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

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

📌 S Forget class distribution for seed 5:
Class 0: 527
Class 1: 527

📊 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: 0.7835	LR: 0.000000
Training Epoch: 1 [512/9756]	Loss: 0.7606	LR: 0.002564
Training Epoch: 1 [768/9756]	Loss: 0.6925	LR: 0.005128
Training Epoch: 1 [1024/9756]	Loss: 0.9478	LR: 0.007692
Training Epoch: 1 [1280/9756]	Loss: 0.9334	LR: 0.010256
Training Epoch: 1 [1536/9756]	Loss: 0.7206	LR: 0.012821
Training Epoch: 1 [1792/9756]	Loss: 1.1872	LR: 0.015385
Training Epoch: 1 [2048/9756]	Loss: 0.7456	LR: 0.017949
Training Epoch: 1 [2304/9756]	Loss: 0.9942	LR: 0.020513
Training Epoch: 1 [2560/9756]	Loss: 1.2114	LR: 0.023077
Training Epoch: 1 [2816/9756]	Loss: 0.7050	LR: 0.025641
Training Epoch: 1 [3072/9756]	Loss: 1.2178	LR: 0.028205
Training Epoch: 1 [3328/9756]	Loss: 1.1810	LR: 0.030769
Training Epoch: 1 [3584/9756]	Loss: 0.6607	LR: 0.033333
Training Epoch: 1 [3840/9756]	Loss: 1.2328	LR: 0.035897
Training Epoch: 1 [4096/9756]	Loss: 0.8581	LR: 0.038462
Training Epoch: 1 [4352/9756]	Loss: 0.7268	LR: 0.041026
Training Epoch: 1 [4608/9756]	Loss: 1.0201	LR: 0.043590
Training Epoch: 1 [4864/9756]	Loss: 0.7798	LR: 0.046154
Training Epoch: 1 [5120/9756]	Loss: 0.7749	LR: 0.048718
Training Epoch: 1 [5376/9756]	Loss: 0.7470	LR: 0.051282
Training Epoch: 1 [5632/9756]	Loss: 0.6521	LR: 0.053846
Training Epoch: 1 [5888/9756]	Loss: 0.9109	LR: 0.056410
Training Epoch: 1 [6144/9756]	Loss: 0.7247	LR: 0.058974
Training Epoch: 1 [6400/9756]	Loss: 0.7860	LR: 0.061538
Training Epoch: 1 [6656/9756]	Loss: 0.7385	LR: 0.064103
Training Epoch: 1 [6912/9756]	Loss: 0.7604	LR: 0.066667
Training Epoch: 1 [7168/9756]	Loss: 0.9185	LR: 0.069231
Training Epoch: 1 [7424/9756]	Loss: 0.7262	LR: 0.071795
Training Epoch: 1 [7680/9756]	Loss: 0.8116	LR: 0.074359
Training Epoch: 1 [7936/9756]	Loss: 0.6646	LR: 0.076923
Training Epoch: 1 [8192/9756]	Loss: 0.8536	LR: 0.079487
Training Epoch: 1 [8448/9756]	Loss: 0.7646	LR: 0.082051
Training Epoch: 1 [8704/9756]	Loss: 0.8101	LR: 0.084615
Training Epoch: 1 [8960/9756]	Loss: 0.7120	LR: 0.087179
Training Epoch: 1 [9216/9756]	Loss: 0.7368	LR: 0.089744
Training Epoch: 1 [9472/9756]	Loss: 0.6834	LR: 0.092308
Training Epoch: 1 [9728/9756]	Loss: 0.7124	LR: 0.094872
Training Epoch: 1 [9756/9756]	Loss: 0.6530	LR: 0.097436
Epoch 1 - Average Train Loss: 0.8376, Train Accuracy: 0.5188
Epoch 1 training time consumed: 324.92s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0795, Accuracy: 0.5550, Time consumed:8.03s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-1-best.pth
Training Epoch: 2 [256/9756]	Loss: 0.8142	LR: 0.100000
Training Epoch: 2 [512/9756]	Loss: 0.6934	LR: 0.100000
Training Epoch: 2 [768/9756]	Loss: 0.7886	LR: 0.100000
Training Epoch: 2 [1024/9756]	Loss: 0.6787	LR: 0.100000
Training Epoch: 2 [1280/9756]	Loss: 0.7242	LR: 0.100000
Training Epoch: 2 [1536/9756]	Loss: 0.7138	LR: 0.100000
Training Epoch: 2 [1792/9756]	Loss: 0.7717	LR: 0.100000
Training Epoch: 2 [2048/9756]	Loss: 0.6658	LR: 0.100000
Training Epoch: 2 [2304/9756]	Loss: 0.6928	LR: 0.100000
Training Epoch: 2 [2560/9756]	Loss: 0.7160	LR: 0.100000
Training Epoch: 2 [2816/9756]	Loss: 0.7180	LR: 0.100000
Training Epoch: 2 [3072/9756]	Loss: 0.6775	LR: 0.100000
Training Epoch: 2 [3328/9756]	Loss: 0.6474	LR: 0.100000
Training Epoch: 2 [3584/9756]	Loss: 0.6670	LR: 0.100000
Training Epoch: 2 [3840/9756]	Loss: 0.7105	LR: 0.100000
Training Epoch: 2 [4096/9756]	Loss: 0.6584	LR: 0.100000
Training Epoch: 2 [4352/9756]	Loss: 0.6808	LR: 0.100000
Training Epoch: 2 [4608/9756]	Loss: 0.7359	LR: 0.100000
Training Epoch: 2 [4864/9756]	Loss: 0.7088	LR: 0.100000
Training Epoch: 2 [5120/9756]	Loss: 0.7254	LR: 0.100000
Training Epoch: 2 [5376/9756]	Loss: 0.7219	LR: 0.100000
