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

📌 S Retain class distribution for seed 2:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 2:
Class 0: 527
Class 1: 527

📊 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: 0.7026	LR: 0.000000
Training Epoch: 1 [512/9756]	Loss: 0.6863	LR: 0.002564
Training Epoch: 1 [768/9756]	Loss: 0.6872	LR: 0.005128
Training Epoch: 1 [1024/9756]	Loss: 0.6844	LR: 0.007692
Training Epoch: 1 [1280/9756]	Loss: 0.6916	LR: 0.010256
Training Epoch: 1 [1536/9756]	Loss: 0.6941	LR: 0.012821
Training Epoch: 1 [1792/9756]	Loss: 0.6679	LR: 0.015385
Training Epoch: 1 [2048/9756]	Loss: 0.7170	LR: 0.017949
Training Epoch: 1 [2304/9756]	Loss: 0.6925	LR: 0.020513
Training Epoch: 1 [2560/9756]	Loss: 0.7617	LR: 0.023077
Training Epoch: 1 [2816/9756]	Loss: 0.7368	LR: 0.025641
Training Epoch: 1 [3072/9756]	Loss: 0.7205	LR: 0.028205
Training Epoch: 1 [3328/9756]	Loss: 0.8091	LR: 0.030769
Training Epoch: 1 [3584/9756]	Loss: 1.0175	LR: 0.033333
Training Epoch: 1 [3840/9756]	Loss: 1.3191	LR: 0.035897
Training Epoch: 1 [4096/9756]	Loss: 1.9032	LR: 0.038462
Training Epoch: 1 [4352/9756]	Loss: 1.2617	LR: 0.041026
Training Epoch: 1 [4608/9756]	Loss: 0.7120	LR: 0.043590
Training Epoch: 1 [4864/9756]	Loss: 0.9523	LR: 0.046154
Training Epoch: 1 [5120/9756]	Loss: 0.9962	LR: 0.048718
Training Epoch: 1 [5376/9756]	Loss: 0.8117	LR: 0.051282
Training Epoch: 1 [5632/9756]	Loss: 0.8640	LR: 0.053846
Training Epoch: 1 [5888/9756]	Loss: 0.9026	LR: 0.056410
Training Epoch: 1 [6144/9756]	Loss: 0.9000	LR: 0.058974
Training Epoch: 1 [6400/9756]	Loss: 1.0743	LR: 0.061538
Training Epoch: 1 [6656/9756]	Loss: 0.7779	LR: 0.064103
Training Epoch: 1 [6912/9756]	Loss: 0.7534	LR: 0.066667
Training Epoch: 1 [7168/9756]	Loss: 0.8572	LR: 0.069231
Training Epoch: 1 [7424/9756]	Loss: 0.9579	LR: 0.071795
Training Epoch: 1 [7680/9756]	Loss: 0.7945	LR: 0.074359
Training Epoch: 1 [7936/9756]	Loss: 0.9527	LR: 0.076923
Training Epoch: 1 [8192/9756]	Loss: 1.4803	LR: 0.079487
Training Epoch: 1 [8448/9756]	Loss: 1.2386	LR: 0.082051
Training Epoch: 1 [8704/9756]	Loss: 1.5578	LR: 0.084615
Training Epoch: 1 [8960/9756]	Loss: 1.2128	LR: 0.087179
Training Epoch: 1 [9216/9756]	Loss: 2.1785	LR: 0.089744
Training Epoch: 1 [9472/9756]	Loss: 0.9115	LR: 0.092308
Training Epoch: 1 [9728/9756]	Loss: 2.8325	LR: 0.094872
Training Epoch: 1 [9756/9756]	Loss: 1.1160	LR: 0.097436
Epoch 1 - Average Train Loss: 1.0127, Train Accuracy: 0.5169
Epoch 1 training time consumed: 338.07s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 1.2710, Accuracy: 0.5550, Time consumed:8.18s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-1-best.pth
Training Epoch: 2 [256/9756]	Loss: 0.7444	LR: 0.100000
Training Epoch: 2 [512/9756]	Loss: 1.2503	LR: 0.100000
Training Epoch: 2 [768/9756]	Loss: 0.8417	LR: 0.100000
Training Epoch: 2 [1024/9756]	Loss: 1.0718	LR: 0.100000
Training Epoch: 2 [1280/9756]	Loss: 1.0057	LR: 0.100000
Training Epoch: 2 [1536/9756]	Loss: 0.7359	LR: 0.100000
Training Epoch: 2 [1792/9756]	Loss: 0.7447	LR: 0.100000
Training Epoch: 2 [2048/9756]	Loss: 0.8619	LR: 0.100000
Training Epoch: 2 [2304/9756]	Loss: 0.7443	LR: 0.100000
Training Epoch: 2 [2560/9756]	Loss: 0.7120	LR: 0.100000
Training Epoch: 2 [2816/9756]	Loss: 0.7249	LR: 0.100000
Training Epoch: 2 [3072/9756]	Loss: 0.7393	LR: 0.100000
Training Epoch: 2 [3328/9756]	Loss: 0.7358	LR: 0.100000
Training Epoch: 2 [3584/9756]	Loss: 0.7063	LR: 0.100000
Training Epoch: 2 [3840/9756]	Loss: 0.7864	LR: 0.100000
Training Epoch: 2 [4096/9756]	Loss: 0.7623	LR: 0.100000
Training Epoch: 2 [4352/9756]	Loss: 0.7847	LR: 0.100000
Training Epoch: 2 [4608/9756]	Loss: 0.7349	LR: 0.100000
Training Epoch: 2 [4864/9756]	Loss: 0.7425	LR: 0.100000
Training Epoch: 2 [5120/9756]	Loss: 0.7803	LR: 0.100000
Training Epoch: 2 [5376/9756]	Loss: 0.7007	LR: 0.100000
Training Epoch: 2 [5632/9756]	Loss: 0.6877	LR: 0.100000
Training Epoch: 2 [5888/9756]	Loss: 0.6956	LR: 0.100000
Training Epoch: 2 [6144/9756]	Loss: 0.7200	LR: 0.100000
Training Epoch: 2 [6400/9756]	Loss: 0.6831	LR: 0.100000
Training Epoch: 2 [6656/9756]	Loss: 0.6904	LR: 0.100000
Training Epoch: 2 [6912/9756]	Loss: 0.6943	LR: 0.100000
Training Epoch: 2 [7168/9756]	Loss: 0.6905	LR: 0.100000
Training Epoch: 2 [7424/9756]	Loss: 0.7112	LR: 0.100000
Training Epoch: 2 [7680/9756]	Loss: 0.7126	LR: 0.100000
Training Epoch: 2 [7936/9756]	Loss: 0.7592	LR: 0.100000
Training Epoch: 2 [8192/9756]	Loss: 0.7068	LR: 0.100000
Training Epoch: 2 [8448/9756]	Loss: 0.7275	LR: 0.100000
Training Epoch: 2 [8704/9756]	Loss: 0.7129	LR: 0.100000
Training Epoch: 2 [8960/9756]	Loss: 0.6840	LR: 0.100000
Training Epoch: 2 [9216/9756]	Loss: 0.6913	LR: 0.100000
Training Epoch: 2 [9472/9756]	Loss: 0.6874	LR: 0.100000
Training Epoch: 2 [9728/9756]	Loss: 0.7010	LR: 0.100000
Training Epoch: 2 [9756/9756]	Loss: 0.6395	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7593, Train Accuracy: 0.5251
Epoch 2 training time consumed: 141.33s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0030, Accuracy: 0.5617, Time consumed:8.00s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-2-best.pth
Training Epoch: 3 [256/9756]	Loss: 0.7377	LR: 0.100000
Training Epoch: 3 [512/9756]	Loss: 0.6868	LR: 0.100000
Training Epoch: 3 [768/9756]	Loss: 0.7040	LR: 0.100000
Training Epoch: 3 [1024/9756]	Loss: 0.7477	LR: 0.100000
Training Epoch: 3 [1280/9756]	Loss: 0.7976	LR: 0.100000
Training Epoch: 3 [1536/9756]	Loss: 0.7374	LR: 0.100000
Training Epoch: 3 [1792/9756]	Loss: 0.6987	LR: 0.100000
Training Epoch: 3 [2048/9756]	Loss: 0.7115	LR: 0.100000
Training Epoch: 3 [2304/9756]	Loss: 0.7477	LR: 0.100000
Training Epoch: 3 [2560/9756]	Loss: 0.8041	LR: 0.100000
Training Epoch: 3 [2816/9756]	Loss: 0.8338	LR: 0.100000
Training Epoch: 3 [3072/9756]	Loss: 0.7352	LR: 0.100000
Training Epoch: 3 [3328/9756]	Loss: 0.7676	LR: 0.100000
Training Epoch: 3 [3584/9756]	Loss: 0.7144	LR: 0.100000
Training Epoch: 3 [3840/9756]	Loss: 0.6774	LR: 0.100000
Training Epoch: 3 [4096/9756]	Loss: 0.8176	LR: 0.100000
Training Epoch: 3 [4352/9756]	Loss: 0.8753	LR: 0.100000
Training Epoch: 3 [4608/9756]	Loss: 0.7222	LR: 0.100000
Training Epoch: 3 [4864/9756]	Loss: 0.6935	LR: 0.100000
Training Epoch: 3 [5120/9756]	Loss: 0.7583	LR: 0.100000
Training Epoch: 3 [5376/9756]	Loss: 0.7212	LR: 0.100000
Training Epoch: 3 [5632/9756]	Loss: 0.7125	LR: 0.100000
Training Epoch: 3 [5888/9756]	Loss: 0.7239	LR: 0.100000
Training Epoch: 3 [6144/9756]	Loss: 0.7519	LR: 0.100000
Training Epoch: 3 [6400/9756]	Loss: 0.7102	LR: 0.100000
Training Epoch: 3 [6656/9756]	Loss: 0.6805	LR: 0.100000
Training Epoch: 3 [6912/9756]	Loss: 0.6825	LR: 0.100000
Training Epoch: 3 [7168/9756]	Loss: 0.7146	LR: 0.100000
Training Epoch: 3 [7424/9756]	Loss: 0.7424	LR: 0.100000
Training Epoch: 3 [7680/9756]	Loss: 0.7044	LR: 0.100000
Training Epoch: 3 [7936/9756]	Loss: 0.6868	LR: 0.100000
Training Epoch: 3 [8192/9756]	Loss: 0.6939	LR: 0.100000
Training Epoch: 3 [8448/9756]	Loss: 0.6799	LR: 0.100000
Training Epoch: 3 [8704/9756]	Loss: 0.7118	LR: 0.100000
Training Epoch: 3 [8960/9756]	Loss: 0.6880	LR: 0.100000
Training Epoch: 3 [9216/9756]	Loss: 0.7018	LR: 0.100000
Training Epoch: 3 [9472/9756]	Loss: 0.7034	LR: 0.100000
Training Epoch: 3 [9728/9756]	Loss: 0.7024	LR: 0.100000
Training Epoch: 3 [9756/9756]	Loss: 0.7028	LR: 0.100000
Epoch 3 - Average Train Loss: 0.7284, Train Accuracy: 0.5274
Epoch 3 training time consumed: 140.79s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5763, Time consumed:8.22s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-3-best.pth
Training Epoch: 4 [256/9756]	Loss: 0.6828	LR: 0.100000
Training Epoch: 4 [512/9756]	Loss: 0.6793	LR: 0.100000
Training Epoch: 4 [768/9756]	Loss: 0.8389	LR: 0.100000
Training Epoch: 4 [1024/9756]	Loss: 0.7684	LR: 0.100000
Training Epoch: 4 [1280/9756]	Loss: 0.6784	LR: 0.100000
Training Epoch: 4 [1536/9756]	Loss: 0.6879	LR: 0.100000
Training Epoch: 4 [1792/9756]	Loss: 0.7101	LR: 0.100000
Training Epoch: 4 [2048/9756]	Loss: 0.7037	LR: 0.100000
Training Epoch: 4 [2304/9756]	Loss: 0.6710	LR: 0.100000
Training Epoch: 4 [2560/9756]	Loss: 0.6867	LR: 0.100000
Training Epoch: 4 [2816/9756]	Loss: 0.6956	LR: 0.100000
Training Epoch: 4 [3072/9756]	Loss: 0.6906	LR: 0.100000
Training Epoch: 4 [3328/9756]	Loss: 0.6868	LR: 0.100000
Training Epoch: 4 [3584/9756]	Loss: 0.7038	LR: 0.100000
Training Epoch: 4 [3840/9756]	Loss: 0.7059	LR: 0.100000
Training Epoch: 4 [4096/9756]	Loss: 0.6936	LR: 0.100000
Training Epoch: 4 [4352/9756]	Loss: 0.6930	LR: 0.100000
Training Epoch: 4 [4608/9756]	Loss: 0.6947	LR: 0.100000
Training Epoch: 4 [4864/9756]	Loss: 0.6860	LR: 0.100000
Training Epoch: 4 [5120/9756]	Loss: 0.6836	LR: 0.100000
Training Epoch: 4 [5376/9756]	Loss: 0.6838	LR: 0.100000
Training Epoch: 4 [5632/9756]	Loss: 0.6822	LR: 0.100000
Training Epoch: 4 [5888/9756]	Loss: 0.7093	LR: 0.100000
Training Epoch: 4 [6144/9756]	Loss: 0.6965	LR: 0.100000
Training Epoch: 4 [6400/9756]	Loss: 0.6791	LR: 0.100000
Training Epoch: 4 [6656/9756]	Loss: 0.7235	LR: 0.100000
Training Epoch: 4 [6912/9756]	Loss: 0.7251	LR: 0.100000
Training Epoch: 4 [7168/9756]	Loss: 0.6855	LR: 0.100000
Training Epoch: 4 [7424/9756]	Loss: 0.6854	LR: 0.100000
Training Epoch: 4 [7680/9756]	Loss: 0.6611	LR: 0.100000
Training Epoch: 4 [7936/9756]	Loss: 0.7019	LR: 0.100000
Training Epoch: 4 [8192/9756]	Loss: 0.7505	LR: 0.100000
Training Epoch: 4 [8448/9756]	Loss: 0.6805	LR: 0.100000
Training Epoch: 4 [8704/9756]	Loss: 0.6863	LR: 0.100000
Training Epoch: 4 [8960/9756]	Loss: 0.6922	LR: 0.100000
Training Epoch: 4 [9216/9756]	Loss: 0.6756	LR: 0.100000
Training Epoch: 4 [9472/9756]	Loss: 0.6848	LR: 0.100000
