training Epoch: 27 [7680/9756]	Loss: 0.1283	LR: 0.004000
Training Epoch: 27 [7936/9756]	Loss: 0.1452	LR: 0.004000
Training Epoch: 27 [8192/9756]	Loss: 0.1291	LR: 0.004000
Training Epoch: 27 [8448/9756]	Loss: 0.1237	LR: 0.004000
Training Epoch: 27 [8704/9756]	Loss: 0.1319	LR: 0.004000
Training Epoch: 27 [8960/9756]	Loss: 0.1245	LR: 0.004000
Training Epoch: 27 [9216/9756]	Loss: 0.1804	LR: 0.004000
Training Epoch: 27 [9472/9756]	Loss: 0.1450	LR: 0.004000
Training Epoch: 27 [9728/9756]	Loss: 0.2129	LR: 0.004000
Training Epoch: 27 [9756/9756]	Loss: 0.1078	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1520, Train Accuracy: 0.9378
Epoch 27 training time consumed: 141.39s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0005, Accuracy: 0.9438, Time consumed:8.12s
Training Epoch: 28 [256/9756]	Loss: 0.1388	LR: 0.004000
Training Epoch: 28 [512/9756]	Loss: 0.1495	LR: 0.004000
Training Epoch: 28 [768/9756]	Loss: 0.1247	LR: 0.004000
Training Epoch: 28 [1024/9756]	Loss: 0.1723	LR: 0.004000
Training Epoch: 28 [1280/9756]	Loss: 0.1516	LR: 0.004000
Training Epoch: 28 [1536/9756]	Loss: 0.1653	LR: 0.004000
Training Epoch: 28 [1792/9756]	Loss: 0.1134	LR: 0.004000
Training Epoch: 28 [2048/9756]	Loss: 0.1277	LR: 0.004000
Training Epoch: 28 [2304/9756]	Loss: 0.1152	LR: 0.004000
Training Epoch: 28 [2560/9756]	Loss: 0.1037	LR: 0.004000
Training Epoch: 28 [2816/9756]	Loss: 0.1047	LR: 0.004000
Training Epoch: 28 [3072/9756]	Loss: 0.1515	LR: 0.004000
Training Epoch: 28 [3328/9756]	Loss: 0.1944	LR: 0.004000
Training Epoch: 28 [3584/9756]	Loss: 0.1736	LR: 0.004000
Training Epoch: 28 [3840/9756]	Loss: 0.1639	LR: 0.004000
Training Epoch: 28 [4096/9756]	Loss: 0.1543	LR: 0.004000
Training Epoch: 28 [4352/9756]	Loss: 0.1725	LR: 0.004000
Training Epoch: 28 [4608/9756]	Loss: 0.1518	LR: 0.004000
Training Epoch: 28 [4864/9756]	Loss: 0.1569	LR: 0.004000
Training Epoch: 28 [5120/9756]	Loss: 0.2217	LR: 0.004000
Training Epoch: 28 [5376/9756]	Loss: 0.1474	LR: 0.004000
Training Epoch: 28 [5632/9756]	Loss: 0.1430	LR: 0.004000
Training Epoch: 28 [5888/9756]	Loss: 0.1923	LR: 0.004000
Training Epoch: 28 [6144/9756]	Loss: 0.1863	LR: 0.004000
Training Epoch: 28 [6400/9756]	Loss: 0.1632	LR: 0.004000
Training Epoch: 28 [6656/9756]	Loss: 0.1561	LR: 0.004000
Training Epoch: 28 [6912/9756]	Loss: 0.1798	LR: 0.004000
Training Epoch: 28 [7168/9756]	Loss: 0.1206	LR: 0.004000
Training Epoch: 28 [7424/9756]	Loss: 0.1614	LR: 0.004000
Training Epoch: 28 [7680/9756]	Loss: 0.0956	LR: 0.004000
Training Epoch: 28 [7936/9756]	Loss: 0.1067	LR: 0.004000
Training Epoch: 28 [8192/9756]	Loss: 0.1716	LR: 0.004000
Training Epoch: 28 [8448/9756]	Loss: 0.1651	LR: 0.004000
Training Epoch: 28 [8704/9756]	Loss: 0.1102	LR: 0.004000
Training Epoch: 28 [8960/9756]	Loss: 0.1736	LR: 0.004000
Training Epoch: 28 [9216/9756]	Loss: 0.1600	LR: 0.004000