Training Epoch: 2 [5632/9756]	Loss: 0.6860	LR: 0.100000
Training Epoch: 2 [5888/9756]	Loss: 0.6839	LR: 0.100000
Training Epoch: 2 [6144/9756]	Loss: 0.6690	LR: 0.100000
Training Epoch: 2 [6400/9756]	Loss: 0.6951	LR: 0.100000
Training Epoch: 2 [6656/9756]	Loss: 0.7073	LR: 0.100000
Training Epoch: 2 [6912/9756]	Loss: 0.7053	LR: 0.100000
Training Epoch: 2 [7168/9756]	Loss: 0.7116	LR: 0.100000
Training Epoch: 2 [7424/9756]	Loss: 0.7000	LR: 0.100000
Training Epoch: 2 [7680/9756]	Loss: 0.7248	LR: 0.100000
Training Epoch: 2 [7936/9756]	Loss: 0.6727	LR: 0.100000
Training Epoch: 2 [8192/9756]	Loss: 0.7261	LR: 0.100000
Training Epoch: 2 [8448/9756]	Loss: 0.6903	LR: 0.100000
Training Epoch: 2 [8704/9756]	Loss: 0.7086	LR: 0.100000
Training Epoch: 2 [8960/9756]	Loss: 0.6566	LR: 0.100000
Training Epoch: 2 [9216/9756]	Loss: 0.6958	LR: 0.100000
Training Epoch: 2 [9472/9756]	Loss: 0.6850	LR: 0.100000
Training Epoch: 2 [9728/9756]	Loss: 0.6865	LR: 0.100000
Training Epoch: 2 [9756/9756]	Loss: 0.5940	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7027, Train Accuracy: 0.5658
Epoch 2 training time consumed: 141.96s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0048, Accuracy: 0.4775, Time consumed:8.14s
Training Epoch: 3 [256/9756]	Loss: 0.9595	LR: 0.100000
Training Epoch: 3 [512/9756]	Loss: 0.8674	LR: 0.100000
Training Epoch: 3 [768/9756]	Loss: 0.9040	LR: 0.100000
Training Epoch: 3 [1024/9756]	Loss: 0.7247	LR: 0.100000
Training Epoch: 3 [1280/9756]	Loss: 1.0772	LR: 0.100000
Training Epoch: 3 [1536/9756]	Loss: 0.7452	LR: 0.100000
Training Epoch: 3 [1792/9756]	Loss: 0.9418	LR: 0.100000
Training Epoch: 3 [2048/9756]	Loss: 0.8268	LR: 0.100000
Training Epoch: 3 [2304/9756]	Loss: 0.7523	LR: 0.100000
Training Epoch: 3 [2560/9756]	Loss: 0.8941	LR: 0.100000
Training Epoch: 3 [2816/9756]	Loss: 0.6961	LR: 0.100000
Training Epoch: 3 [3072/9756]	Loss: 0.8343	LR: 0.100000
Training Epoch: 3 [3328/9756]	Loss: 0.7753	LR: 0.100000
Training Epoch: 3 [3584/9756]	Loss: 0.7069	LR: 0.100000
Training Epoch: 3 [3840/9756]	Loss: 0.7290	LR: 0.100000
Training Epoch: 3 [4096/9756]	Loss: 0.7504	LR: 0.100000
Training Epoch: 3 [4352/9756]	Loss: 0.6948	LR: 0.100000
Training Epoch: 3 [4608/9756]	Loss: 0.6881	LR: 0.100000
Training Epoch: 3 [4864/9756]	Loss: 0.7680	LR: 0.100000
Training Epoch: 3 [5120/9756]	Loss: 0.7108	LR: 0.100000
Training Epoch: 3 [5376/9756]	Loss: 0.6783	LR: 0.100000
Training Epoch: 3 [5632/9756]	Loss: 0.7027	LR: 0.100000
Training Epoch: 3 [5888/9756]	Loss: 0.7024	LR: 0.100000
Training Epoch: 3 [6144/9756]	Loss: 0.6970	LR: 0.100000
Training Epoch: 3 [6400/9756]	Loss: 0.6899	LR: 0.100000
Training Epoch: 3 [6656/9756]	Loss: 0.6845	LR: 0.100000
Training Epoch: 3 [6912/9756]	Loss: 0.6995	LR: 0.100000
Training Epoch: 3 [7168/9756]	Loss: 0.7036	LR: 0.100000
Training Epoch: 3 [7424/9756]	Loss: 0.6997	LR: 0.100000
Training Epoch: 3 [7680/9756]	Loss: 0.6665	LR: 0.100000
Training Epoch: 3 [7936/9756]	Loss: 0.6747	LR: 0.100000
Training Epoch: 3 [8192/9756]	Loss: 0.7211	LR: 0.100000
Training Epoch: 3 [8448/9756]	Loss: 0.6836	LR: 0.100000
Training Epoch: 3 [8704/9756]	Loss: 0.6895	LR: 0.100000
Training Epoch: 3 [8960/9756]	Loss: 0.7020	LR: 0.100000
Training Epoch: 3 [9216/9756]	Loss: 0.6581	LR: 0.100000
Training Epoch: 3 [9472/9756]	Loss: 0.6663	LR: 0.100000
Training Epoch: 3 [9728/9756]	Loss: 0.6891	LR: 0.100000
Training Epoch: 3 [9756/9756]	Loss: 0.7652	LR: 0.100000
Epoch 3 - Average Train Loss: 0.7489, Train Accuracy: 0.5249
Epoch 3 training time consumed: 141.32s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5734, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-3-best.pth
Training Epoch: 4 [256/9756]	Loss: 0.6566	LR: 0.100000
Training Epoch: 4 [512/9756]	Loss: 0.6944	LR: 0.100000
Training Epoch: 4 [768/9756]	Loss: 0.6904	LR: 0.100000