Training Epoch: 4 [9728/9756]	Loss: 0.7160	LR: 0.100000
Training Epoch: 4 [9756/9756]	Loss: 0.6241	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6987, Train Accuracy: 0.5531
Epoch 4 training time consumed: 140.78s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0029, Accuracy: 0.5976, Time consumed:8.16s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-4-best.pth
Training Epoch: 5 [256/9756]	Loss: 0.6808	LR: 0.100000
Training Epoch: 5 [512/9756]	Loss: 0.6962	LR: 0.100000
Training Epoch: 5 [768/9756]	Loss: 0.6807	LR: 0.100000
Training Epoch: 5 [1024/9756]	Loss: 0.6622	LR: 0.100000
Training Epoch: 5 [1280/9756]	Loss: 0.6853	LR: 0.100000
Training Epoch: 5 [1536/9756]	Loss: 0.6770	LR: 0.100000
Training Epoch: 5 [1792/9756]	Loss: 0.6956	LR: 0.100000
Training Epoch: 5 [2048/9756]	Loss: 0.6764	LR: 0.100000
Training Epoch: 5 [2304/9756]	Loss: 0.7023	LR: 0.100000
Training Epoch: 5 [2560/9756]	Loss: 0.6775	LR: 0.100000
Training Epoch: 5 [2816/9756]	Loss: 0.7044	LR: 0.100000
Training Epoch: 5 [3072/9756]	Loss: 0.6830	LR: 0.100000
Training Epoch: 5 [3328/9756]	Loss: 0.6649	LR: 0.100000
Training Epoch: 5 [3584/9756]	Loss: 0.7035	LR: 0.100000
Training Epoch: 5 [3840/9756]	Loss: 0.7010	LR: 0.100000
Training Epoch: 5 [4096/9756]	Loss: 0.7017	LR: 0.100000
Training Epoch: 5 [4352/9756]	Loss: 0.6831	LR: 0.100000
Training Epoch: 5 [4608/9756]	Loss: 0.6729	LR: 0.100000
Training Epoch: 5 [4864/9756]	Loss: 0.7007	LR: 0.100000
Training Epoch: 5 [5120/9756]	Loss: 0.6805	LR: 0.100000
Training Epoch: 5 [5376/9756]	Loss: 0.6691	LR: 0.100000
Training Epoch: 5 [5632/9756]	Loss: 0.6767	LR: 0.100000
Training Epoch: 5 [5888/9756]	Loss: 0.6768	LR: 0.100000
Training Epoch: 5 [6144/9756]	Loss: 0.6559	LR: 0.100000
Training Epoch: 5 [6400/9756]	Loss: 0.6622	LR: 0.100000
Training Epoch: 5 [6656/9756]	Loss: 0.7104	LR: 0.100000
Training Epoch: 5 [6912/9756]	Loss: 0.7033	LR: 0.100000
Training Epoch: 5 [7168/9756]	Loss: 0.6807	LR: 0.100000
Training Epoch: 5 [7424/9756]	Loss: 0.6914	LR: 0.100000
Training Epoch: 5 [7680/9756]	Loss: 0.6507	LR: 0.100000
Training Epoch: 5 [7936/9756]	Loss: 0.6556	LR: 0.100000
Training Epoch: 5 [8192/9756]	Loss: 0.7090	LR: 0.100000
Training Epoch: 5 [8448/9756]	Loss: 0.7552	LR: 0.100000
Training Epoch: 5 [8704/9756]	Loss: 0.6799	LR: 0.100000
Training Epoch: 5 [8960/9756]	Loss: 0.6766	LR: 0.100000
Training Epoch: 5 [9216/9756]	Loss: 0.6841	LR: 0.100000
Training Epoch: 5 [9472/9756]	Loss: 0.6753	LR: 0.100000
Training Epoch: 5 [9728/9756]	Loss: 0.6857	LR: 0.100000
Training Epoch: 5 [9756/9756]	Loss: 0.7012	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6850, Train Accuracy: 0.5749
Epoch 5 training time consumed: 141.01s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0029, Accuracy: 0.5855, Time consumed:8.08s
Training Epoch: 6 [256/9756]	Loss: 0.7061	LR: 0.100000
Training Epoch: 6 [512/9756]	Loss: 0.6750	LR: 0.100000
Training Epoch: 6 [768/9756]	Loss: 0.6839	LR: 0.100000
Training Epoch: 6 [1024/9756]	Loss: 0.7040	LR: 0.100000
Training Epoch: 6 [1280/9756]	Loss: 0.6713	LR: 0.100000
Training Epoch: 6 [1536/9756]	Loss: 0.6859	LR: 0.100000
Training Epoch: 6 [1792/9756]	Loss: 0.6748	LR: 0.100000
Training Epoch: 6 [2048/9756]	Loss: 0.6758	LR: 0.100000
Training Epoch: 6 [2304/9756]	Loss: 0.6703	LR: 0.100000
Training Epoch: 6 [2560/9756]	Loss: 0.6789	LR: 0.100000
Training Epoch: 6 [2816/9756]	Loss: 0.6804	LR: 0.100000
Training Epoch: 6 [3072/9756]	Loss: 0.6888	LR: 0.100000
Training Epoch: 6 [3328/9756]	Loss: 0.7066	LR: 0.100000
Training Epoch: 6 [3584/9756]	Loss: 0.6754	LR: 0.100000
Training Epoch: 6 [3840/9756]	Loss: 0.6786	LR: 0.100000
Training Epoch: 6 [4096/9756]	Loss: 0.6718	LR: 0.100000
Training Epoch: 6 [4352/9756]	Loss: 0.6800	LR: 0.100000
Training Epoch: 6 [4608/9756]	Loss: 0.6549	LR: 0.100000
Training Epoch: 6 [4864/9756]	Loss: 0.6431	LR: 0.100000
Training Epoch: 6 [5120/9756]	Loss: 0.6805	LR: 0.100000
Training Epoch: 6 [5376/9756]	Loss: 0.6737	LR: 0.100000
Training Epoch: 6 [5632/9756]	Loss: 0.6587	LR: 0.100000
Training Epoch: 6 [5888/9756]	Loss: 0.6578	LR: 0.100000
Training Epoch: 6 [6144/9756]	Loss: 0.6717	LR: 0.100000
Training Epoch: 6 [6400/9756]	Loss: 0.6550	LR: 0.100000
Training Epoch: 6 [6656/9756]	Loss: 0.7184	LR: 0.100000
Training Epoch: 6 [6912/9756]	Loss: 0.6518	LR: 0.100000
Training Epoch: 6 [7168/9756]	Loss: 0.6764	LR: 0.100000
Training Epoch: 6 [7424/9756]	Loss: 0.6709	LR: 0.100000
Training Epoch: 6 [7680/9756]	Loss: 0.6686	LR: 0.100000
Training Epoch: 6 [7936/9756]	Loss: 0.6472	LR: 0.100000
Training Epoch: 6 [8192/9756]	Loss: 0.6857	LR: 0.100000
Training Epoch: 6 [8448/9756]	Loss: 0.6736	LR: 0.100000
Training Epoch: 6 [8704/9756]	Loss: 0.6862	LR: 0.100000
Training Epoch: 6 [8960/9756]	Loss: 0.6916	LR: 0.100000
Training Epoch: 6 [9216/9756]	Loss: 0.6774	LR: 0.100000
Training Epoch: 6 [9472/9756]	Loss: 0.6695	LR: 0.100000
Training Epoch: 6 [9728/9756]	Loss: 0.6651	LR: 0.100000
Training Epoch: 6 [9756/9756]	Loss: 0.6842	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6759, Train Accuracy: 0.5906
Epoch 6 training time consumed: 140.88s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0030, Accuracy: 0.6087, Time consumed:7.81s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-6-best.pth
Training Epoch: 7 [256/9756]	Loss: 0.6645	LR: 0.100000
Training Epoch: 7 [512/9756]	Loss: 0.6750	LR: 0.100000
Training Epoch: 7 [768/9756]	Loss: 0.6885	LR: 0.100000
Training Epoch: 7 [1024/9756]	Loss: 0.6581	LR: 0.100000
Training Epoch: 7 [1280/9756]	Loss: 0.6774	LR: 0.100000
Training Epoch: 7 [1536/9756]	Loss: 0.6886	LR: 0.100000
Training Epoch: 7 [1792/9756]	Loss: 0.6388	LR: 0.100000
Training Epoch: 7 [2048/9756]	Loss: 0.7100	LR: 0.100000
Training Epoch: 7 [2304/9756]	Loss: 0.6726	LR: 0.100000
Training Epoch: 7 [2560/9756]	Loss: 0.6738	LR: 0.100000
Training Epoch: 7 [2816/9756]	Loss: 0.6783	LR: 0.100000
Training Epoch: 7 [3072/9756]	Loss: 0.6625	LR: 0.100000
Training Epoch: 7 [3328/9756]	Loss: 0.6611	LR: 0.100000
Training Epoch: 7 [3584/9756]	Loss: 0.7157	LR: 0.100000
Training Epoch: 7 [3840/9756]	Loss: 0.7192	LR: 0.100000
Training Epoch: 7 [4096/9756]	Loss: 0.6649	LR: 0.100000
Training Epoch: 7 [4352/9756]	Loss: 0.6484	LR: 0.100000
Training Epoch: 7 [4608/9756]	Loss: 0.7005	LR: 0.100000
Training Epoch: 7 [4864/9756]	Loss: 0.6772	LR: 0.100000
Training Epoch: 7 [5120/9756]	Loss: 0.6511	LR: 0.100000
Training Epoch: 7 [5376/9756]	Loss: 0.6668	LR: 0.100000
Training Epoch: 7 [5632/9756]	Loss: 0.6719	LR: 0.100000
Training Epoch: 7 [5888/9756]	Loss: 0.6573	LR: 0.100000
Training Epoch: 7 [6144/9756]	Loss: 0.7127	LR: 0.100000
Training Epoch: 7 [6400/9756]	Loss: 0.6910	LR: 0.100000
Training Epoch: 7 [6656/9756]	Loss: 0.6542	LR: 0.100000
Training Epoch: 7 [6912/9756]	Loss: 0.6726	LR: 0.100000
Training Epoch: 7 [7168/9756]	Loss: 0.6772	LR: 0.100000
Training Epoch: 7 [7424/9756]	Loss: 0.6478	LR: 0.100000
Training Epoch: 7 [7680/9756]	Loss: 0.6780	LR: 0.100000
Training Epoch: 7 [7936/9756]	Loss: 0.6453	LR: 0.100000
Training Epoch: 7 [8192/9756]	Loss: 0.6577	LR: 0.100000
Training Epoch: 7 [8448/9756]	Loss: 0.6594	LR: 0.100000
Training Epoch: 7 [8704/9756]	Loss: 0.6927	LR: 0.100000
Training Epoch: 7 [8960/9756]	Loss: 0.6959	LR: 0.100000
Training Epoch: 7 [9216/9756]	Loss: 0.6678	LR: 0.100000
Training Epoch: 7 [9472/9756]	Loss: 0.6498	LR: 0.100000
Training Epoch: 7 [9728/9756]	Loss: 0.6609	LR: 0.100000
Training Epoch: 7 [9756/9756]	Loss: 0.6770	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6733, Train Accuracy: 0.5993
Epoch 7 training time consumed: 141.00s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0030, Accuracy: 0.5985, Time consumed:7.84s
Training Epoch: 8 [256/9756]	Loss: 0.7139	LR: 0.100000
Training Epoch: 8 [512/9756]	Loss: 0.6839	LR: 0.100000
Training Epoch: 8 [768/9756]	Loss: 0.6928	LR: 0.100000
Training Epoch: 8 [1024/9756]	Loss: 0.7096	LR: 0.100000
Training Epoch: 8 [1280/9756]	Loss: 0.6483	LR: 0.100000
Training Epoch: 8 [1536/9756]	Loss: 0.6735	LR: 0.100000
Training Epoch: 8 [1792/9756]	Loss: 0.6684	LR: 0.100000
Training Epoch: 8 [2048/9756]	Loss: 0.6688	LR: 0.100000
Training Epoch: 8 [2304/9756]	Loss: 0.7022	LR: 0.100000
Training Epoch: 8 [2560/9756]	Loss: 0.6561	LR: 0.100000
Training Epoch: 8 [2816/9756]	Loss: 0.6748	LR: 0.100000
Training Epoch: 8 [3072/9756]	Loss: 0.6873	LR: 0.100000
Training Epoch: 8 [3328/9756]	Loss: 0.6713	LR: 0.100000
Training Epoch: 8 [3584/9756]	Loss: 0.6673	LR: 0.100000
Training Epoch: 8 [3840/9756]	Loss: 0.7063	LR: 0.100000
Training Epoch: 8 [4096/9756]	Loss: 0.6738	LR: 0.100000
Training Epoch: 8 [4352/9756]	Loss: 0.6637	LR: 0.100000
Training Epoch: 8 [4608/9756]	Loss: 0.6502	LR: 0.100000
Training Epoch: 8 [4864/9756]	Loss: 0.6726	LR: 0.100000
Training Epoch: 8 [5120/9756]	Loss: 0.7044	LR: 0.100000
Training Epoch: 8 [5376/9756]	Loss: 0.6642	LR: 0.100000
Training Epoch: 8 [5632/9756]	Loss: 0.6862	LR: 0.100000
Training Epoch: 8 [5888/9756]	Loss: 0.6355	LR: 0.100000
Training Epoch: 8 [6144/9756]	Loss: 0.6622	LR: 0.100000
Training Epoch: 8 [6400/9756]	Loss: 0.6646	LR: 0.100000
Training Epoch: 8 [6656/9756]	Loss: 0.6759	LR: 0.100000
Training Epoch: 8 [6912/9756]	Loss: 0.6565	LR: 0.100000
Training Epoch: 8 [7168/9756]	Loss: 0.6595	LR: 0.100000
Training Epoch: 8 [7424/9756]	Loss: 0.6363	LR: 0.100000
Training Epoch: 8 [7680/9756]	Loss: 0.6095	LR: 0.100000
Training Epoch: 8 [7936/9756]	Loss: 0.7046	LR: 0.100000
Training Epoch: 8 [8192/9756]	Loss: 0.6830	LR: 0.100000
Training Epoch: 8 [8448/9756]	Loss: 0.6576	LR: 0.100000
Training Epoch: 8 [8704/9756]	Loss: 0.6825	LR: 0.100000
Training Epoch: 8 [8960/9756]	Loss: 0.7067	LR: 0.100000