Training Epoch: 28 [9472/9756]	Loss: 0.1517	LR: 0.004000
Training Epoch: 28 [9728/9756]	Loss: 0.1660	LR: 0.004000
Training Epoch: 28 [9756/9756]	Loss: 0.0906	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1513, Train Accuracy: 0.9388
Epoch 28 training time consumed: 142.85s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0007, Accuracy: 0.9312, Time consumed:7.98s
Training Epoch: 29 [256/9756]	Loss: 0.1029	LR: 0.004000
Training Epoch: 29 [512/9756]	Loss: 0.1149	LR: 0.004000
Training Epoch: 29 [768/9756]	Loss: 0.1397	LR: 0.004000
Training Epoch: 29 [1024/9756]	Loss: 0.1338	LR: 0.004000
Training Epoch: 29 [1280/9756]	Loss: 0.1885	LR: 0.004000
Training Epoch: 29 [1536/9756]	Loss: 0.1696	LR: 0.004000
Training Epoch: 29 [1792/9756]	Loss: 0.1646	LR: 0.004000
Training Epoch: 29 [2048/9756]	Loss: 0.1452	LR: 0.004000
Training Epoch: 29 [2304/9756]	Loss: 0.1370	LR: 0.004000
Training Epoch: 29 [2560/9756]	Loss: 0.1690	LR: 0.004000
Training Epoch: 29 [2816/9756]	Loss: 0.1585	LR: 0.004000
Training Epoch: 29 [3072/9756]	Loss: 0.2127	LR: 0.004000
Training Epoch: 29 [3328/9756]	Loss: 0.1255	LR: 0.004000
Training Epoch: 29 [3584/9756]	Loss: 0.1765	LR: 0.004000
Training Epoch: 29 [3840/9756]	Loss: 0.1306	LR: 0.004000
Training Epoch: 29 [4096/9756]	Loss: 0.1762	LR: 0.004000
Training Epoch: 29 [4352/9756]	Loss: 0.1410	LR: 0.004000
Training Epoch: 29 [4608/9756]	Loss: 0.1527	LR: 0.004000
Training Epoch: 29 [4864/9756]	Loss: 0.1778	LR: 0.004000
Training Epoch: 29 [5120/9756]	Loss: 0.1174	LR: 0.004000
Training Epoch: 29 [5376/9756]	Loss: 0.2105	LR: 0.004000
Training Epoch: 29 [5632/9756]	Loss: 0.1092	LR: 0.004000
Training Epoch: 29 [5888/9756]	Loss: 0.0831	LR: 0.004000
Training Epoch: 29 [6144/9756]	Loss: 0.1383	LR: 0.004000
Training Epoch: 29 [6400/9756]	Loss: 0.1213	LR: 0.004000
Training Epoch: 29 [6656/9756]	Loss: 0.1624	LR: 0.004000
Training Epoch: 29 [6912/9756]	Loss: 0.1305	LR: 0.004000
Training Epoch: 29 [7168/9756]	Loss: 0.2029	LR: 0.004000
Training Epoch: 29 [7424/9756]	Loss: 0.1797	LR: 0.004000
Training Epoch: 29 [7680/9756]	Loss: 0.1500	LR: 0.004000
Training Epoch: 29 [7936/9756]	Loss: 0.1678	LR: 0.004000
Training Epoch: 29 [8192/9756]	Loss: 0.1076	LR: 0.004000
Training Epoch: 29 [8448/9756]	Loss: 0.1811	LR: 0.004000
Training Epoch: 29 [8704/9756]	Loss: 0.1589	LR: 0.004000
Training Epoch: 29 [8960/9756]	Loss: 0.1174	LR: 0.004000
Training Epoch: 29 [9216/9756]	Loss: 0.1490	LR: 0.004000
Training Epoch: 29 [9472/9756]	Loss: 0.1715	LR: 0.004000
Training Epoch: 29 [9728/9756]	Loss: 0.1405	LR: 0.004000
Training Epoch: 29 [9756/9756]	Loss: 0.1006	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1503, Train Accuracy: 0.9370
Epoch 29 training time consumed: 143.16s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0007, Accuracy: 0.9356, Time consumed:8.31s
Training Epoch: 30 [256/9756]	Loss: 0.1945	LR: 0.004000