Training Epoch: 4 [1024/9756]	Loss: 0.7124	LR: 0.100000
Training Epoch: 4 [1280/9756]	Loss: 0.6848	LR: 0.100000
Training Epoch: 4 [1536/9756]	Loss: 0.6868	LR: 0.100000
Training Epoch: 4 [1792/9756]	Loss: 0.6827	LR: 0.100000
Training Epoch: 4 [2048/9756]	Loss: 0.6908	LR: 0.100000
Training Epoch: 4 [2304/9756]	Loss: 0.7060	LR: 0.100000
Training Epoch: 4 [2560/9756]	Loss: 0.6943	LR: 0.100000
Training Epoch: 4 [2816/9756]	Loss: 0.6967	LR: 0.100000
Training Epoch: 4 [3072/9756]	Loss: 0.6758	LR: 0.100000
Training Epoch: 4 [3328/9756]	Loss: 0.6984	LR: 0.100000
Training Epoch: 4 [3584/9756]	Loss: 0.7060	LR: 0.100000
Training Epoch: 4 [3840/9756]	Loss: 0.7066	LR: 0.100000
Training Epoch: 4 [4096/9756]	Loss: 0.6799	LR: 0.100000
Training Epoch: 4 [4352/9756]	Loss: 0.6746	LR: 0.100000
Training Epoch: 4 [4608/9756]	Loss: 0.7039	LR: 0.100000
Training Epoch: 4 [4864/9756]	Loss: 0.6784	LR: 0.100000
Training Epoch: 4 [5120/9756]	Loss: 0.7195	LR: 0.100000
Training Epoch: 4 [5376/9756]	Loss: 0.7128	LR: 0.100000
Training Epoch: 4 [5632/9756]	Loss: 0.6822	LR: 0.100000
Training Epoch: 4 [5888/9756]	Loss: 0.6789	LR: 0.100000
Training Epoch: 4 [6144/9756]	Loss: 0.6742	LR: 0.100000
Training Epoch: 4 [6400/9756]	Loss: 0.6840	LR: 0.100000
Training Epoch: 4 [6656/9756]	Loss: 0.6736	LR: 0.100000
Training Epoch: 4 [6912/9756]	Loss: 0.6967	LR: 0.100000
Training Epoch: 4 [7168/9756]	Loss: 0.6806	LR: 0.100000
Training Epoch: 4 [7424/9756]	Loss: 0.6462	LR: 0.100000
Training Epoch: 4 [7680/9756]	Loss: 0.7147	LR: 0.100000
Training Epoch: 4 [7936/9756]	Loss: 0.6824	LR: 0.100000
Training Epoch: 4 [8192/9756]	Loss: 0.6922	LR: 0.100000
Training Epoch: 4 [8448/9756]	Loss: 0.6612	LR: 0.100000
Training Epoch: 4 [8704/9756]	Loss: 0.6741	LR: 0.100000
Training Epoch: 4 [8960/9756]	Loss: 0.6647	LR: 0.100000
Training Epoch: 4 [9216/9756]	Loss: 0.6741	LR: 0.100000
Training Epoch: 4 [9472/9756]	Loss: 0.6886	LR: 0.100000
Training Epoch: 4 [9728/9756]	Loss: 0.6572	LR: 0.100000
Training Epoch: 4 [9756/9756]	Loss: 0.6220	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6861, Train Accuracy: 0.5603
Epoch 4 training time consumed: 141.41s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0035, Accuracy: 0.4780, Time consumed:7.98s
Training Epoch: 5 [256/9756]	Loss: 0.6857	LR: 0.100000
Training Epoch: 5 [512/9756]	Loss: 0.6941	LR: 0.100000
Training Epoch: 5 [768/9756]	Loss: 0.6925	LR: 0.100000
Training Epoch: 5 [1024/9756]	Loss: 0.6802	LR: 0.100000
Training Epoch: 5 [1280/9756]	Loss: 0.6601	LR: 0.100000
Training Epoch: 5 [1536/9756]	Loss: 0.7259	LR: 0.100000
Training Epoch: 5 [1792/9756]	Loss: 0.7009	LR: 0.100000
Training Epoch: 5 [2048/9756]	Loss: 0.6640	LR: 0.100000
Training Epoch: 5 [2304/9756]	Loss: 0.6772	LR: 0.100000
Training Epoch: 5 [2560/9756]	Loss: 0.6844	LR: 0.100000
Training Epoch: 5 [2816/9756]	Loss: 0.6953	LR: 0.100000
Training Epoch: 5 [3072/9756]	Loss: 0.6865	LR: 0.100000
Training Epoch: 5 [3328/9756]	Loss: 0.6971	LR: 0.100000
Training Epoch: 5 [3584/9756]	Loss: 0.6669	LR: 0.100000
Training Epoch: 5 [3840/9756]	Loss: 0.6734	LR: 0.100000
Training Epoch: 5 [4096/9756]	Loss: 0.6776	LR: 0.100000
Training Epoch: 5 [4352/9756]	Loss: 0.6613	LR: 0.100000
Training Epoch: 5 [4608/9756]	Loss: 0.6884	LR: 0.100000
Training Epoch: 5 [4864/9756]	Loss: 0.6932	LR: 0.100000
Training Epoch: 5 [5120/9756]	Loss: 0.6705	LR: 0.100000
Training Epoch: 5 [5376/9756]	Loss: 0.6792	LR: 0.100000
Training Epoch: 5 [5632/9756]	Loss: 0.6668	LR: 0.100000
Training Epoch: 5 [5888/9756]	Loss: 0.6964	LR: 0.100000
Training Epoch: 5 [6144/9756]	Loss: 0.6606	LR: 0.100000
Training Epoch: 5 [6400/9756]	Loss: 0.6870	LR: 0.100000
Training Epoch: 5 [6656/9756]	Loss: 0.6747	LR: 0.100000
Training Epoch: 5 [6912/9756]	Loss: 0.6860	LR: 0.100000
Training Epoch: 5 [7168/9756]	Loss: 0.6619	LR: 0.100000
Training Epoch: 5 [7424/9756]	Loss: 0.6818	LR: 0.100000