Training Epoch: 8 [9216/9756]	Loss: 0.6515	LR: 0.100000
Training Epoch: 8 [9472/9756]	Loss: 0.6810	LR: 0.100000
Training Epoch: 8 [9728/9756]	Loss: 0.6838	LR: 0.100000
Training Epoch: 8 [9756/9756]	Loss: 0.6354	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6733, Train Accuracy: 0.5982
Epoch 8 training time consumed: 140.36s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0030, Accuracy: 0.6034, Time consumed:8.06s
Training Epoch: 9 [256/9756]	Loss: 0.6493	LR: 0.100000
Training Epoch: 9 [512/9756]	Loss: 0.6597	LR: 0.100000
Training Epoch: 9 [768/9756]	Loss: 0.6612	LR: 0.100000
Training Epoch: 9 [1024/9756]	Loss: 0.7025	LR: 0.100000
Training Epoch: 9 [1280/9756]	Loss: 0.6873	LR: 0.100000
Training Epoch: 9 [1536/9756]	Loss: 0.6945	LR: 0.100000
Training Epoch: 9 [1792/9756]	Loss: 0.6423	LR: 0.100000
Training Epoch: 9 [2048/9756]	Loss: 0.6735	LR: 0.100000
Training Epoch: 9 [2304/9756]	Loss: 0.6761	LR: 0.100000
Training Epoch: 9 [2560/9756]	Loss: 0.6326	LR: 0.100000
Training Epoch: 9 [2816/9756]	Loss: 0.6399	LR: 0.100000
Training Epoch: 9 [3072/9756]	Loss: 0.6569	LR: 0.100000
Training Epoch: 9 [3328/9756]	Loss: 0.6874	LR: 0.100000
Training Epoch: 9 [3584/9756]	Loss: 0.6512	LR: 0.100000
Training Epoch: 9 [3840/9756]	Loss: 0.6739	LR: 0.100000
Training Epoch: 9 [4096/9756]	Loss: 0.7008	LR: 0.100000
Training Epoch: 9 [4352/9756]	Loss: 0.6739	LR: 0.100000
Training Epoch: 9 [4608/9756]	Loss: 0.6271	LR: 0.100000
Training Epoch: 9 [4864/9756]	Loss: 0.6745	LR: 0.100000
Training Epoch: 9 [5120/9756]	Loss: 0.6590	LR: 0.100000
Training Epoch: 9 [5376/9756]	Loss: 0.6501	LR: 0.100000
Training Epoch: 9 [5632/9756]	Loss: 0.6701	LR: 0.100000
Training Epoch: 9 [5888/9756]	Loss: 0.6783	LR: 0.100000
Training Epoch: 9 [6144/9756]	Loss: 0.6580	LR: 0.100000
Training Epoch: 9 [6400/9756]	Loss: 0.6436	LR: 0.100000
Training Epoch: 9 [6656/9756]	Loss: 0.6543	LR: 0.100000
Training Epoch: 9 [6912/9756]	Loss: 0.6541	LR: 0.100000
Training Epoch: 9 [7168/9756]	Loss: 0.6612	LR: 0.100000
Training Epoch: 9 [7424/9756]	Loss: 0.6931	LR: 0.100000
Training Epoch: 9 [7680/9756]	Loss: 0.6491	LR: 0.100000
Training Epoch: 9 [7936/9756]	Loss: 0.6327	LR: 0.100000
Training Epoch: 9 [8192/9756]	Loss: 0.6395	LR: 0.100000
Training Epoch: 9 [8448/9756]	Loss: 0.6535	LR: 0.100000
Training Epoch: 9 [8704/9756]	Loss: 0.6222	LR: 0.100000
Training Epoch: 9 [8960/9756]	Loss: 0.6132	LR: 0.100000
Training Epoch: 9 [9216/9756]	Loss: 0.6502	LR: 0.100000
Training Epoch: 9 [9472/9756]	Loss: 0.6628	LR: 0.100000
Training Epoch: 9 [9728/9756]	Loss: 0.6686	LR: 0.100000
Training Epoch: 9 [9756/9756]	Loss: 0.8618	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6605, Train Accuracy: 0.6163
Epoch 9 training time consumed: 140.27s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0042, Accuracy: 0.4780, Time consumed:8.07s
Training Epoch: 10 [256/9756]	Loss: 0.6988	LR: 0.020000
Training Epoch: 10 [512/9756]	Loss: 0.7110	LR: 0.020000
Training Epoch: 10 [768/9756]	Loss: 0.6842	LR: 0.020000
Training Epoch: 10 [1024/9756]	Loss: 0.6657	LR: 0.020000
Training Epoch: 10 [1280/9756]	Loss: 0.6630	LR: 0.020000
Training Epoch: 10 [1536/9756]	Loss: 0.6598	LR: 0.020000
Training Epoch: 10 [1792/9756]	Loss: 0.6681	LR: 0.020000
Training Epoch: 10 [2048/9756]	Loss: 0.6528	LR: 0.020000
Training Epoch: 10 [2304/9756]	Loss: 0.6702	LR: 0.020000
Training Epoch: 10 [2560/9756]	Loss: 0.6571	LR: 0.020000
Training Epoch: 10 [2816/9756]	Loss: 0.6736	LR: 0.020000
Training Epoch: 10 [3072/9756]	Loss: 0.6748	LR: 0.020000
Training Epoch: 10 [3328/9756]	Loss: 0.6650	LR: 0.020000
Training Epoch: 10 [3584/9756]	Loss: 0.6515	LR: 0.020000
Training Epoch: 10 [3840/9756]	Loss: 0.6566	LR: 0.020000
Training Epoch: 10 [4096/9756]	Loss: 0.6548	LR: 0.020000
Training Epoch: 10 [4352/9756]	Loss: 0.6472	LR: 0.020000
Training Epoch: 10 [4608/9756]	Loss: 0.6595	LR: 0.020000
Training Epoch: 10 [4864/9756]	Loss: 0.6614	LR: 0.020000
Training Epoch: 10 [5120/9756]	Loss: 0.6476	LR: 0.020000
Training Epoch: 10 [5376/9756]	Loss: 0.6439	LR: 0.020000
Training Epoch: 10 [5632/9756]	Loss: 0.6647	LR: 0.020000
Training Epoch: 10 [5888/9756]	Loss: 0.6674	LR: 0.020000
Training Epoch: 10 [6144/9756]	Loss: 0.6663	LR: 0.020000
Training Epoch: 10 [6400/9756]	Loss: 0.6563	LR: 0.020000
Training Epoch: 10 [6656/9756]	Loss: 0.6584	LR: 0.020000
Training Epoch: 10 [6912/9756]	Loss: 0.6407	LR: 0.020000
Training Epoch: 10 [7168/9756]	Loss: 0.6683	LR: 0.020000
Training Epoch: 10 [7424/9756]	Loss: 0.6739	LR: 0.020000
Training Epoch: 10 [7680/9756]	Loss: 0.6452	LR: 0.020000
Training Epoch: 10 [7936/9756]	Loss: 0.6058	LR: 0.020000
Training Epoch: 10 [8192/9756]	Loss: 0.6813	LR: 0.020000
Training Epoch: 10 [8448/9756]	Loss: 0.6564	LR: 0.020000
Training Epoch: 10 [8704/9756]	Loss: 0.6497	LR: 0.020000
Training Epoch: 10 [8960/9756]	Loss: 0.6693	LR: 0.020000
Training Epoch: 10 [9216/9756]	Loss: 0.6564	LR: 0.020000
Training Epoch: 10 [9472/9756]	Loss: 0.6619	LR: 0.020000
Training Epoch: 10 [9728/9756]	Loss: 0.6192	LR: 0.020000
Training Epoch: 10 [9756/9756]	Loss: 0.6056	LR: 0.020000
Epoch 10 - Average Train Loss: 0.6606, Train Accuracy: 0.6146
Epoch 10 training time consumed: 140.82s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0028, Accuracy: 0.6547, Time consumed:7.92s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-10-best.pth
Training Epoch: 11 [256/9756]	Loss: 0.6503	LR: 0.020000
Training Epoch: 11 [512/9756]	Loss: 0.6399	LR: 0.020000
Training Epoch: 11 [768/9756]	Loss: 0.6270	LR: 0.020000
Training Epoch: 11 [1024/9756]	Loss: 0.6415	LR: 0.020000
Training Epoch: 11 [1280/9756]	Loss: 0.6535	LR: 0.020000
Training Epoch: 11 [1536/9756]	Loss: 0.6431	LR: 0.020000
Training Epoch: 11 [1792/9756]	Loss: 0.6544	LR: 0.020000
Training Epoch: 11 [2048/9756]	Loss: 0.6440	LR: 0.020000
Training Epoch: 11 [2304/9756]	Loss: 0.6065	LR: 0.020000
Training Epoch: 11 [2560/9756]	Loss: 0.6219	LR: 0.020000
Training Epoch: 11 [2816/9756]	Loss: 0.6243	LR: 0.020000
Training Epoch: 11 [3072/9756]	Loss: 0.6797	LR: 0.020000
Training Epoch: 11 [3328/9756]	Loss: 0.6258	LR: 0.020000
Training Epoch: 11 [3584/9756]	Loss: 0.6415	LR: 0.020000
Training Epoch: 11 [3840/9756]	Loss: 0.6030	LR: 0.020000
Training Epoch: 11 [4096/9756]	Loss: 0.6367	LR: 0.020000
Training Epoch: 11 [4352/9756]	Loss: 0.6528	LR: 0.020000
Training Epoch: 11 [4608/9756]	Loss: 0.6199	LR: 0.020000
Training Epoch: 11 [4864/9756]	Loss: 0.6412	LR: 0.020000
Training Epoch: 11 [5120/9756]	Loss: 0.6262	LR: 0.020000
Training Epoch: 11 [5376/9756]	Loss: 0.6161	LR: 0.020000
Training Epoch: 11 [5632/9756]	Loss: 0.6292	LR: 0.020000
Training Epoch: 11 [5888/9756]	Loss: 0.6198	LR: 0.020000
Training Epoch: 11 [6144/9756]	Loss: 0.6735	LR: 0.020000
Training Epoch: 11 [6400/9756]	Loss: 0.6559	LR: 0.020000
Training Epoch: 11 [6656/9756]	Loss: 0.6373	LR: 0.020000
Training Epoch: 11 [6912/9756]	Loss: 0.6013	LR: 0.020000
Training Epoch: 11 [7168/9756]	Loss: 0.6199	LR: 0.020000
Training Epoch: 11 [7424/9756]	Loss: 0.6582	LR: 0.020000
Training Epoch: 11 [7680/9756]	Loss: 0.6130	LR: 0.020000
Training Epoch: 11 [7936/9756]	Loss: 0.6218	LR: 0.020000
Training Epoch: 11 [8192/9756]	Loss: 0.5589	LR: 0.020000
Training Epoch: 11 [8448/9756]	Loss: 0.5866	LR: 0.020000
Training Epoch: 11 [8704/9756]	Loss: 0.6128	LR: 0.020000
Training Epoch: 11 [8960/9756]	Loss: 0.6153	LR: 0.020000
Training Epoch: 11 [9216/9756]	Loss: 0.6397	LR: 0.020000
Training Epoch: 11 [9472/9756]	Loss: 0.6127	LR: 0.020000
Training Epoch: 11 [9728/9756]	Loss: 0.6235	LR: 0.020000
Training Epoch: 11 [9756/9756]	Loss: 0.6811	LR: 0.020000
Epoch 11 - Average Train Loss: 0.6298, Train Accuracy: 0.6482
Epoch 11 training time consumed: 140.58s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0027, Accuracy: 0.6726, Time consumed:7.85s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-11-best.pth
Training Epoch: 12 [256/9756]	Loss: 0.6119	LR: 0.020000
Training Epoch: 12 [512/9756]	Loss: 0.6083	LR: 0.020000
Training Epoch: 12 [768/9756]	Loss: 0.5756	LR: 0.020000
Training Epoch: 12 [1024/9756]	Loss: 0.6280	LR: 0.020000
Training Epoch: 12 [1280/9756]	Loss: 0.6010	LR: 0.020000
Training Epoch: 12 [1536/9756]	Loss: 0.6251	LR: 0.020000
Training Epoch: 12 [1792/9756]	Loss: 0.6175	LR: 0.020000
Training Epoch: 12 [2048/9756]	Loss: 0.6008	LR: 0.020000
Training Epoch: 12 [2304/9756]	Loss: 0.6259	LR: 0.020000
Training Epoch: 12 [2560/9756]	Loss: 0.6080	LR: 0.020000
Training Epoch: 12 [2816/9756]	Loss: 0.6047	LR: 0.020000
Training Epoch: 12 [3072/9756]	Loss: 0.5964	LR: 0.020000
Training Epoch: 12 [3328/9756]	Loss: 0.6317	LR: 0.020000
Training Epoch: 12 [3584/9756]	Loss: 0.6077	LR: 0.020000
Training Epoch: 12 [3840/9756]	Loss: 0.6227	LR: 0.020000
Training Epoch: 12 [4096/9756]	Loss: 0.5738	LR: 0.020000
Training Epoch: 12 [4352/9756]	Loss: 0.6535	LR: 0.020000
Training Epoch: 12 [4608/9756]	Loss: 0.6583	LR: 0.020000
Training Epoch: 12 [4864/9756]	Loss: 0.5992	LR: 0.020000
Training Epoch: 12 [5120/9756]	Loss: 0.6148	LR: 0.020000
Training Epoch: 12 [5376/9756]	Loss: 0.6426	LR: 0.020000
Training Epoch: 12 [5632/9756]	Loss: 0.6245	LR: 0.020000
Training Epoch: 12 [5888/9756]	Loss: 0.5873	LR: 0.020000
Training Epoch: 12 [6144/9756]	Loss: 0.5733	LR: 0.020000
Training Epoch: 12 [6400/9756]	Loss: 0.6132	LR: 0.020000
Training Epoch: 12 [6656/9756]	Loss: 0.5891	LR: 0.020000
Training Epoch: 12 [6912/9756]	Loss: 0.6241	LR: 0.020000
Training Epoch: 12 [7168/9756]	Loss: 0.6333	LR: 0.020000
Training Epoch: 12 [7424/9756]	Loss: 0.6317	LR: 0.020000
Training Epoch: 12 [7680/9756]	Loss: 0.6353	LR: 0.020000
Training Epoch: 12 [7936/9756]	Loss: 0.5957	LR: 0.020000