Training Epoch: 30 [512/9756]	Loss: 0.1766	LR: 0.004000
Training Epoch: 30 [768/9756]	Loss: 0.1161	LR: 0.004000
Training Epoch: 30 [1024/9756]	Loss: 0.1372	LR: 0.004000
Training Epoch: 30 [1280/9756]	Loss: 0.1007	LR: 0.004000
Training Epoch: 30 [1536/9756]	Loss: 0.1717	LR: 0.004000
Training Epoch: 30 [1792/9756]	Loss: 0.1089	LR: 0.004000
Training Epoch: 30 [2048/9756]	Loss: 0.1344	LR: 0.004000
Training Epoch: 30 [2304/9756]	Loss: 0.1683	LR: 0.004000
Training Epoch: 30 [2560/9756]	Loss: 0.1335	LR: 0.004000
Training Epoch: 30 [2816/9756]	Loss: 0.1224	LR: 0.004000
Training Epoch: 30 [3072/9756]	Loss: 0.1143	LR: 0.004000
Training Epoch: 30 [3328/9756]	Loss: 0.1875	LR: 0.004000
Training Epoch: 30 [3584/9756]	Loss: 0.1681	LR: 0.004000
Training Epoch: 30 [3840/9756]	Loss: 0.1216	LR: 0.004000
Training Epoch: 30 [4096/9756]	Loss: 0.1619	LR: 0.004000
Training Epoch: 30 [4352/9756]	Loss: 0.1847	LR: 0.004000
Training Epoch: 30 [4608/9756]	Loss: 0.1431	LR: 0.004000
Training Epoch: 30 [4864/9756]	Loss: 0.1552	LR: 0.004000
Training Epoch: 30 [5120/9756]	Loss: 0.1372	LR: 0.004000
Training Epoch: 30 [5376/9756]	Loss: 0.1599	LR: 0.004000
Training Epoch: 30 [5632/9756]	Loss: 0.1340	LR: 0.004000
Training Epoch: 30 [5888/9756]	Loss: 0.1167	LR: 0.004000
Training Epoch: 30 [6144/9756]	Loss: 0.1409	LR: 0.004000
Training Epoch: 30 [6400/9756]	Loss: 0.1607	LR: 0.004000
Training Epoch: 30 [6656/9756]	Loss: 0.1662	LR: 0.004000
Training Epoch: 30 [6912/9756]	Loss: 0.0794	LR: 0.004000
Training Epoch: 30 [7168/9756]	Loss: 0.1557	LR: 0.004000
Training Epoch: 30 [7424/9756]	Loss: 0.1432	LR: 0.004000
Training Epoch: 30 [7680/9756]	Loss: 0.1509	LR: 0.004000
Training Epoch: 30 [7936/9756]	Loss: 0.1798	LR: 0.004000
Training Epoch: 30 [8192/9756]	Loss: 0.1216	LR: 0.004000
Training Epoch: 30 [8448/9756]	Loss: 0.1921	LR: 0.004000
Training Epoch: 30 [8704/9756]	Loss: 0.1643	LR: 0.004000
Training Epoch: 30 [8960/9756]	Loss: 0.1176	LR: 0.004000
Training Epoch: 30 [9216/9756]	Loss: 0.0951	LR: 0.004000
Training Epoch: 30 [9472/9756]	Loss: 0.1766	LR: 0.004000
Training Epoch: 30 [9728/9756]	Loss: 0.1450	LR: 0.004000
Training Epoch: 30 [9756/9756]	Loss: 0.3048	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1462, Train Accuracy: 0.9384
Epoch 30 training time consumed: 143.13s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9380, Time consumed:8.06s
Training Epoch: 31 [256/9756]	Loss: 0.1267	LR: 0.004000
Training Epoch: 31 [512/9756]	Loss: 0.0986	LR: 0.004000
Training Epoch: 31 [768/9756]	Loss: 0.1641	LR: 0.004000
Training Epoch: 31 [1024/9756]	Loss: 0.1769	LR: 0.004000
Training Epoch: 31 [1280/9756]	Loss: 0.1572	LR: 0.004000
Training Epoch: 31 [1536/9756]	Loss: 0.1662	LR: 0.004000
Training Epoch: 31 [1792/9756]	Loss: 0.1349	LR: 0.004000
Training Epoch: 31 [2048/9756]	Loss: 0.1392	LR: 0.004000