Training Epoch: 5 [7680/9756]	Loss: 0.6884	LR: 0.100000
Training Epoch: 5 [7936/9756]	Loss: 0.6912	LR: 0.100000
Training Epoch: 5 [8192/9756]	Loss: 0.6700	LR: 0.100000
Training Epoch: 5 [8448/9756]	Loss: 0.6779	LR: 0.100000
Training Epoch: 5 [8704/9756]	Loss: 0.6779	LR: 0.100000
Training Epoch: 5 [8960/9756]	Loss: 0.6806	LR: 0.100000
Training Epoch: 5 [9216/9756]	Loss: 0.6888	LR: 0.100000
Training Epoch: 5 [9472/9756]	Loss: 0.6899	LR: 0.100000
Training Epoch: 5 [9728/9756]	Loss: 0.6688	LR: 0.100000
Training Epoch: 5 [9756/9756]	Loss: 0.6981	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6817, Train Accuracy: 0.5657
Epoch 5 training time consumed: 141.18s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0031, Accuracy: 0.5593, Time consumed:8.10s
Training Epoch: 6 [256/9756]	Loss: 0.6730	LR: 0.100000
Training Epoch: 6 [512/9756]	Loss: 0.6848	LR: 0.100000
Training Epoch: 6 [768/9756]	Loss: 0.6549	LR: 0.100000
Training Epoch: 6 [1024/9756]	Loss: 0.6644	LR: 0.100000
Training Epoch: 6 [1280/9756]	Loss: 0.6807	LR: 0.100000
Training Epoch: 6 [1536/9756]	Loss: 0.6625	LR: 0.100000
Training Epoch: 6 [1792/9756]	Loss: 0.6924	LR: 0.100000
Training Epoch: 6 [2048/9756]	Loss: 0.6628	LR: 0.100000
Training Epoch: 6 [2304/9756]	Loss: 0.6698	LR: 0.100000
Training Epoch: 6 [2560/9756]	Loss: 0.6936	LR: 0.100000
Training Epoch: 6 [2816/9756]	Loss: 0.6969	LR: 0.100000
Training Epoch: 6 [3072/9756]	Loss: 0.6651	LR: 0.100000
Training Epoch: 6 [3328/9756]	Loss: 0.6787	LR: 0.100000
Training Epoch: 6 [3584/9756]	Loss: 0.6777	LR: 0.100000
Training Epoch: 6 [3840/9756]	Loss: 0.6916	LR: 0.100000
Training Epoch: 6 [4096/9756]	Loss: 0.6829	LR: 0.100000
Training Epoch: 6 [4352/9756]	Loss: 0.6657	LR: 0.100000
Training Epoch: 6 [4608/9756]	Loss: 0.6914	LR: 0.100000
Training Epoch: 6 [4864/9756]	Loss: 0.6653	LR: 0.100000
Training Epoch: 6 [5120/9756]	Loss: 0.6622	LR: 0.100000
Training Epoch: 6 [5376/9756]	Loss: 0.6674	LR: 0.100000
Training Epoch: 6 [5632/9756]	Loss: 0.6585	LR: 0.100000
Training Epoch: 6 [5888/9756]	Loss: 0.6706	LR: 0.100000
Training Epoch: 6 [6144/9756]	Loss: 0.6765	LR: 0.100000
Training Epoch: 6 [6400/9756]	Loss: 0.6837	LR: 0.100000
Training Epoch: 6 [6656/9756]	Loss: 0.6701	LR: 0.100000
Training Epoch: 6 [6912/9756]	Loss: 0.7000	LR: 0.100000
Training Epoch: 6 [7168/9756]	Loss: 0.6744	LR: 0.100000
Training Epoch: 6 [7424/9756]	Loss: 0.6713	LR: 0.100000
Training Epoch: 6 [7680/9756]	Loss: 0.6520	LR: 0.100000
Training Epoch: 6 [7936/9756]	Loss: 0.6918	LR: 0.100000
Training Epoch: 6 [8192/9756]	Loss: 0.6504	LR: 0.100000
Training Epoch: 6 [8448/9756]	Loss: 0.6754	LR: 0.100000
Training Epoch: 6 [8704/9756]	Loss: 0.6564	LR: 0.100000
Training Epoch: 6 [8960/9756]	Loss: 0.6937	LR: 0.100000
Training Epoch: 6 [9216/9756]	Loss: 0.6775	LR: 0.100000
Training Epoch: 6 [9472/9756]	Loss: 0.6516	LR: 0.100000
Training Epoch: 6 [9728/9756]	Loss: 0.6360	LR: 0.100000
Training Epoch: 6 [9756/9756]	Loss: 0.6807	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6730, Train Accuracy: 0.5884
Epoch 6 training time consumed: 140.93s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0029, Accuracy: 0.6034, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-6-best.pth
Training Epoch: 7 [256/9756]	Loss: 0.6725	LR: 0.100000
Training Epoch: 7 [512/9756]	Loss: 0.7158	LR: 0.100000
Training Epoch: 7 [768/9756]	Loss: 0.6799	LR: 0.100000
Training Epoch: 7 [1024/9756]	Loss: 0.6426	LR: 0.100000
Training Epoch: 7 [1280/9756]	Loss: 0.6785	LR: 0.100000
Training Epoch: 7 [1536/9756]	Loss: 0.6803	LR: 0.100000
Training Epoch: 7 [1792/9756]	Loss: 0.6767	LR: 0.100000
Training Epoch: 7 [2048/9756]	Loss: 0.6771	LR: 0.100000
Training Epoch: 7 [2304/9756]	Loss: 0.6724	LR: 0.100000
Training Epoch: 7 [2560/9756]	Loss: 0.6495	LR: 0.100000
Training Epoch: 7 [2816/9756]	Loss: 0.6731	LR: 0.100000