Training Epoch: 12 [8192/9756]	Loss: 0.6431	LR: 0.020000
Training Epoch: 12 [8448/9756]	Loss: 0.5909	LR: 0.020000
Training Epoch: 12 [8704/9756]	Loss: 0.6008	LR: 0.020000
Training Epoch: 12 [8960/9756]	Loss: 0.6311	LR: 0.020000
Training Epoch: 12 [9216/9756]	Loss: 0.5787	LR: 0.020000
Training Epoch: 12 [9472/9756]	Loss: 0.6501	LR: 0.020000
Training Epoch: 12 [9728/9756]	Loss: 0.6271	LR: 0.020000
Training Epoch: 12 [9756/9756]	Loss: 0.6356	LR: 0.020000
Epoch 12 - Average Train Loss: 0.6142, Train Accuracy: 0.6649
Epoch 12 training time consumed: 140.80s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0028, Accuracy: 0.6053, Time consumed:7.92s
Training Epoch: 13 [256/9756]	Loss: 0.6011	LR: 0.020000
Training Epoch: 13 [512/9756]	Loss: 0.6367	LR: 0.020000
Training Epoch: 13 [768/9756]	Loss: 0.6209	LR: 0.020000
Training Epoch: 13 [1024/9756]	Loss: 0.5922	LR: 0.020000
Training Epoch: 13 [1280/9756]	Loss: 0.5836	LR: 0.020000
Training Epoch: 13 [1536/9756]	Loss: 0.6221	LR: 0.020000
Training Epoch: 13 [1792/9756]	Loss: 0.5927	LR: 0.020000
Training Epoch: 13 [2048/9756]	Loss: 0.6217	LR: 0.020000
Training Epoch: 13 [2304/9756]	Loss: 0.5862	LR: 0.020000
Training Epoch: 13 [2560/9756]	Loss: 0.6234	LR: 0.020000
Training Epoch: 13 [2816/9756]	Loss: 0.6282	LR: 0.020000
Training Epoch: 13 [3072/9756]	Loss: 0.6178	LR: 0.020000
Training Epoch: 13 [3328/9756]	Loss: 0.6329	LR: 0.020000
Training Epoch: 13 [3584/9756]	Loss: 0.6253	LR: 0.020000
Training Epoch: 13 [3840/9756]	Loss: 0.5969	LR: 0.020000
Training Epoch: 13 [4096/9756]	Loss: 0.5657	LR: 0.020000
Training Epoch: 13 [4352/9756]	Loss: 0.6254	LR: 0.020000
Training Epoch: 13 [4608/9756]	Loss: 0.6120	LR: 0.020000
Training Epoch: 13 [4864/9756]	Loss: 0.5901	LR: 0.020000
Training Epoch: 13 [5120/9756]	Loss: 0.5836	LR: 0.020000
Training Epoch: 13 [5376/9756]	Loss: 0.5358	LR: 0.020000
Training Epoch: 13 [5632/9756]	Loss: 0.6039	LR: 0.020000
Training Epoch: 13 [5888/9756]	Loss: 0.5745	LR: 0.020000
Training Epoch: 13 [6144/9756]	Loss: 0.5871	LR: 0.020000
Training Epoch: 13 [6400/9756]	Loss: 0.5837	LR: 0.020000
Training Epoch: 13 [6656/9756]	Loss: 0.5922	LR: 0.020000
Training Epoch: 13 [6912/9756]	Loss: 0.6370	LR: 0.020000
Training Epoch: 13 [7168/9756]	Loss: 0.6109	LR: 0.020000
Training Epoch: 13 [7424/9756]	Loss: 0.6067	LR: 0.020000
Training Epoch: 13 [7680/9756]	Loss: 0.5742	LR: 0.020000
Training Epoch: 13 [7936/9756]	Loss: 0.5838	LR: 0.020000
Training Epoch: 13 [8192/9756]	Loss: 0.5503	LR: 0.020000
Training Epoch: 13 [8448/9756]	Loss: 0.6154	LR: 0.020000
Training Epoch: 13 [8704/9756]	Loss: 0.5365	LR: 0.020000
Training Epoch: 13 [8960/9756]	Loss: 0.5616	LR: 0.020000
Training Epoch: 13 [9216/9756]	Loss: 0.5963	LR: 0.020000
Training Epoch: 13 [9472/9756]	Loss: 0.6001	LR: 0.020000
Training Epoch: 13 [9728/9756]	Loss: 0.6103	LR: 0.020000
Training Epoch: 13 [9756/9756]	Loss: 0.4996	LR: 0.020000
Epoch 13 - Average Train Loss: 0.5976, Train Accuracy: 0.6810
Epoch 13 training time consumed: 140.37s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0026, Accuracy: 0.6804, Time consumed:8.02s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-13-best.pth
Training Epoch: 14 [256/9756]	Loss: 0.5506	LR: 0.020000
Training Epoch: 14 [512/9756]	Loss: 0.6051	LR: 0.020000
Training Epoch: 14 [768/9756]	Loss: 0.6134	LR: 0.020000
Training Epoch: 14 [1024/9756]	Loss: 0.6418	LR: 0.020000
Training Epoch: 14 [1280/9756]	Loss: 0.6237	LR: 0.020000
Training Epoch: 14 [1536/9756]	Loss: 0.6376	LR: 0.020000
Training Epoch: 14 [1792/9756]	Loss: 0.5826	LR: 0.020000
Training Epoch: 14 [2048/9756]	Loss: 0.5595	LR: 0.020000
Training Epoch: 14 [2304/9756]	Loss: 0.5945	LR: 0.020000
Training Epoch: 14 [2560/9756]	Loss: 0.5420	LR: 0.020000
Training Epoch: 14 [2816/9756]	Loss: 0.5984	LR: 0.020000
Training Epoch: 14 [3072/9756]	Loss: 0.6323	LR: 0.020000
Training Epoch: 14 [3328/9756]	Loss: 0.6407	LR: 0.020000
Training Epoch: 14 [3584/9756]	Loss: 0.5898	LR: 0.020000
Training Epoch: 14 [3840/9756]	Loss: 0.5960	LR: 0.020000
Training Epoch: 14 [4096/9756]	Loss: 0.6410	LR: 0.020000
Training Epoch: 14 [4352/9756]	Loss: 0.5884	LR: 0.020000
Training Epoch: 14 [4608/9756]	Loss: 0.5930	LR: 0.020000
Training Epoch: 14 [4864/9756]	Loss: 0.5700	LR: 0.020000
Training Epoch: 14 [5120/9756]	Loss: 0.6093	LR: 0.020000
Training Epoch: 14 [5376/9756]	Loss: 0.5647	LR: 0.020000
Training Epoch: 14 [5632/9756]	Loss: 0.5794	LR: 0.020000
Training Epoch: 14 [5888/9756]	Loss: 0.5804	LR: 0.020000
Training Epoch: 14 [6144/9756]	Loss: 0.6006	LR: 0.020000
Training Epoch: 14 [6400/9756]	Loss: 0.6342	LR: 0.020000
Training Epoch: 14 [6656/9756]	Loss: 0.5538	LR: 0.020000
Training Epoch: 14 [6912/9756]	Loss: 0.5661	LR: 0.020000
Training Epoch: 14 [7168/9756]	Loss: 0.5566	LR: 0.020000
Training Epoch: 14 [7424/9756]	Loss: 0.5718	LR: 0.020000
Training Epoch: 14 [7680/9756]	Loss: 0.5934	LR: 0.020000
Training Epoch: 14 [7936/9756]	Loss: 0.5824	LR: 0.020000
Training Epoch: 14 [8192/9756]	Loss: 0.5977	LR: 0.020000
Training Epoch: 14 [8448/9756]	Loss: 0.5660	LR: 0.020000
Training Epoch: 14 [8704/9756]	Loss: 0.5763	LR: 0.020000
Training Epoch: 14 [8960/9756]	Loss: 0.5584	LR: 0.020000
Training Epoch: 14 [9216/9756]	Loss: 0.5119	LR: 0.020000
Training Epoch: 14 [9472/9756]	Loss: 0.5662	LR: 0.020000
Training Epoch: 14 [9728/9756]	Loss: 0.5764	LR: 0.020000
Training Epoch: 14 [9756/9756]	Loss: 0.5449	LR: 0.020000
Epoch 14 - Average Train Loss: 0.5879, Train Accuracy: 0.6912
Epoch 14 training time consumed: 140.45s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0030, Accuracy: 0.6145, Time consumed:7.98s
Training Epoch: 15 [256/9756]	Loss: 0.5855	LR: 0.020000
Training Epoch: 15 [512/9756]	Loss: 0.5420	LR: 0.020000
Training Epoch: 15 [768/9756]	Loss: 0.5838	LR: 0.020000
Training Epoch: 15 [1024/9756]	Loss: 0.6467	LR: 0.020000
Training Epoch: 15 [1280/9756]	Loss: 0.6111	LR: 0.020000
Training Epoch: 15 [1536/9756]	Loss: 0.5804	LR: 0.020000
Training Epoch: 15 [1792/9756]	Loss: 0.5741	LR: 0.020000
Training Epoch: 15 [2048/9756]	Loss: 0.5291	LR: 0.020000
Training Epoch: 15 [2304/9756]	Loss: 0.5585	LR: 0.020000
Training Epoch: 15 [2560/9756]	Loss: 0.5742	LR: 0.020000
Training Epoch: 15 [2816/9756]	Loss: 0.5713	LR: 0.020000
Training Epoch: 15 [3072/9756]	Loss: 0.5498	LR: 0.020000
Training Epoch: 15 [3328/9756]	Loss: 0.5272	LR: 0.020000
Training Epoch: 15 [3584/9756]	Loss: 0.5617	LR: 0.020000
Training Epoch: 15 [3840/9756]	Loss: 0.5481	LR: 0.020000
Training Epoch: 15 [4096/9756]	Loss: 0.6253	LR: 0.020000
Training Epoch: 15 [4352/9756]	Loss: 0.5962	LR: 0.020000
Training Epoch: 15 [4608/9756]	Loss: 0.5751	LR: 0.020000
Training Epoch: 15 [4864/9756]	Loss: 0.6220	LR: 0.020000
Training Epoch: 15 [5120/9756]	Loss: 0.5700	LR: 0.020000
Training Epoch: 15 [5376/9756]	Loss: 0.5635	LR: 0.020000
Training Epoch: 15 [5632/9756]	Loss: 0.5302	LR: 0.020000
Training Epoch: 15 [5888/9756]	Loss: 0.5359	LR: 0.020000
Training Epoch: 15 [6144/9756]	Loss: 0.5431	LR: 0.020000
Training Epoch: 15 [6400/9756]	Loss: 0.5438	LR: 0.020000
Training Epoch: 15 [6656/9756]	Loss: 0.4909	LR: 0.020000
Training Epoch: 15 [6912/9756]	Loss: 0.5686	LR: 0.020000
Training Epoch: 15 [7168/9756]	Loss: 0.5134	LR: 0.020000
Training Epoch: 15 [7424/9756]	Loss: 0.5283	LR: 0.020000
Training Epoch: 15 [7680/9756]	Loss: 0.5174	LR: 0.020000
Training Epoch: 15 [7936/9756]	Loss: 0.4950	LR: 0.020000
Training Epoch: 15 [8192/9756]	Loss: 0.5093	LR: 0.020000
Training Epoch: 15 [8448/9756]	Loss: 0.5699	LR: 0.020000
Training Epoch: 15 [8704/9756]	Loss: 0.5151	LR: 0.020000
Training Epoch: 15 [8960/9756]	Loss: 0.4904	LR: 0.020000
Training Epoch: 15 [9216/9756]	Loss: 0.5327	LR: 0.020000
Training Epoch: 15 [9472/9756]	Loss: 0.5057	LR: 0.020000
Training Epoch: 15 [9728/9756]	Loss: 0.5032	LR: 0.020000
Training Epoch: 15 [9756/9756]	Loss: 0.6848	LR: 0.020000
Epoch 15 - Average Train Loss: 0.5527, Train Accuracy: 0.7226
Epoch 15 training time consumed: 140.72s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0025, Accuracy: 0.7274, Time consumed:8.03s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-15-best.pth
Training Epoch: 16 [256/9756]	Loss: 0.5540	LR: 0.020000
Training Epoch: 16 [512/9756]	Loss: 0.6206	LR: 0.020000
Training Epoch: 16 [768/9756]	Loss: 0.5399	LR: 0.020000
Training Epoch: 16 [1024/9756]	Loss: 0.5513	LR: 0.020000
Training Epoch: 16 [1280/9756]	Loss: 0.5324	LR: 0.020000
Training Epoch: 16 [1536/9756]	Loss: 0.5179	LR: 0.020000
Training Epoch: 16 [1792/9756]	Loss: 0.4763	LR: 0.020000
Training Epoch: 16 [2048/9756]	Loss: 0.5501	LR: 0.020000
Training Epoch: 16 [2304/9756]	Loss: 0.5253	LR: 0.020000
Training Epoch: 16 [2560/9756]	Loss: 0.5838	LR: 0.020000
Training Epoch: 16 [2816/9756]	Loss: 0.5292	LR: 0.020000
Training Epoch: 16 [3072/9756]	Loss: 0.5185	LR: 0.020000
Training Epoch: 16 [3328/9756]	Loss: 0.4656	LR: 0.020000
Training Epoch: 16 [3584/9756]	Loss: 0.4821	LR: 0.020000
Training Epoch: 16 [3840/9756]	Loss: 0.5352	LR: 0.020000
Training Epoch: 16 [4096/9756]	Loss: 0.5488	LR: 0.020000
Training Epoch: 16 [4352/9756]	Loss: 0.5084	LR: 0.020000
Training Epoch: 16 [4608/9756]	Loss: 0.4695	LR: 0.020000
Training Epoch: 16 [4864/9756]	Loss: 0.5433	LR: 0.020000
Training Epoch: 16 [5120/9756]	Loss: 0.5052	LR: 0.020000
Training Epoch: 16 [5376/9756]	Loss: 0.5824	LR: 0.020000
Training Epoch: 16 [5632/9756]	Loss: 0.5421	LR: 0.020000
Training Epoch: 16 [5888/9756]	Loss: 0.5212	LR: 0.020000
Training Epoch: 16 [6144/9756]	Loss: 0.5144	LR: 0.020000
Training Epoch: 16 [6400/9756]	Loss: 0.5593	LR: 0.020000
Training Epoch: 16 [6656/9756]	Loss: 0.5118	LR: 0.020000
Training Epoch: 16 [6912/9756]	Loss: 0.5261	LR: 0.020000