Training Epoch: 31 [2304/9756]	Loss: 0.1324	LR: 0.004000
Training Epoch: 31 [2560/9756]	Loss: 0.1930	LR: 0.004000
Training Epoch: 31 [2816/9756]	Loss: 0.1220	LR: 0.004000
Training Epoch: 31 [3072/9756]	Loss: 0.1067	LR: 0.004000
Training Epoch: 31 [3328/9756]	Loss: 0.1209	LR: 0.004000
Training Epoch: 31 [3584/9756]	Loss: 0.1301	LR: 0.004000
Training Epoch: 31 [3840/9756]	Loss: 0.1703	LR: 0.004000
Training Epoch: 31 [4096/9756]	Loss: 0.1424	LR: 0.004000
Training Epoch: 31 [4352/9756]	Loss: 0.1189	LR: 0.004000
Training Epoch: 31 [4608/9756]	Loss: 0.1572	LR: 0.004000
Training Epoch: 31 [4864/9756]	Loss: 0.1676	LR: 0.004000
Training Epoch: 31 [5120/9756]	Loss: 0.1167	LR: 0.004000
Training Epoch: 31 [5376/9756]	Loss: 0.1167	LR: 0.004000
Training Epoch: 31 [5632/9756]	Loss: 0.1368	LR: 0.004000
Training Epoch: 31 [5888/9756]	Loss: 0.1290	LR: 0.004000
Training Epoch: 31 [6144/9756]	Loss: 0.1128	LR: 0.004000
Training Epoch: 31 [6400/9756]	Loss: 0.1228	LR: 0.004000
Training Epoch: 31 [6656/9756]	Loss: 0.1267	LR: 0.004000
Training Epoch: 31 [6912/9756]	Loss: 0.1199	LR: 0.004000
Training Epoch: 31 [7168/9756]	Loss: 0.1576	LR: 0.004000
Training Epoch: 31 [7424/9756]	Loss: 0.1312	LR: 0.004000
Training Epoch: 31 [7680/9756]	Loss: 0.1895	LR: 0.004000
Training Epoch: 31 [7936/9756]	Loss: 0.1843	LR: 0.004000
Training Epoch: 31 [8192/9756]	Loss: 0.1618	LR: 0.004000
Training Epoch: 31 [8448/9756]	Loss: 0.1667	LR: 0.004000
Training Epoch: 31 [8704/9756]	Loss: 0.2086	LR: 0.004000
Training Epoch: 31 [8960/9756]	Loss: 0.1392	LR: 0.004000
Training Epoch: 31 [9216/9756]	Loss: 0.1576	LR: 0.004000
Training Epoch: 31 [9472/9756]	Loss: 0.1428	LR: 0.004000
Training Epoch: 31 [9728/9756]	Loss: 0.1304	LR: 0.004000
Training Epoch: 31 [9756/9756]	Loss: 0.2520	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1444, Train Accuracy: 0.9414
Epoch 31 training time consumed: 140.98s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9400, Time consumed:7.99s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  9756
Forget Train Dl:  792
Retain Valid Dl:  9756
Forget Valid Dl:  792
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 792 samples
Set1 Distribution: 792 samples
Set2 Distribution: 792 samples
Set1 Distribution: 792 samples
Set2 Distribution: 792 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 94.00786590576172
Retain Accuracy: 94.21073913574219
Zero-Retain Forget (ZRF): 0.7806111574172974
Membership Inference Attack (MIA): 0.33585858585858586
Forget vs Retain Membership Inference Attack (MIA): 0.5394321766561514
Forget vs Test Membership Inference Attack (MIA): 0.555205047318612
Test vs Retain Membership Inference Attack (MIA): 0.5181598062953995
Train vs Test Membership Inference Attack (MIA): 0.5314769975786925
Forget Set Accuracy (Df): 92.93620300292969
Method Execution Time: 5798.43 seconds