Training Epoch: 7 [3072/9756]	Loss: 0.6567	LR: 0.100000
Training Epoch: 7 [3328/9756]	Loss: 0.6937	LR: 0.100000
Training Epoch: 7 [3584/9756]	Loss: 0.6620	LR: 0.100000
Training Epoch: 7 [3840/9756]	Loss: 0.6668	LR: 0.100000
Training Epoch: 7 [4096/9756]	Loss: 0.7011	LR: 0.100000
Training Epoch: 7 [4352/9756]	Loss: 0.6748	LR: 0.100000
Training Epoch: 7 [4608/9756]	Loss: 0.6656	LR: 0.100000
Training Epoch: 7 [4864/9756]	Loss: 0.6643	LR: 0.100000
Training Epoch: 7 [5120/9756]	Loss: 0.6221	LR: 0.100000
Training Epoch: 7 [5376/9756]	Loss: 0.6321	LR: 0.100000
Training Epoch: 7 [5632/9756]	Loss: 0.6815	LR: 0.100000
Training Epoch: 7 [5888/9756]	Loss: 0.6438	LR: 0.100000
Training Epoch: 7 [6144/9756]	Loss: 0.6538	LR: 0.100000
Training Epoch: 7 [6400/9756]	Loss: 0.6572	LR: 0.100000
Training Epoch: 7 [6656/9756]	Loss: 0.6814	LR: 0.100000
Training Epoch: 7 [6912/9756]	Loss: 0.6651	LR: 0.100000
Training Epoch: 7 [7168/9756]	Loss: 0.6558	LR: 0.100000
Training Epoch: 7 [7424/9756]	Loss: 0.6602	LR: 0.100000
Training Epoch: 7 [7680/9756]	Loss: 0.6382	LR: 0.100000
Training Epoch: 7 [7936/9756]	Loss: 0.6521	LR: 0.100000
Training Epoch: 7 [8192/9756]	Loss: 0.6766	LR: 0.100000
Training Epoch: 7 [8448/9756]	Loss: 0.6774	LR: 0.100000
Training Epoch: 7 [8704/9756]	Loss: 0.6676	LR: 0.100000
Training Epoch: 7 [8960/9756]	Loss: 0.6500	LR: 0.100000
Training Epoch: 7 [9216/9756]	Loss: 0.6816	LR: 0.100000
Training Epoch: 7 [9472/9756]	Loss: 0.6651	LR: 0.100000
Training Epoch: 7 [9728/9756]	Loss: 0.6379	LR: 0.100000
Training Epoch: 7 [9756/9756]	Loss: 0.6609	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6659, Train Accuracy: 0.6075
Epoch 7 training time consumed: 140.89s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0030, Accuracy: 0.5758, Time consumed:7.90s
Training Epoch: 8 [256/9756]	Loss: 0.6689	LR: 0.100000
Training Epoch: 8 [512/9756]	Loss: 0.6308	LR: 0.100000
Training Epoch: 8 [768/9756]	Loss: 0.6332	LR: 0.100000
Training Epoch: 8 [1024/9756]	Loss: 0.7113	LR: 0.100000
Training Epoch: 8 [1280/9756]	Loss: 0.6611	LR: 0.100000
Training Epoch: 8 [1536/9756]	Loss: 0.6675	LR: 0.100000
Training Epoch: 8 [1792/9756]	Loss: 0.6634	LR: 0.100000
Training Epoch: 8 [2048/9756]	Loss: 0.6700	LR: 0.100000
Training Epoch: 8 [2304/9756]	Loss: 0.6530	LR: 0.100000
Training Epoch: 8 [2560/9756]	Loss: 0.6399	LR: 0.100000
Training Epoch: 8 [2816/9756]	Loss: 0.6586	LR: 0.100000
Training Epoch: 8 [3072/9756]	Loss: 0.6506	LR: 0.100000
Training Epoch: 8 [3328/9756]	Loss: 0.6678	LR: 0.100000
Training Epoch: 8 [3584/9756]	Loss: 0.7145	LR: 0.100000
Training Epoch: 8 [3840/9756]	Loss: 0.6488	LR: 0.100000
Training Epoch: 8 [4096/9756]	Loss: 0.6709	LR: 0.100000
Training Epoch: 8 [4352/9756]	Loss: 0.6811	LR: 0.100000
Training Epoch: 8 [4608/9756]	Loss: 0.6389	LR: 0.100000
Training Epoch: 8 [4864/9756]	Loss: 0.6686	LR: 0.100000
Training Epoch: 8 [5120/9756]	Loss: 0.6311	LR: 0.100000
Training Epoch: 8 [5376/9756]	Loss: 0.6570	LR: 0.100000
Training Epoch: 8 [5632/9756]	Loss: 0.6370	LR: 0.100000
Training Epoch: 8 [5888/9756]	Loss: 0.6683	LR: 0.100000
Training Epoch: 8 [6144/9756]	Loss: 0.6130	LR: 0.100000
Training Epoch: 8 [6400/9756]	Loss: 0.6169	LR: 0.100000
Training Epoch: 8 [6656/9756]	Loss: 0.6223	LR: 0.100000
Training Epoch: 8 [6912/9756]	Loss: 0.6138	LR: 0.100000
Training Epoch: 8 [7168/9756]	Loss: 0.5960	LR: 0.100000
Training Epoch: 8 [7424/9756]	Loss: 0.6589	LR: 0.100000
Training Epoch: 8 [7680/9756]	Loss: 0.6753	LR: 0.100000
Training Epoch: 8 [7936/9756]	Loss: 0.6129	LR: 0.100000
Training Epoch: 8 [8192/9756]	Loss: 0.6420	LR: 0.100000
Training Epoch: 8 [8448/9756]	Loss: 0.6076	LR: 0.100000
Training Epoch: 8 [8704/9756]	Loss: 0.6392	LR: 0.100000
Training Epoch: 8 [8960/9756]	Loss: 0.6088	LR: 0.100000
Training Epoch: 8 [9216/9756]	Loss: 0.6189	LR: 0.100000