Training Epoch: 16 [7168/9756]	Loss: 0.4693	LR: 0.020000
Training Epoch: 16 [7424/9756]	Loss: 0.5044	LR: 0.020000
Training Epoch: 16 [7680/9756]	Loss: 0.4844	LR: 0.020000
Training Epoch: 16 [7936/9756]	Loss: 0.4559	LR: 0.020000
Training Epoch: 16 [8192/9756]	Loss: 0.4947	LR: 0.020000
Training Epoch: 16 [8448/9756]	Loss: 0.4515	LR: 0.020000
Training Epoch: 16 [8704/9756]	Loss: 0.4910	LR: 0.020000
Training Epoch: 16 [8960/9756]	Loss: 0.4778	LR: 0.020000
Training Epoch: 16 [9216/9756]	Loss: 0.5329	LR: 0.020000
Training Epoch: 16 [9472/9756]	Loss: 0.5062	LR: 0.020000
Training Epoch: 16 [9728/9756]	Loss: 0.4882	LR: 0.020000
Training Epoch: 16 [9756/9756]	Loss: 0.6314	LR: 0.020000
Epoch 16 - Average Train Loss: 0.5180, Train Accuracy: 0.7499
Epoch 16 training time consumed: 140.57s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0028, Accuracy: 0.6596, Time consumed:7.87s
Training Epoch: 17 [256/9756]	Loss: 0.5015	LR: 0.020000
Training Epoch: 17 [512/9756]	Loss: 0.6221	LR: 0.020000
Training Epoch: 17 [768/9756]	Loss: 0.5448	LR: 0.020000
Training Epoch: 17 [1024/9756]	Loss: 0.4957	LR: 0.020000
Training Epoch: 17 [1280/9756]	Loss: 0.5219	LR: 0.020000
Training Epoch: 17 [1536/9756]	Loss: 0.4946	LR: 0.020000
Training Epoch: 17 [1792/9756]	Loss: 0.4903	LR: 0.020000
Training Epoch: 17 [2048/9756]	Loss: 0.4891	LR: 0.020000
Training Epoch: 17 [2304/9756]	Loss: 0.4671	LR: 0.020000
Training Epoch: 17 [2560/9756]	Loss: 0.5559	LR: 0.020000
Training Epoch: 17 [2816/9756]	Loss: 0.4769	LR: 0.020000
Training Epoch: 17 [3072/9756]	Loss: 0.4769	LR: 0.020000
Training Epoch: 17 [3328/9756]	Loss: 0.4568	LR: 0.020000
Training Epoch: 17 [3584/9756]	Loss: 0.4715	LR: 0.020000
Training Epoch: 17 [3840/9756]	Loss: 0.4296	LR: 0.020000
Training Epoch: 17 [4096/9756]	Loss: 0.4749	LR: 0.020000
Training Epoch: 17 [4352/9756]	Loss: 0.4592	LR: 0.020000
Training Epoch: 17 [4608/9756]	Loss: 0.5497	LR: 0.020000
Training Epoch: 17 [4864/9756]	Loss: 0.4729	LR: 0.020000
Training Epoch: 17 [5120/9756]	Loss: 0.4378	LR: 0.020000
Training Epoch: 17 [5376/9756]	Loss: 0.4825	LR: 0.020000
Training Epoch: 17 [5632/9756]	Loss: 0.4460	LR: 0.020000
Training Epoch: 17 [5888/9756]	Loss: 0.5150	LR: 0.020000
Training Epoch: 17 [6144/9756]	Loss: 0.4811	LR: 0.020000
Training Epoch: 17 [6400/9756]	Loss: 0.4498	LR: 0.020000
Training Epoch: 17 [6656/9756]	Loss: 0.4579	LR: 0.020000
Training Epoch: 17 [6912/9756]	Loss: 0.4856	LR: 0.020000
Training Epoch: 17 [7168/9756]	Loss: 0.5026	LR: 0.020000
Training Epoch: 17 [7424/9756]	Loss: 0.4707	LR: 0.020000
Training Epoch: 17 [7680/9756]	Loss: 0.4536	LR: 0.020000
Training Epoch: 17 [7936/9756]	Loss: 0.4594	LR: 0.020000
Training Epoch: 17 [8192/9756]	Loss: 0.4498	LR: 0.020000
Training Epoch: 17 [8448/9756]	Loss: 0.4571	LR: 0.020000
Training Epoch: 17 [8704/9756]	Loss: 0.4600	LR: 0.020000
Training Epoch: 17 [8960/9756]	Loss: 0.4417	LR: 0.020000
Training Epoch: 17 [9216/9756]	Loss: 0.4710	LR: 0.020000
Training Epoch: 17 [9472/9756]	Loss: 0.4202	LR: 0.020000
Training Epoch: 17 [9728/9756]	Loss: 0.4886	LR: 0.020000
Training Epoch: 17 [9756/9756]	Loss: 0.5031	LR: 0.020000
Epoch 17 - Average Train Loss: 0.4812, Train Accuracy: 0.7720
Epoch 17 training time consumed: 140.46s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0023, Accuracy: 0.7564, Time consumed:7.87s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-17-best.pth
Training Epoch: 18 [256/9756]	Loss: 0.4177	LR: 0.020000
Training Epoch: 18 [512/9756]	Loss: 0.4363	LR: 0.020000
Training Epoch: 18 [768/9756]	Loss: 0.4446	LR: 0.020000
Training Epoch: 18 [1024/9756]	Loss: 0.4559	LR: 0.020000
Training Epoch: 18 [1280/9756]	Loss: 0.4063	LR: 0.020000
Training Epoch: 18 [1536/9756]	Loss: 0.4659	LR: 0.020000
Training Epoch: 18 [1792/9756]	Loss: 0.4620	LR: 0.020000
Training Epoch: 18 [2048/9756]	Loss: 0.5090	LR: 0.020000
Training Epoch: 18 [2304/9756]	Loss: 0.4617	LR: 0.020000
Training Epoch: 18 [2560/9756]	Loss: 0.4261	LR: 0.020000
Training Epoch: 18 [2816/9756]	Loss: 0.4160	LR: 0.020000
Training Epoch: 18 [3072/9756]	Loss: 0.4450	LR: 0.020000
Training Epoch: 18 [3328/9756]	Loss: 0.4204	LR: 0.020000
Training Epoch: 18 [3584/9756]	Loss: 0.3852	LR: 0.020000
Training Epoch: 18 [3840/9756]	Loss: 0.4666	LR: 0.020000
Training Epoch: 18 [4096/9756]	Loss: 0.4443	LR: 0.020000
Training Epoch: 18 [4352/9756]	Loss: 0.4099	LR: 0.020000
Training Epoch: 18 [4608/9756]	Loss: 0.4586	LR: 0.020000
Training Epoch: 18 [4864/9756]	Loss: 0.4174	LR: 0.020000
Training Epoch: 18 [5120/9756]	Loss: 0.3487	LR: 0.020000
Training Epoch: 18 [5376/9756]	Loss: 0.4000	LR: 0.020000
Training Epoch: 18 [5632/9756]	Loss: 0.4805	LR: 0.020000
Training Epoch: 18 [5888/9756]	Loss: 0.4635	LR: 0.020000
Training Epoch: 18 [6144/9756]	Loss: 0.4679	LR: 0.020000
Training Epoch: 18 [6400/9756]	Loss: 0.4932	LR: 0.020000
Training Epoch: 18 [6656/9756]	Loss: 0.4372	LR: 0.020000
Training Epoch: 18 [6912/9756]	Loss: 0.4618	LR: 0.020000
Training Epoch: 18 [7168/9756]	Loss: 0.4904	LR: 0.020000
Training Epoch: 18 [7424/9756]	Loss: 0.4215	LR: 0.020000
Training Epoch: 18 [7680/9756]	Loss: 0.4531	LR: 0.020000
Training Epoch: 18 [7936/9756]	Loss: 0.4105	LR: 0.020000
Training Epoch: 18 [8192/9756]	Loss: 0.4205	LR: 0.020000
Training Epoch: 18 [8448/9756]	Loss: 0.5446	LR: 0.020000
Training Epoch: 18 [8704/9756]	Loss: 0.4224	LR: 0.020000
Training Epoch: 18 [8960/9756]	Loss: 0.5081	LR: 0.020000
Training Epoch: 18 [9216/9756]	Loss: 0.3878	LR: 0.020000
Training Epoch: 18 [9472/9756]	Loss: 0.4469	LR: 0.020000
Training Epoch: 18 [9728/9756]	Loss: 0.4448	LR: 0.020000
Training Epoch: 18 [9756/9756]	Loss: 0.6071	LR: 0.020000
Epoch 18 - Average Train Loss: 0.4440, Train Accuracy: 0.7965
Epoch 18 training time consumed: 140.68s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0019, Accuracy: 0.8068, Time consumed:8.13s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-18-best.pth
Training Epoch: 19 [256/9756]	Loss: 0.4046	LR: 0.020000
Training Epoch: 19 [512/9756]	Loss: 0.4173	LR: 0.020000
Training Epoch: 19 [768/9756]	Loss: 0.4119	LR: 0.020000
Training Epoch: 19 [1024/9756]	Loss: 0.4416	LR: 0.020000
Training Epoch: 19 [1280/9756]	Loss: 0.4717	LR: 0.020000
Training Epoch: 19 [1536/9756]	Loss: 0.4324	LR: 0.020000
Training Epoch: 19 [1792/9756]	Loss: 0.4630	LR: 0.020000
Training Epoch: 19 [2048/9756]	Loss: 0.4586	LR: 0.020000
Training Epoch: 19 [2304/9756]	Loss: 0.4119	LR: 0.020000
Training Epoch: 19 [2560/9756]	Loss: 0.4641	LR: 0.020000
Training Epoch: 19 [2816/9756]	Loss: 0.4405	LR: 0.020000
Training Epoch: 19 [3072/9756]	Loss: 0.4166	LR: 0.020000
Training Epoch: 19 [3328/9756]	Loss: 0.4007	LR: 0.020000
Training Epoch: 19 [3584/9756]	Loss: 0.3971	LR: 0.020000
Training Epoch: 19 [3840/9756]	Loss: 0.3917	LR: 0.020000
Training Epoch: 19 [4096/9756]	Loss: 0.3897	LR: 0.020000
Training Epoch: 19 [4352/9756]	Loss: 0.4170	LR: 0.020000
Training Epoch: 19 [4608/9756]	Loss: 0.3893	LR: 0.020000
Training Epoch: 19 [4864/9756]	Loss: 0.4399	LR: 0.020000
Training Epoch: 19 [5120/9756]	Loss: 0.3821	LR: 0.020000
Training Epoch: 19 [5376/9756]	Loss: 0.3289	LR: 0.020000
Training Epoch: 19 [5632/9756]	Loss: 0.3649	LR: 0.020000
Training Epoch: 19 [5888/9756]	Loss: 0.4227	LR: 0.020000
Training Epoch: 19 [6144/9756]	Loss: 0.3409	LR: 0.020000
Training Epoch: 19 [6400/9756]	Loss: 0.4411	LR: 0.020000
Training Epoch: 19 [6656/9756]	Loss: 0.3420	LR: 0.020000
Training Epoch: 19 [6912/9756]	Loss: 0.3455	LR: 0.020000
Training Epoch: 19 [7168/9756]	Loss: 0.3312	LR: 0.020000
Training Epoch: 19 [7424/9756]	Loss: 0.3985	LR: 0.020000
Training Epoch: 19 [7680/9756]	Loss: 0.4412	LR: 0.020000
Training Epoch: 19 [7936/9756]	Loss: 0.4415	LR: 0.020000
Training Epoch: 19 [8192/9756]	Loss: 0.4325	LR: 0.020000
Training Epoch: 19 [8448/9756]	Loss: 0.3944	LR: 0.020000
Training Epoch: 19 [8704/9756]	Loss: 0.4014	LR: 0.020000
Training Epoch: 19 [8960/9756]	Loss: 0.4192	LR: 0.020000
Training Epoch: 19 [9216/9756]	Loss: 0.3965	LR: 0.020000
Training Epoch: 19 [9472/9756]	Loss: 0.4306	LR: 0.020000
Training Epoch: 19 [9728/9756]	Loss: 0.4088	LR: 0.020000
Training Epoch: 19 [9756/9756]	Loss: 0.4323	LR: 0.020000
Epoch 19 - Average Train Loss: 0.4086, Train Accuracy: 0.8181
Epoch 19 training time consumed: 140.60s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0017, Accuracy: 0.8358, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-19-best.pth
Training Epoch: 20 [256/9756]	Loss: 0.3918	LR: 0.004000
Training Epoch: 20 [512/9756]	Loss: 0.4649	LR: 0.004000
Training Epoch: 20 [768/9756]	Loss: 0.4671	LR: 0.004000
Training Epoch: 20 [1024/9756]	Loss: 0.3805	LR: 0.004000
Training Epoch: 20 [1280/9756]	Loss: 0.4664	LR: 0.004000
Training Epoch: 20 [1536/9756]	Loss: 0.3339	LR: 0.004000
Training Epoch: 20 [1792/9756]	Loss: 0.3999	LR: 0.004000
Training Epoch: 20 [2048/9756]	Loss: 0.4120	LR: 0.004000
Training Epoch: 20 [2304/9756]	Loss: 0.4063	LR: 0.004000
Training Epoch: 20 [2560/9756]	Loss: 0.3586	LR: 0.004000
Training Epoch: 20 [2816/9756]	Loss: 0.3914	LR: 0.004000
Training Epoch: 20 [3072/9756]	Loss: 0.4072	LR: 0.004000
Training Epoch: 20 [3328/9756]	Loss: 0.3523	LR: 0.004000
Training Epoch: 20 [3584/9756]	Loss: 0.3278	LR: 0.004000
Training Epoch: 20 [3840/9756]	Loss: 0.3921	LR: 0.004000
Training Epoch: 20 [4096/9756]	Loss: 0.3728	LR: 0.004000
Training Epoch: 20 [4352/9756]	Loss: 0.3759	LR: 0.004000
Training Epoch: 20 [4608/9756]	Loss: 0.3319	LR: 0.004000
Training Epoch: 20 [4864/9756]	Loss: 0.3020	LR: 0.004000
Training Epoch: 20 [5120/9756]	Loss: 0.3900	LR: 0.004000
Training Epoch: 20 [5376/9756]	Loss: 0.3658	LR: 0.004000
Training Epoch: 20 [5632/9756]	Loss: 0.3849	LR: 0.004000
Training Epoch: 20 [5888/9756]	Loss: 0.4363	LR: 0.004000
Training Epoch: 20 [6144/9756]	Loss: 0.3035	LR: 0.004000
Training Epoch: 20 [6400/9756]	Loss: 0.3768	LR: 0.004000
Training Epoch: 20 [6656/9756]	Loss: 0.3411	LR: 0.004000
Training Epoch: 20 [6912/9756]	Loss: 0.3425	LR: 0.004000
Training Epoch: 20 [7168/9756]	Loss: 0.3332	LR: 0.004000
Training Epoch: 20 [7424/9756]	Loss: 0.3670	LR: 0.004000
Training Epoch: 20 [7680/9756]	Loss: 0.3913	LR: 0.004000
Training Epoch: 20 [7936/9756]	Loss: 0.3693	LR: 0.004000
Training Epoch: 20 [8192/9756]	Loss: 0.4188	LR: 0.004000
Training Epoch: 20 [8448/9756]	Loss: 0.3608	LR: 0.004000
Training Epoch: 20 [8704/9756]	Loss: 0.3629	LR: 0.004000
Training Epoch: 20 [8960/9756]	Loss: 0.2689	LR: 0.004000
Training Epoch: 20 [9216/9756]	Loss: 0.3660	LR: 0.004000
Training Epoch: 20 [9472/9756]	Loss: 0.3516	LR: 0.004000
Training Epoch: 20 [9728/9756]	Loss: 0.4278	LR: 0.004000
Training Epoch: 20 [9756/9756]	Loss: 0.4699	LR: 0.004000
Epoch 20 - Average Train Loss: 0.3764, Train Accuracy: 0.8354
Epoch 20 training time consumed: 141.13s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0014, Accuracy: 0.8760, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-20-best.pth
Training Epoch: 21 [256/9756]	Loss: 0.3824	LR: 0.004000
Training Epoch: 21 [512/9756]	Loss: 0.3287	LR: 0.004000
Training Epoch: 21 [768/9756]	Loss: 0.3492	LR: 0.004000
Training Epoch: 21 [1024/9756]	Loss: 0.3762	LR: 0.004000
Training Epoch: 21 [1280/9756]	Loss: 0.3417	LR: 0.004000
Training Epoch: 21 [1536/9756]	Loss: 0.3085	LR: 0.004000
Training Epoch: 21 [1792/9756]	Loss: 0.3817	LR: 0.004000
Training Epoch: 21 [2048/9756]	Loss: 0.3420	LR: 0.004000
Training Epoch: 21 [2304/9756]	Loss: 0.3443	LR: 0.004000
Training Epoch: 21 [2560/9756]	Loss: 0.3741	LR: 0.004000
Training Epoch: 21 [2816/9756]	Loss: 0.3798	LR: 0.004000
Training Epoch: 21 [3072/9756]	Loss: 0.3187	LR: 0.004000
Training Epoch: 21 [3328/9756]	Loss: 0.3640	LR: 0.004000
Training Epoch: 21 [3584/9756]	Loss: 0.3486	LR: 0.004000
Training Epoch: 21 [3840/9756]	Loss: 0.3488	LR: 0.004000
Training Epoch: 21 [4096/9756]	Loss: 0.3487	LR: 0.004000
Training Epoch: 21 [4352/9756]	Loss: 0.3434	LR: 0.004000
Training Epoch: 21 [4608/9756]	Loss: 0.3592	LR: 0.004000
Training Epoch: 21 [4864/9756]	Loss: 0.3386	LR: 0.004000
Training Epoch: 21 [5120/9756]	Loss: 0.3312	LR: 0.004000
Training Epoch: 21 [5376/9756]	Loss: 0.3033	LR: 0.004000
Training Epoch: 21 [5632/9756]	Loss: 0.3641	LR: 0.004000
Training Epoch: 21 [5888/9756]	Loss: 0.3890	LR: 0.004000
Training Epoch: 21 [6144/9756]	Loss: 0.3299	LR: 0.004000
Training Epoch: 21 [6400/9756]	Loss: 0.3933	LR: 0.004000
Training Epoch: 21 [6656/9756]	Loss: 0.3586	LR: 0.004000
Training Epoch: 21 [6912/9756]	Loss: 0.3144	LR: 0.004000
Training Epoch: 21 [7168/9756]	Loss: 0.3588	LR: 0.004000
Training Epoch: 21 [7424/9756]	Loss: 0.4515	LR: 0.004000
Training Epoch: 21 [7680/9756]	Loss: 0.3603	LR: 0.004000
Training Epoch: 21 [7936/9756]	Loss: 0.3381	LR: 0.004000
Training Epoch: 21 [8192/9756]	Loss: 0.4307	LR: 0.004000
Training Epoch: 21 [8448/9756]	Loss: 0.3819	LR: 0.004000
Training Epoch: 21 [8704/9756]	Loss: 0.2956	LR: 0.004000
Training Epoch: 21 [8960/9756]	Loss: 0.3354	LR: 0.004000
Training Epoch: 21 [9216/9756]	Loss: 0.3734	LR: 0.004000
Training Epoch: 21 [9472/9756]	Loss: 0.3004	LR: 0.004000
Training Epoch: 21 [9728/9756]	Loss: 0.4007	LR: 0.004000
Training Epoch: 21 [9756/9756]	Loss: 0.4690	LR: 0.004000
Epoch 21 - Average Train Loss: 0.3553, Train Accuracy: 0.8424
Epoch 21 training time consumed: 140.43s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0014, Accuracy: 0.8630, Time consumed:8.03s
Training Epoch: 22 [256/9756]	Loss: 0.2879	LR: 0.004000
Training Epoch: 22 [512/9756]	Loss: 0.3829	LR: 0.004000
Training Epoch: 22 [768/9756]	Loss: 0.3402	LR: 0.004000
Training Epoch: 22 [1024/9756]	Loss: 0.3782	LR: 0.004000
Training Epoch: 22 [1280/9756]	Loss: 0.3368	LR: 0.004000
Training Epoch: 22 [1536/9756]	Loss: 0.3403	LR: 0.004000
Training Epoch: 22 [1792/9756]	Loss: 0.3180	LR: 0.004000
Training Epoch: 22 [2048/9756]	Loss: 0.3872	LR: 0.004000
Training Epoch: 22 [2304/9756]	Loss: 0.2991	LR: 0.004000
Training Epoch: 22 [2560/9756]	Loss: 0.2970	LR: 0.004000
Training Epoch: 22 [2816/9756]	Loss: 0.3325	LR: 0.004000
Training Epoch: 22 [3072/9756]	Loss: 0.3328	LR: 0.004000
Training Epoch: 22 [3328/9756]	Loss: 0.3324	LR: 0.004000
Training Epoch: 22 [3584/9756]	Loss: 0.3421	LR: 0.004000
Training Epoch: 22 [3840/9756]	Loss: 0.3339	LR: 0.004000
Training Epoch: 22 [4096/9756]	Loss: 0.3109	LR: 0.004000
Training Epoch: 22 [4352/9756]	Loss: 0.3964	LR: 0.004000
Training Epoch: 22 [4608/9756]	Loss: 0.3340	LR: 0.004000
Training Epoch: 22 [4864/9756]	Loss: 0.3249	LR: 0.004000
Training Epoch: 22 [5120/9756]	Loss: 0.3096	LR: 0.004000
Training Epoch: 22 [5376/9756]	Loss: 0.3262	LR: 0.004000
Training Epoch: 22 [5632/9756]	Loss: 0.2935	LR: 0.004000
Training Epoch: 22 [5888/9756]	Loss: 0.3092	LR: 0.004000
Training Epoch: 22 [6144/9756]	Loss: 0.3719	LR: 0.004000
Training Epoch: 22 [6400/9756]	Loss: 0.3162	LR: 0.004000
Training Epoch: 22 [6656/9756]	Loss: 0.3530	LR: 0.004000
Training Epoch: 22 [6912/9756]	Loss: 0.3392	LR: 0.004000
Training Epoch: 22 [7168/9756]	Loss: 0.3115	LR: 0.004000
Training Epoch: 22 [7424/9756]	Loss: 0.3517	LR: 0.004000
Training Epoch: 22 [7680/9756]	Loss: 0.3085	LR: 0.004000
Training Epoch: 22 [7936/9756]	Loss: 0.3139	LR: 0.004000
Training Epoch: 22 [8192/9756]	Loss: 0.3368	LR: 0.004000
Training Epoch: 22 [8448/9756]	Loss: 0.3626	LR: 0.004000
Training Epoch: 22 [8704/9756]	Loss: 0.3081	LR: 0.004000
Training Epoch: 22 [8960/9756]	Loss: 0.3187	LR: 0.004000
Training Epoch: 22 [9216/9756]	Loss: 0.3301	LR: 0.004000
Training Epoch: 22 [9472/9756]	Loss: 0.3223	LR: 0.004000
Training Epoch: 22 [9728/9756]	Loss: 0.3269	LR: 0.004000
Training Epoch: 22 [9756/9756]	Loss: 0.2136	LR: 0.004000
Epoch 22 - Average Train Loss: 0.3317, Train Accuracy: 0.8575
Epoch 22 training time consumed: 140.63s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0013, Accuracy: 0.8804, Time consumed:7.97s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-22-best.pth
Training Epoch: 23 [256/9756]	Loss: 0.2719	LR: 0.004000
Training Epoch: 23 [512/9756]	Loss: 0.3127	LR: 0.004000
Training Epoch: 23 [768/9756]	Loss: 0.3342	LR: 0.004000
Training Epoch: 23 [1024/9756]	Loss: 0.3248	LR: 0.004000
Training Epoch: 23 [1280/9756]	Loss: 0.3144	LR: 0.004000
Training Epoch: 23 [1536/9756]	Loss: 0.3202	LR: 0.004000
Training Epoch: 23 [1792/9756]	Loss: 0.3918	LR: 0.004000
Training Epoch: 23 [2048/9756]	Loss: 0.2631	LR: 0.004000
Training Epoch: 23 [2304/9756]	Loss: 0.3189	LR: 0.004000
Training Epoch: 23 [2560/9756]	Loss: 0.3473	LR: 0.004000
Training Epoch: 23 [2816/9756]	Loss: 0.3197	LR: 0.004000
Training Epoch: 23 [3072/9756]	Loss: 0.2664	LR: 0.004000
Training Epoch: 23 [3328/9756]	Loss: 0.2759	LR: 0.004000
Training Epoch: 23 [3584/9756]	Loss: 0.3235	LR: 0.004000
Training Epoch: 23 [3840/9756]	Loss: 0.3243	LR: 0.004000
Training Epoch: 23 [4096/9756]	Loss: 0.3874	LR: 0.004000
Training Epoch: 23 [4352/9756]	Loss: 0.3275	LR: 0.004000
Training Epoch: 23 [4608/9756]	Loss: 0.3302	LR: 0.004000
Training Epoch: 23 [4864/9756]	Loss: 0.4024	LR: 0.004000
Training Epoch: 23 [5120/9756]	Loss: 0.3033	LR: 0.004000
Training Epoch: 23 [5376/9756]	Loss: 0.3478	LR: 0.004000
Training Epoch: 23 [5632/9756]	Loss: 0.2671	LR: 0.004000
Training Epoch: 23 [5888/9756]	Loss: 0.3029	LR: 0.004000
Training Epoch: 23 [6144/9756]	Loss: 0.3258	LR: 0.004000
Training Epoch: 23 [6400/9756]	Loss: 0.3369	LR: 0.004000
Training Epoch: 23 [6656/9756]	Loss: 0.3216	LR: 0.004000
Training Epoch: 23 [6912/9756]	Loss: 0.2716	LR: 0.004000
Training Epoch: 23 [7168/9756]	Loss: 0.2998	LR: 0.004000
Training Epoch: 23 [7424/9756]	Loss: 0.3403	LR: 0.004000
Training Epoch: 23 [7680/9756]	Loss: 0.3494	LR: 0.004000
Training Epoch: 23 [7936/9756]	Loss: 0.3156	LR: 0.004000
Training Epoch: 23 [8192/9756]	Loss: 0.2864	LR: 0.004000
Training Epoch: 23 [8448/9756]	Loss: 0.2520	LR: 0.004000
Training Epoch: 23 [8704/9756]	Loss: 0.3154	LR: 0.004000
Training Epoch: 23 [8960/9756]	Loss: 0.2835	LR: 0.004000
Training Epoch: 23 [9216/9756]	Loss: 0.3473	LR: 0.004000
Training Epoch: 23 [9472/9756]	Loss: 0.3488	LR: 0.004000
Training Epoch: 23 [9728/9756]	Loss: 0.2927	LR: 0.004000
Training Epoch: 23 [9756/9756]	Loss: 0.2778	LR: 0.004000
Epoch 23 - Average Train Loss: 0.3174, Train Accuracy: 0.8648
Epoch 23 training time consumed: 141.49s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0018, Accuracy: 0.8266, Time consumed:8.32s
Training Epoch: 24 [256/9756]	Loss: 0.2602	LR: 0.004000
Training Epoch: 24 [512/9756]	Loss: 0.3740	LR: 0.004000
Training Epoch: 24 [768/9756]	Loss: 0.3654	LR: 0.004000
Training Epoch: 24 [1024/9756]	Loss: 0.3105	LR: 0.004000
Training Epoch: 24 [1280/9756]	Loss: 0.3625	LR: 0.004000
Training Epoch: 24 [1536/9756]	Loss: 0.2719	LR: 0.004000
Training Epoch: 24 [1792/9756]	Loss: 0.3291	LR: 0.004000
Training Epoch: 24 [2048/9756]	Loss: 0.2592	LR: 0.004000
Training Epoch: 24 [2304/9756]	Loss: 0.3399	LR: 0.004000
Training Epoch: 24 [2560/9756]	Loss: 0.3213	LR: 0.004000
Training Epoch: 24 [2816/9756]	Loss: 0.3085	LR: 0.004000
Training Epoch: 24 [3072/9756]	Loss: 0.2694	LR: 0.004000
Training Epoch: 24 [3328/9756]	Loss: 0.2780	LR: 0.004000
Training Epoch: 24 [3584/9756]	Loss: 0.3467	LR: 0.004000
Training Epoch: 24 [3840/9756]	Loss: 0.3385	LR: 0.004000
Training Epoch: 24 [4096/9756]	Loss: 0.3466	LR: 0.004000
Training Epoch: 24 [4352/9756]	Loss: 0.3055	LR: 0.004000
Training Epoch: 24 [4608/9756]	Loss: 0.3350	LR: 0.004000