Training Epoch: 8 [9472/9756]	Loss: 0.6405	LR: 0.100000
Training Epoch: 8 [9728/9756]	Loss: 0.5974	LR: 0.100000
Training Epoch: 8 [9756/9756]	Loss: 0.5504	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6459, Train Accuracy: 0.6356
Epoch 8 training time consumed: 140.40s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0027, Accuracy: 0.6586, Time consumed:7.92s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-8-best.pth
Training Epoch: 9 [256/9756]	Loss: 0.6651	LR: 0.100000
Training Epoch: 9 [512/9756]	Loss: 0.7338	LR: 0.100000
Training Epoch: 9 [768/9756]	Loss: 0.5888	LR: 0.100000
Training Epoch: 9 [1024/9756]	Loss: 0.5899	LR: 0.100000
Training Epoch: 9 [1280/9756]	Loss: 0.6101	LR: 0.100000
Training Epoch: 9 [1536/9756]	Loss: 0.6478	LR: 0.100000
Training Epoch: 9 [1792/9756]	Loss: 0.6318	LR: 0.100000
Training Epoch: 9 [2048/9756]	Loss: 0.6119	LR: 0.100000
Training Epoch: 9 [2304/9756]	Loss: 0.6408	LR: 0.100000
Training Epoch: 9 [2560/9756]	Loss: 0.5898	LR: 0.100000
Training Epoch: 9 [2816/9756]	Loss: 0.6087	LR: 0.100000
Training Epoch: 9 [3072/9756]	Loss: 0.6071	LR: 0.100000
Training Epoch: 9 [3328/9756]	Loss: 0.6124	LR: 0.100000
Training Epoch: 9 [3584/9756]	Loss: 0.6437	LR: 0.100000
Training Epoch: 9 [3840/9756]	Loss: 0.5942	LR: 0.100000
Training Epoch: 9 [4096/9756]	Loss: 0.6181	LR: 0.100000
Training Epoch: 9 [4352/9756]	Loss: 0.5837	LR: 0.100000
Training Epoch: 9 [4608/9756]	Loss: 0.5928	LR: 0.100000
Training Epoch: 9 [4864/9756]	Loss: 0.5667	LR: 0.100000
Training Epoch: 9 [5120/9756]	Loss: 0.6043	LR: 0.100000
Training Epoch: 9 [5376/9756]	Loss: 0.5881	LR: 0.100000
Training Epoch: 9 [5632/9756]	Loss: 0.6515	LR: 0.100000
Training Epoch: 9 [5888/9756]	Loss: 0.6515	LR: 0.100000
Training Epoch: 9 [6144/9756]	Loss: 0.5543	LR: 0.100000
Training Epoch: 9 [6400/9756]	Loss: 0.5447	LR: 0.100000
Training Epoch: 9 [6656/9756]	Loss: 0.5756	LR: 0.100000
Training Epoch: 9 [6912/9756]	Loss: 0.5642	LR: 0.100000
Training Epoch: 9 [7168/9756]	Loss: 0.6018	LR: 0.100000
Training Epoch: 9 [7424/9756]	Loss: 0.5602	LR: 0.100000
Training Epoch: 9 [7680/9756]	Loss: 0.6199	LR: 0.100000
Training Epoch: 9 [7936/9756]	Loss: 0.5895	LR: 0.100000
Training Epoch: 9 [8192/9756]	Loss: 0.5556	LR: 0.100000
Training Epoch: 9 [8448/9756]	Loss: 0.5686	LR: 0.100000
Training Epoch: 9 [8704/9756]	Loss: 0.5746	LR: 0.100000
Training Epoch: 9 [8960/9756]	Loss: 0.6106	LR: 0.100000
Training Epoch: 9 [9216/9756]	Loss: 0.5931	LR: 0.100000
Training Epoch: 9 [9472/9756]	Loss: 0.5618	LR: 0.100000
Training Epoch: 9 [9728/9756]	Loss: 0.5784	LR: 0.100000
Training Epoch: 9 [9756/9756]	Loss: 0.4153	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6017, Train Accuracy: 0.6831
Epoch 9 training time consumed: 140.99s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0025, Accuracy: 0.7196, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-9-best.pth
Training Epoch: 10 [256/9756]	Loss: 0.5366	LR: 0.020000
Training Epoch: 10 [512/9756]	Loss: 0.5844	LR: 0.020000
Training Epoch: 10 [768/9756]	Loss: 0.5830	LR: 0.020000
Training Epoch: 10 [1024/9756]	Loss: 0.6156	LR: 0.020000
Training Epoch: 10 [1280/9756]	Loss: 0.5483	LR: 0.020000
Training Epoch: 10 [1536/9756]	Loss: 0.5747	LR: 0.020000
Training Epoch: 10 [1792/9756]	Loss: 0.5379	LR: 0.020000
Training Epoch: 10 [2048/9756]	Loss: 0.5699	LR: 0.020000
Training Epoch: 10 [2304/9756]	Loss: 0.5778	LR: 0.020000
Training Epoch: 10 [2560/9756]	Loss: 0.5499	LR: 0.020000
Training Epoch: 10 [2816/9756]	Loss: 0.5952	LR: 0.020000
Training Epoch: 10 [3072/9756]	Loss: 0.5646	LR: 0.020000
Training Epoch: 10 [3328/9756]	Loss: 0.5506	LR: 0.020000
Training Epoch: 10 [3584/9756]	Loss: 0.5312	LR: 0.020000
Training Epoch: 10 [3840/9756]	Loss: 0.5569	LR: 0.020000
Training Epoch: 10 [4096/9756]	Loss: 0.5613	LR: 0.020000
Training Epoch: 10 [4352/9756]	Loss: 0.5809	LR: 0.020000
Training Epoch: 10 [4608/9756]	Loss: 0.5733	LR: 0.020000
Training Epoch: 10 [4864/9756]	Loss: 0.5279	LR: 0.020000
Training Epoch: 10 [5120/9756]	Loss: 0.5376	LR: 0.020000
Training Epoch: 10 [5376/9756]	Loss: 0.5377	LR: 0.020000
Training Epoch: 10 [5632/9756]	Loss: 0.5581	LR: 0.020000
Training Epoch: 10 [5888/9756]	Loss: 0.5187	LR: 0.020000
Training Epoch: 10 [6144/9756]	Loss: 0.4863	LR: 0.020000
Training Epoch: 10 [6400/9756]	Loss: 0.5035	LR: 0.020000
Training Epoch: 10 [6656/9756]	Loss: 0.5033	LR: 0.020000
Training Epoch: 10 [6912/9756]	Loss: 0.4592	LR: 0.020000
Training Epoch: 10 [7168/9756]	Loss: 0.4538	LR: 0.020000
Training Epoch: 10 [7424/9756]	Loss: 0.5299	LR: 0.020000
Training Epoch: 10 [7680/9756]	Loss: 0.5081	LR: 0.020000
Training Epoch: 10 [7936/9756]	Loss: 0.4881	LR: 0.020000
Training Epoch: 10 [8192/9756]	Loss: 0.4937	LR: 0.020000
Training Epoch: 10 [8448/9756]	Loss: 0.4842	LR: 0.020000
Training Epoch: 10 [8704/9756]	Loss: 0.4900	LR: 0.020000
Training Epoch: 10 [8960/9756]	Loss: 0.4830	LR: 0.020000
Training Epoch: 10 [9216/9756]	Loss: 0.4930	LR: 0.020000
Training Epoch: 10 [9472/9756]	Loss: 0.5185	LR: 0.020000
Training Epoch: 10 [9728/9756]	Loss: 0.5571	LR: 0.020000
Training Epoch: 10 [9756/9756]	Loss: 0.5652	LR: 0.020000
Epoch 10 - Average Train Loss: 0.5349, Train Accuracy: 0.7386
Epoch 10 training time consumed: 141.04s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0047, Accuracy: 0.5550, Time consumed:8.03s
Training Epoch: 11 [256/9756]	Loss: 0.4840	LR: 0.020000
Training Epoch: 11 [512/9756]	Loss: 0.5246	LR: 0.020000
Training Epoch: 11 [768/9756]	Loss: 0.4525	LR: 0.020000
Training Epoch: 11 [1024/9756]	Loss: 0.4388	LR: 0.020000
Training Epoch: 11 [1280/9756]	Loss: 0.4866	LR: 0.020000
Training Epoch: 11 [1536/9756]	Loss: 0.5554	LR: 0.020000
Training Epoch: 11 [1792/9756]	Loss: 0.4807	LR: 0.020000
Training Epoch: 11 [2048/9756]	Loss: 0.4861	LR: 0.020000
Training Epoch: 11 [2304/9756]	Loss: 0.4491	LR: 0.020000
Training Epoch: 11 [2560/9756]	Loss: 0.4526	LR: 0.020000
Training Epoch: 11 [2816/9756]	Loss: 0.5285	LR: 0.020000
Training Epoch: 11 [3072/9756]	Loss: 0.5002	LR: 0.020000
Training Epoch: 11 [3328/9756]	Loss: 0.4755	LR: 0.020000
Training Epoch: 11 [3584/9756]	Loss: 0.4266	LR: 0.020000
Training Epoch: 11 [3840/9756]	Loss: 0.3977	LR: 0.020000
Training Epoch: 11 [4096/9756]	Loss: 0.4270	LR: 0.020000
Training Epoch: 11 [4352/9756]	Loss: 0.4916	LR: 0.020000
Training Epoch: 11 [4608/9756]	Loss: 0.4024	LR: 0.020000
Training Epoch: 11 [4864/9756]	Loss: 0.4757	LR: 0.020000
Training Epoch: 11 [5120/9756]	Loss: 0.4866	LR: 0.020000
Training Epoch: 11 [5376/9756]	Loss: 0.5262	LR: 0.020000
Training Epoch: 11 [5632/9756]	Loss: 0.4592	LR: 0.020000
Training Epoch: 11 [5888/9756]	Loss: 0.5305	LR: 0.020000
Training Epoch: 11 [6144/9756]	Loss: 0.4180	LR: 0.020000
Training Epoch: 11 [6400/9756]	Loss: 0.4659	LR: 0.020000
Training Epoch: 11 [6656/9756]	Loss: 0.4859	LR: 0.020000
Training Epoch: 11 [6912/9756]	Loss: 0.4538	LR: 0.020000
Training Epoch: 11 [7168/9756]	Loss: 0.4323	LR: 0.020000
Training Epoch: 11 [7424/9756]	Loss: 0.4725	LR: 0.020000
Training Epoch: 11 [7680/9756]	Loss: 0.4384	LR: 0.020000
Training Epoch: 11 [7936/9756]	Loss: 0.4245	LR: 0.020000
Training Epoch: 11 [8192/9756]	Loss: 0.3919	LR: 0.020000
Training Epoch: 11 [8448/9756]	Loss: 0.4203	LR: 0.020000
Training Epoch: 11 [8704/9756]	Loss: 0.4644	LR: 0.020000
Training Epoch: 11 [8960/9756]	Loss: 0.5010	LR: 0.020000
Training Epoch: 11 [9216/9756]	Loss: 0.4285	LR: 0.020000
Training Epoch: 11 [9472/9756]	Loss: 0.4139	LR: 0.020000
Training Epoch: 11 [9728/9756]	Loss: 0.4662	LR: 0.020000
Training Epoch: 11 [9756/9756]	Loss: 0.2783	LR: 0.020000
Epoch 11 - Average Train Loss: 0.4630, Train Accuracy: 0.7853