Training Epoch: 24 [4864/9756]	Loss: 0.3352	LR: 0.004000
Training Epoch: 24 [5120/9756]	Loss: 0.2994	LR: 0.004000
Training Epoch: 24 [5376/9756]	Loss: 0.3375	LR: 0.004000
Training Epoch: 24 [5632/9756]	Loss: 0.3030	LR: 0.004000
Training Epoch: 24 [5888/9756]	Loss: 0.3290	LR: 0.004000
Training Epoch: 24 [6144/9756]	Loss: 0.2741	LR: 0.004000
Training Epoch: 24 [6400/9756]	Loss: 0.3008	LR: 0.004000
Training Epoch: 24 [6656/9756]	Loss: 0.2938	LR: 0.004000
Training Epoch: 24 [6912/9756]	Loss: 0.2736	LR: 0.004000
Training Epoch: 24 [7168/9756]	Loss: 0.2967	LR: 0.004000
Training Epoch: 24 [7424/9756]	Loss: 0.2932	LR: 0.004000
Training Epoch: 24 [7680/9756]	Loss: 0.2912	LR: 0.004000
Training Epoch: 24 [7936/9756]	Loss: 0.3341	LR: 0.004000
Training Epoch: 24 [8192/9756]	Loss: 0.2690	LR: 0.004000
Training Epoch: 24 [8448/9756]	Loss: 0.3403	LR: 0.004000
Training Epoch: 24 [8704/9756]	Loss: 0.3606	LR: 0.004000
Training Epoch: 24 [8960/9756]	Loss: 0.3096	LR: 0.004000
Training Epoch: 24 [9216/9756]	Loss: 0.2646	LR: 0.004000
Training Epoch: 24 [9472/9756]	Loss: 0.3018	LR: 0.004000
Training Epoch: 24 [9728/9756]	Loss: 0.3124	LR: 0.004000
Training Epoch: 24 [9756/9756]	Loss: 0.4215	LR: 0.004000
Epoch 24 - Average Train Loss: 0.3120, Train Accuracy: 0.8674
Epoch 24 training time consumed: 140.49s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0016, Accuracy: 0.8368, Time consumed:8.08s
Training Epoch: 25 [256/9756]	Loss: 0.2691	LR: 0.004000
Training Epoch: 25 [512/9756]	Loss: 0.3538	LR: 0.004000
Training Epoch: 25 [768/9756]	Loss: 0.3148	LR: 0.004000
Training Epoch: 25 [1024/9756]	Loss: 0.3628	LR: 0.004000
Training Epoch: 25 [1280/9756]	Loss: 0.3104	LR: 0.004000
Training Epoch: 25 [1536/9756]	Loss: 0.3101	LR: 0.004000
Training Epoch: 25 [1792/9756]	Loss: 0.3458	LR: 0.004000
Training Epoch: 25 [2048/9756]	Loss: 0.3023	LR: 0.004000
Training Epoch: 25 [2304/9756]	Loss: 0.3653	LR: 0.004000
Training Epoch: 25 [2560/9756]	Loss: 0.3229	LR: 0.004000
Training Epoch: 25 [2816/9756]	Loss: 0.2898	LR: 0.004000
Training Epoch: 25 [3072/9756]	Loss: 0.2686	LR: 0.004000
Training Epoch: 25 [3328/9756]	Loss: 0.2749	LR: 0.004000
Training Epoch: 25 [3584/9756]	Loss: 0.3392	LR: 0.004000
Training Epoch: 25 [3840/9756]	Loss: 0.2863	LR: 0.004000
Training Epoch: 25 [4096/9756]	Loss: 0.3125	LR: 0.004000
Training Epoch: 25 [4352/9756]	Loss: 0.3064	LR: 0.004000
Training Epoch: 25 [4608/9756]	Loss: 0.3083	LR: 0.004000
Training Epoch: 25 [4864/9756]	Loss: 0.3185	LR: 0.004000
Training Epoch: 25 [5120/9756]	Loss: 0.3168	LR: 0.004000
Training Epoch: 25 [5376/9756]	Loss: 0.3070	LR: 0.004000
Training Epoch: 25 [5632/9756]	Loss: 0.3614	LR: 0.004000
Training Epoch: 25 [5888/9756]	Loss: 0.3202	LR: 0.004000
Training Epoch: 25 [6144/9756]	Loss: 0.3660	LR: 0.004000
Training Epoch: 25 [6400/9756]	Loss: 0.3155	LR: 0.004000
Training Epoch: 25 [6656/9756]	Loss: 0.2825	LR: 0.004000
Training Epoch: 25 [6912/9756]	Loss: 0.2886	LR: 0.004000
Training Epoch: 25 [7168/9756]	Loss: 0.3098	LR: 0.004000
Training Epoch: 25 [7424/9756]	Loss: 0.3041	LR: 0.004000
Training Epoch: 25 [7680/9756]	Loss: 0.2743	LR: 0.004000
Training Epoch: 25 [7936/9756]	Loss: 0.2931	LR: 0.004000
Training Epoch: 25 [8192/9756]	Loss: 0.2560	LR: 0.004000
Training Epoch: 25 [8448/9756]	Loss: 0.2603	LR: 0.004000
Training Epoch: 25 [8704/9756]	Loss: 0.2641	LR: 0.004000
Training Epoch: 25 [8960/9756]	Loss: 0.3120	LR: 0.004000
Training Epoch: 25 [9216/9756]	Loss: 0.3468	LR: 0.004000
Training Epoch: 25 [9472/9756]	Loss: 0.2311	LR: 0.004000
Training Epoch: 25 [9728/9756]	Loss: 0.2742	LR: 0.004000
Training Epoch: 25 [9756/9756]	Loss: 0.1311	LR: 0.004000
Epoch 25 - Average Train Loss: 0.3060, Train Accuracy: 0.8720
Epoch 25 training time consumed: 140.57s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0012, Accuracy: 0.8843, Time consumed:7.96s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-25-best.pth
Training Epoch: 26 [256/9756]	Loss: 0.2993	LR: 0.004000
Training Epoch: 26 [512/9756]	Loss: 0.2642	LR: 0.004000
Training Epoch: 26 [768/9756]	Loss: 0.4010	LR: 0.004000
Training Epoch: 26 [1024/9756]	Loss: 0.3018	LR: 0.004000
Training Epoch: 26 [1280/9756]	Loss: 0.2596	LR: 0.004000
Training Epoch: 26 [1536/9756]	Loss: 0.2672	LR: 0.004000
Training Epoch: 26 [1792/9756]	Loss: 0.3635	LR: 0.004000
Training Epoch: 26 [2048/9756]	Loss: 0.3364	LR: 0.004000
Training Epoch: 26 [2304/9756]	Loss: 0.3446	LR: 0.004000
Training Epoch: 26 [2560/9756]	Loss: 0.2683	LR: 0.004000
Training Epoch: 26 [2816/9756]	Loss: 0.3483	LR: 0.004000
Training Epoch: 26 [3072/9756]	Loss: 0.2807	LR: 0.004000
Training Epoch: 26 [3328/9756]	Loss: 0.2710	LR: 0.004000
Training Epoch: 26 [3584/9756]	Loss: 0.2534	LR: 0.004000
Training Epoch: 26 [3840/9756]	Loss: 0.2246	LR: 0.004000
Training Epoch: 26 [4096/9756]	Loss: 0.2937	LR: 0.004000
Training Epoch: 26 [4352/9756]	Loss: 0.3329	LR: 0.004000
Training Epoch: 26 [4608/9756]	Loss: 0.3007	LR: 0.004000
Training Epoch: 26 [4864/9756]	Loss: 0.3040	LR: 0.004000
Training Epoch: 26 [5120/9756]	Loss: 0.3084	LR: 0.004000
Training Epoch: 26 [5376/9756]	Loss: 0.3006	LR: 0.004000
Training Epoch: 26 [5632/9756]	Loss: 0.2948	LR: 0.004000
Training Epoch: 26 [5888/9756]	Loss: 0.2922	LR: 0.004000
Training Epoch: 26 [6144/9756]	Loss: 0.3101	LR: 0.004000
Training Epoch: 26 [6400/9756]	Loss: 0.3216	LR: 0.004000
Training Epoch: 26 [6656/9756]	Loss: 0.3104	LR: 0.004000
Training Epoch: 26 [6912/9756]	Loss: 0.2556	LR: 0.004000
Training Epoch: 26 [7168/9756]	Loss: 0.3540	LR: 0.004000
Training Epoch: 26 [7424/9756]	Loss: 0.2744	LR: 0.004000
Training Epoch: 26 [7680/9756]	Loss: 0.2736	LR: 0.004000
Training Epoch: 26 [7936/9756]	Loss: 0.2982	LR: 0.004000
Training Epoch: 26 [8192/9756]	Loss: 0.2941	LR: 0.004000
Training Epoch: 26 [8448/9756]	Loss: 0.2405	LR: 0.004000
Training Epoch: 26 [8704/9756]	Loss: 0.3311	LR: 0.004000
Training Epoch: 26 [8960/9756]	Loss: 0.2836	LR: 0.004000
Training Epoch: 26 [9216/9756]	Loss: 0.2861	LR: 0.004000
Training Epoch: 26 [9472/9756]	Loss: 0.2504	LR: 0.004000
Training Epoch: 26 [9728/9756]	Loss: 0.2749	LR: 0.004000
Training Epoch: 26 [9756/9756]	Loss: 0.3630	LR: 0.004000
Epoch 26 - Average Train Loss: 0.2968, Train Accuracy: 0.8714
Epoch 26 training time consumed: 140.87s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0012, Accuracy: 0.8867, Time consumed:7.89s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-26-best.pth
Training Epoch: 27 [256/9756]	Loss: 0.2911	LR: 0.004000
Training Epoch: 27 [512/9756]	Loss: 0.2938	LR: 0.004000
Training Epoch: 27 [768/9756]	Loss: 0.2090	LR: 0.004000
Training Epoch: 27 [1024/9756]	Loss: 0.2995	LR: 0.004000
Training Epoch: 27 [1280/9756]	Loss: 0.3570	LR: 0.004000
Training Epoch: 27 [1536/9756]	Loss: 0.3335	LR: 0.004000
Training Epoch: 27 [1792/9756]	Loss: 0.3843	LR: 0.004000
Training Epoch: 27 [2048/9756]	Loss: 0.3304	LR: 0.004000
Training Epoch: 27 [2304/9756]	Loss: 0.2868	LR: 0.004000
Training Epoch: 27 [2560/9756]	Loss: 0.2914	LR: 0.004000
Training Epoch: 27 [2816/9756]	Loss: 0.3130	LR: 0.004000
Training Epoch: 27 [3072/9756]	Loss: 0.3153	LR: 0.004000
Training Epoch: 27 [3328/9756]	Loss: 0.2945	LR: 0.004000
Training Epoch: 27 [3584/9756]	Loss: 0.3061	LR: 0.004000
Training Epoch: 27 [3840/9756]	Loss: 0.3305	LR: 0.004000
Training Epoch: 27 [4096/9756]	Loss: 0.2828	LR: 0.004000
Training Epoch: 27 [4352/9756]	Loss: 0.3396	LR: 0.004000
Training Epoch: 27 [4608/9756]	Loss: 0.2985	LR: 0.004000
Training Epoch: 27 [4864/9756]	Loss: 0.2967	LR: 0.004000
Training Epoch: 27 [5120/9756]	Loss: 0.2684	LR: 0.004000
Training Epoch: 27 [5376/9756]	Loss: 0.2660	LR: 0.004000
Training Epoch: 27 [5632/9756]	Loss: 0.3188	LR: 0.004000
Training Epoch: 27 [5888/9756]	Loss: 0.2878	LR: 0.004000
Training Epoch: 27 [6144/9756]	Loss: 0.2549	LR: 0.004000
Training Epoch: 27 [6400/9756]	Loss: 0.2986	LR: 0.004000
Training Epoch: 27 [6656/9756]	Loss: 0.2784	LR: 0.004000
Training Epoch: 27 [6912/9756]	Loss: 0.2676	LR: 0.004000
Training Epoch: 27 [7168/9756]	Loss: 0.2464	LR: 0.004000
Training Epoch: 27 [7424/9756]	Loss: 0.2431	LR: 0.004000
Training Epoch: 27 [7680/9756]	Loss: 0.2851	LR: 0.004000
Training Epoch: 27 [7936/9756]	Loss: 0.3048	LR: 0.004000
Training Epoch: 27 [8192/9756]	Loss: 0.2629	LR: 0.004000
Training Epoch: 27 [8448/9756]	Loss: 0.2635	LR: 0.004000
Training Epoch: 27 [8704/9756]	Loss: 0.2557	LR: 0.004000
Training Epoch: 27 [8960/9756]	Loss: 0.3244	LR: 0.004000
Training Epoch: 27 [9216/9756]	Loss: 0.3129	LR: 0.004000
Training Epoch: 27 [9472/9756]	Loss: 0.2943	LR: 0.004000
Training Epoch: 27 [9728/9756]	Loss: 0.3126	LR: 0.004000
Training Epoch: 27 [9756/9756]	Loss: 0.1203	LR: 0.004000
Epoch 27 - Average Train Loss: 0.2942, Train Accuracy: 0.8752
Epoch 27 training time consumed: 140.65s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0016, Accuracy: 0.8412, Time consumed:8.10s
Training Epoch: 28 [256/9756]	Loss: 0.2853	LR: 0.004000
Training Epoch: 28 [512/9756]	Loss: 0.2489	LR: 0.004000
Training Epoch: 28 [768/9756]	Loss: 0.3186	LR: 0.004000
Training Epoch: 28 [1024/9756]	Loss: 0.2511	LR: 0.004000
Training Epoch: 28 [1280/9756]	Loss: 0.3079	LR: 0.004000
Training Epoch: 28 [1536/9756]	Loss: 0.2797	LR: 0.004000
Training Epoch: 28 [1792/9756]	Loss: 0.2964	LR: 0.004000
Training Epoch: 28 [2048/9756]	Loss: 0.2757	LR: 0.004000
Training Epoch: 28 [2304/9756]	Loss: 0.2401	LR: 0.004000
Training Epoch: 28 [2560/9756]	Loss: 0.3065	LR: 0.004000
Training Epoch: 28 [2816/9756]	Loss: 0.2554	LR: 0.004000
Training Epoch: 28 [3072/9756]	Loss: 0.2773	LR: 0.004000
Training Epoch: 28 [3328/9756]	Loss: 0.3532	LR: 0.004000
Training Epoch: 28 [3584/9756]	Loss: 0.2649	LR: 0.004000
Training Epoch: 28 [3840/9756]	Loss: 0.2732	LR: 0.004000
Training Epoch: 28 [4096/9756]	Loss: 0.2516	LR: 0.004000
Training Epoch: 28 [4352/9756]	Loss: 0.2349	LR: 0.004000
Training Epoch: 28 [4608/9756]	Loss: 0.3031	LR: 0.004000
Training Epoch: 28 [4864/9756]	Loss: 0.2729	LR: 0.004000
Training Epoch: 28 [5120/9756]	Loss: 0.2646	LR: 0.004000
Training Epoch: 28 [5376/9756]	Loss: 0.2551	LR: 0.004000
Training Epoch: 28 [5632/9756]	Loss: 0.2576	LR: 0.004000
Training Epoch: 28 [5888/9756]	Loss: 0.2801	LR: 0.004000
Training Epoch: 28 [6144/9756]	Loss: 0.3016	LR: 0.004000
Training Epoch: 28 [6400/9756]	Loss: 0.2713	LR: 0.004000
Training Epoch: 28 [6656/9756]	Loss: 0.2500	LR: 0.004000
Training Epoch: 28 [6912/9756]	Loss: 0.2607	LR: 0.004000
Training Epoch: 28 [7168/9756]	Loss: 0.2970	LR: 0.004000
Training Epoch: 28 [7424/9756]	Loss: 0.2824	LR: 0.004000
Training Epoch: 28 [7680/9756]	Loss: 0.2772	LR: 0.004000
Training Epoch: 28 [7936/9756]	Loss: 0.2608	LR: 0.004000
Training Epoch: 28 [8192/9756]	Loss: 0.2603	LR: 0.004000
Training Epoch: 28 [8448/9756]	Loss: 0.2366	LR: 0.004000
Training Epoch: 28 [8704/9756]	Loss: 0.2758	LR: 0.004000
Training Epoch: 28 [8960/9756]	Loss: 0.3061	LR: 0.004000
Training Epoch: 28 [9216/9756]	Loss: 0.2892	LR: 0.004000
Training Epoch: 28 [9472/9756]	Loss: 0.3440	LR: 0.004000
Training Epoch: 28 [9728/9756]	Loss: 0.2195	LR: 0.004000
Training Epoch: 28 [9756/9756]	Loss: 0.2228	LR: 0.004000
Epoch 28 - Average Train Loss: 0.2758, Train Accuracy: 0.8837
Epoch 28 training time consumed: 140.22s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0010, Accuracy: 0.9002, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_22h_41m_54s/ResNet18-MUCAC-seed2-ret25-28-best.pth
Training Epoch: 29 [256/9756]	Loss: 0.3084	LR: 0.004000
Training Epoch: 29 [512/9756]	Loss: 0.2646	LR: 0.004000
Training Epoch: 29 [768/9756]	Loss: 0.2376	LR: 0.004000
Training Epoch: 29 [1024/9756]	Loss: 0.2947	LR: 0.004000
Training Epoch: 29 [1280/9756]	Loss: 0.2729	LR: 0.004000
Training Epoch: 29 [1536/9756]	Loss: 0.2697	LR: 0.004000
Training Epoch: 29 [1792/9756]	Loss: 0.2325	LR: 0.004000
Training Epoch: 29 [2048/9756]	Loss: 0.2376	LR: 0.004000
Training Epoch: 29 [2304/9756]	Loss: 0.3196	LR: 0.004000
Training Epoch: 29 [2560/9756]	Loss: 0.2403	LR: 0.004000
Training Epoch: 29 [2816/9756]	Loss: 0.2573	LR: 0.004000
Training Epoch: 29 [3072/9756]	Loss: 0.2765	LR: 0.004000
Training Epoch: 29 [3328/9756]	Loss: 0.2423	LR: 0.004000
Training Epoch: 29 [3584/9756]	Loss: 0.2510	LR: 0.004000
Training Epoch: 29 [3840/9756]	Loss: 0.2579	LR: 0.004000
Training Epoch: 29 [4096/9756]	Loss: 0.2678	LR: 0.004000
Training Epoch: 29 [4352/9756]	Loss: 0.2557	LR: 0.004000
Training Epoch: 29 [4608/9756]	Loss: 0.3418	LR: 0.004000
Training Epoch: 29 [4864/9756]	Loss: 0.2494	LR: 0.004000
Training Epoch: 29 [5120/9756]	Loss: 0.2185	LR: 0.004000
Training Epoch: 29 [5376/9756]	Loss: 0.2468	LR: 0.004000
Training Epoch: 29 [5632/9756]	Loss: 0.1887	LR: 0.004000
Training Epoch: 29 [5888/9756]	Loss: 0.2993	LR: 0.004000
Training Epoch: 29 [6144/9756]	Loss: 0.2337	LR: 0.004000
Training Epoch: 29 [6400/9756]	Loss: 0.2213	LR: 0.004000
Training Epoch: 29 [6656/9756]	Loss: 0.2634	LR: 0.004000
Training Epoch: 29 [6912/9756]	Loss: 0.2542	LR: 0.004000
Training Epoch: 29 [7168/9756]	Loss: 0.2700	LR: 0.004000
Training Epoch: 29 [7424/9756]	Loss: 0.2705	LR: 0.004000
Training Epoch: 29 [7680/9756]	Loss: 0.2856	LR: 0.004000
Training Epoch: 29 [7936/9756]	Loss: 0.2685	LR: 0.004000
Training Epoch: 29 [8192/9756]	Loss: 0.2811	LR: 0.004000
Training Epoch: 29 [8448/9756]	Loss: 0.2779	LR: 0.004000
Training Epoch: 29 [8704/9756]	Loss: 0.2870	LR: 0.004000
Training Epoch: 29 [8960/9756]	Loss: 0.2706	LR: 0.004000
Training Epoch: 29 [9216/9756]	Loss: 0.2601	LR: 0.004000
Training Epoch: 29 [9472/9756]	Loss: 0.2495	LR: 0.004000
Training Epoch: 29 [9728/9756]	Loss: 0.3056	LR: 0.004000
Training Epoch: 29 [9756/9756]	Loss: 0.4289	LR: 0.004000
Epoch 29 - Average Train Loss: 0.2644, Train Accuracy: 0.8900
Epoch 29 training time consumed: 140.62s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0020, Accuracy: 0.7927, Time consumed:7.92s
Training Epoch: 30 [256/9756]	Loss: 0.2447	LR: 0.004000
Training Epoch: 30 [512/9756]	Loss: 0.2425	LR: 0.004000
Training Epoch: 30 [768/9756]	Loss: 0.2653	LR: 0.004000
Training Epoch: 30 [1024/9756]	Loss: 0.2655	LR: 0.004000
Training Epoch: 30 [1280/9756]	Loss: 0.2451	LR: 0.004000
Training Epoch: 30 [1536/9756]	Loss: 0.1817	LR: 0.004000
Training Epoch: 30 [1792/9756]	Loss: 0.2909	LR: 0.004000
Training Epoch: 30 [2048/9756]	Loss: 0.2945	LR: 0.004000
Training Epoch: 30 [2304/9756]	Loss: 0.2632	LR: 0.004000
Training Epoch: 30 [2560/9756]	Loss: 0.3415	LR: 0.004000
Training Epoch: 30 [2816/9756]	Loss: 0.2977	LR: 0.004000
Training Epoch: 30 [3072/9756]	Loss: 0.3133	LR: 0.004000
Training Epoch: 30 [3328/9756]	Loss: 0.3184	LR: 0.004000
Training Epoch: 30 [3584/9756]	Loss: 0.3350	LR: 0.004000
Training Epoch: 30 [3840/9756]	Loss: 0.2374	LR: 0.004000
Training Epoch: 30 [4096/9756]	Loss: 0.2174	LR: 0.004000
Training Epoch: 30 [4352/9756]	Loss: 0.2481	LR: 0.004000
Training Epoch: 30 [4608/9756]	Loss: 0.2667	LR: 0.004000
Training Epoch: 30 [4864/9756]	Loss: 0.2702	LR: 0.004000
Training Epoch: 30 [5120/9756]	Loss: 0.2671	LR: 0.004000
Training Epoch: 30 [5376/9756]	Loss: 0.2552	LR: 0.004000
Training Epoch: 30 [5632/9756]	Loss: 0.2427	LR: 0.004000
Training Epoch: 30 [5888/9756]	Loss: 0.3040	LR: 0.004000
Training Epoch: 30 [6144/9756]	Loss: 0.2404	LR: 0.004000
Training Epoch: 30 [6400/9756]	Loss: 0.2546	LR: 0.004000
Training Epoch: 30 [6656/9756]	Loss: 0.2395	LR: 0.004000
Training Epoch: 30 [6912/9756]	Loss: 0.2774	LR: 0.004000
Training Epoch: 30 [7168/9756]	Loss: 0.3023	LR: 0.004000
Training Epoch: 30 [7424/9756]	Loss: 0.2576	LR: 0.004000
Training Epoch: 30 [7680/9756]	Loss: 0.2268	LR: 0.004000
Training Epoch: 30 [7936/9756]	Loss: 0.2443	LR: 0.004000
Training Epoch: 30 [8192/9756]	Loss: 0.2236	LR: 0.004000
Training Epoch: 30 [8448/9756]	Loss: 0.2022	LR: 0.004000
Training Epoch: 30 [8704/9756]	Loss: 0.2521	LR: 0.004000
Training Epoch: 30 [8960/9756]	Loss: 0.2899	LR: 0.004000
Training Epoch: 30 [9216/9756]	Loss: 0.2431	LR: 0.004000
Training Epoch: 30 [9472/9756]	Loss: 0.2294	LR: 0.004000
Training Epoch: 30 [9728/9756]	Loss: 0.3038	LR: 0.004000
Training Epoch: 30 [9756/9756]	Loss: 0.2278	LR: 0.004000
Epoch 30 - Average Train Loss: 0.2629, Train Accuracy: 0.8907
Epoch 30 training time consumed: 140.58s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0012, Accuracy: 0.8794, Time consumed:7.90s
Training Epoch: 31 [256/9756]	Loss: 0.2577	LR: 0.004000
Training Epoch: 31 [512/9756]	Loss: 0.2574	LR: 0.004000
Training Epoch: 31 [768/9756]	Loss: 0.1995	LR: 0.004000
Training Epoch: 31 [1024/9756]	Loss: 0.3310	LR: 0.004000
Training Epoch: 31 [1280/9756]	Loss: 0.2794	LR: 0.004000
Training Epoch: 31 [1536/9756]	Loss: 0.2567	LR: 0.004000
Training Epoch: 31 [1792/9756]	Loss: 0.2926	LR: 0.004000
Training Epoch: 31 [2048/9756]	Loss: 0.2247	LR: 0.004000
Training Epoch: 31 [2304/9756]	Loss: 0.2402	LR: 0.004000
Training Epoch: 31 [2560/9756]	Loss: 0.2410	LR: 0.004000
Training Epoch: 31 [2816/9756]	Loss: 0.2831	LR: 0.004000
Training Epoch: 31 [3072/9756]	Loss: 0.2591	LR: 0.004000
Training Epoch: 31 [3328/9756]	Loss: 0.2623	LR: 0.004000
Training Epoch: 31 [3584/9756]	Loss: 0.2584	LR: 0.004000
Training Epoch: 31 [3840/9756]	Loss: 0.2435	LR: 0.004000
Training Epoch: 31 [4096/9756]	Loss: 0.2483	LR: 0.004000
Training Epoch: 31 [4352/9756]	Loss: 0.2384	LR: 0.004000
Training Epoch: 31 [4608/9756]	Loss: 0.2772	LR: 0.004000
Training Epoch: 31 [4864/9756]	Loss: 0.2001	LR: 0.004000
Training Epoch: 31 [5120/9756]	Loss: 0.2539	LR: 0.004000
Training Epoch: 31 [5376/9756]	Loss: 0.2428	LR: 0.004000
Training Epoch: 31 [5632/9756]	Loss: 0.2824	LR: 0.004000
Training Epoch: 31 [5888/9756]	Loss: 0.2620	LR: 0.004000
Training Epoch: 31 [6144/9756]	Loss: 0.2579	LR: 0.004000
Training Epoch: 31 [6400/9756]	Loss: 0.2461	LR: 0.004000
Training Epoch: 31 [6656/9756]	Loss: 0.2746	LR: 0.004000
Training Epoch: 31 [6912/9756]	Loss: 0.2739	LR: 0.004000
Training Epoch: 31 [7168/9756]	Loss: 0.2250	LR: 0.004000
Training Epoch: 31 [7424/9756]	Loss: 0.2507	LR: 0.004000
Training Epoch: 31 [7680/9756]	Loss: 0.2521	LR: 0.004000
Training Epoch: 31 [7936/9756]	Loss: 0.2779	LR: 0.004000
Training Epoch: 31 [8192/9756]	Loss: 0.2645	LR: 0.004000
Training Epoch: 31 [8448/9756]	Loss: 0.2522	LR: 0.004000
Training Epoch: 31 [8704/9756]	Loss: 0.2324	LR: 0.004000
Training Epoch: 31 [8960/9756]	Loss: 0.1909	LR: 0.004000
Training Epoch: 31 [9216/9756]	Loss: 0.2691	LR: 0.004000
Training Epoch: 31 [9472/9756]	Loss: 0.2730	LR: 0.004000
Training Epoch: 31 [9728/9756]	Loss: 0.2196	LR: 0.004000
Training Epoch: 31 [9756/9756]	Loss: 0.1729	LR: 0.004000
Epoch 31 - Average Train Loss: 0.2538, Train Accuracy: 0.8934
Epoch 31 training time consumed: 140.90s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0010, Accuracy: 0.8920, Time consumed:8.12s
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: 89.10079956054688
Retain Accuracy: 90.12277221679688
Zero-Retain Forget (ZRF): 0.8855236768722534
Membership Inference Attack (MIA): 0.4810606060606061
Forget vs Retain Membership Inference Attack (MIA): 0.4889589905362776
Forget vs Test Membership Inference Attack (MIA): 0.5488958990536278
Test vs Retain Membership Inference Attack (MIA): 0.5338983050847458
Train vs Test Membership Inference Attack (MIA): 0.5278450363196125
Forget Set Accuracy (Df): 89.90885925292969
Method Execution Time: 5771.41 seconds