Epoch 11 training time consumed: 140.78s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0031, Accuracy: 0.6746, Time consumed:7.95s
Training Epoch: 12 [256/9756]	Loss: 0.4256	LR: 0.020000
Training Epoch: 12 [512/9756]	Loss: 0.4700	LR: 0.020000
Training Epoch: 12 [768/9756]	Loss: 0.4862	LR: 0.020000
Training Epoch: 12 [1024/9756]	Loss: 0.4006	LR: 0.020000
Training Epoch: 12 [1280/9756]	Loss: 0.4675	LR: 0.020000
Training Epoch: 12 [1536/9756]	Loss: 0.4399	LR: 0.020000
Training Epoch: 12 [1792/9756]	Loss: 0.4557	LR: 0.020000
Training Epoch: 12 [2048/9756]	Loss: 0.3649	LR: 0.020000
Training Epoch: 12 [2304/9756]	Loss: 0.4159	LR: 0.020000
Training Epoch: 12 [2560/9756]	Loss: 0.4828	LR: 0.020000
Training Epoch: 12 [2816/9756]	Loss: 0.4608	LR: 0.020000
Training Epoch: 12 [3072/9756]	Loss: 0.4531	LR: 0.020000
Training Epoch: 12 [3328/9756]	Loss: 0.4418	LR: 0.020000
Training Epoch: 12 [3584/9756]	Loss: 0.4164	LR: 0.020000
Training Epoch: 12 [3840/9756]	Loss: 0.5169	LR: 0.020000
Training Epoch: 12 [4096/9756]	Loss: 0.5014	LR: 0.020000
Training Epoch: 12 [4352/9756]	Loss: 0.4039	LR: 0.020000
Training Epoch: 12 [4608/9756]	Loss: 0.4784	LR: 0.020000
Training Epoch: 12 [4864/9756]	Loss: 0.4058	LR: 0.020000
Training Epoch: 12 [5120/9756]	Loss: 0.4045	LR: 0.020000
Training Epoch: 12 [5376/9756]	Loss: 0.4039	LR: 0.020000
Training Epoch: 12 [5632/9756]	Loss: 0.5265	LR: 0.020000
Training Epoch: 12 [5888/9756]	Loss: 0.4923	LR: 0.020000
Training Epoch: 12 [6144/9756]	Loss: 0.4695	LR: 0.020000
Training Epoch: 12 [6400/9756]	Loss: 0.4416	LR: 0.020000
Training Epoch: 12 [6656/9756]	Loss: 0.3712	LR: 0.020000
Training Epoch: 12 [6912/9756]	Loss: 0.4020	LR: 0.020000
Training Epoch: 12 [7168/9756]	Loss: 0.3854	LR: 0.020000
Training Epoch: 12 [7424/9756]	Loss: 0.4440	LR: 0.020000
Training Epoch: 12 [7680/9756]	Loss: 0.4150	LR: 0.020000
Training Epoch: 12 [7936/9756]	Loss: 0.4055	LR: 0.020000
Training Epoch: 12 [8192/9756]	Loss: 0.3900	LR: 0.020000
Training Epoch: 12 [8448/9756]	Loss: 0.4131	LR: 0.020000
Training Epoch: 12 [8704/9756]	Loss: 0.3900	LR: 0.020000
Training Epoch: 12 [8960/9756]	Loss: 0.4229	LR: 0.020000
Training Epoch: 12 [9216/9756]	Loss: 0.3982	LR: 0.020000
Training Epoch: 12 [9472/9756]	Loss: 0.4128	LR: 0.020000
Training Epoch: 12 [9728/9756]	Loss: 0.3658	LR: 0.020000
Training Epoch: 12 [9756/9756]	Loss: 0.3769	LR: 0.020000
Epoch 12 - Average Train Loss: 0.4325, Train Accuracy: 0.7995
Epoch 12 training time consumed: 140.95s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0016, Accuracy: 0.8450, Time consumed:7.75s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-12-best.pth
Training Epoch: 13 [256/9756]	Loss: 0.3833	LR: 0.020000
Training Epoch: 13 [512/9756]	Loss: 0.4402	LR: 0.020000
Training Epoch: 13 [768/9756]	Loss: 0.3606	LR: 0.020000
Training Epoch: 13 [1024/9756]	Loss: 0.3339	LR: 0.020000
Training Epoch: 13 [1280/9756]	Loss: 0.4463	LR: 0.020000
Training Epoch: 13 [1536/9756]	Loss: 0.5215	LR: 0.020000
Training Epoch: 13 [1792/9756]	Loss: 0.3808	LR: 0.020000
Training Epoch: 13 [2048/9756]	Loss: 0.3745	LR: 0.020000
Training Epoch: 13 [2304/9756]	Loss: 0.3902	LR: 0.020000
Training Epoch: 13 [2560/9756]	Loss: 0.3748	LR: 0.020000
Training Epoch: 13 [2816/9756]	Loss: 0.3707	LR: 0.020000
Training Epoch: 13 [3072/9756]	Loss: 0.3820	LR: 0.020000
Training Epoch: 13 [3328/9756]	Loss: 0.3973	LR: 0.020000
Training Epoch: 13 [3584/9756]	Loss: 0.4439	LR: 0.020000
Training Epoch: 13 [3840/9756]	Loss: 0.4155	LR: 0.020000
Training Epoch: 13 [4096/9756]	Loss: 0.4039	LR: 0.020000
Training Epoch: 13 [4352/9756]	Loss: 0.4252	LR: 0.020000
Training Epoch: 13 [4608/9756]	Loss: 0.3730	LR: 0.020000
Training Epoch: 13 [4864/9756]	Loss: 0.3627	LR: 0.020000
Training Epoch: 13 [5120/9756]	Loss: 0.3806	LR: 0.020000
Training Epoch: 13 [5376/9756]	Loss: 0.3382	LR: 0.020000
Training Epoch: 13 [5632/9756]	Loss: 0.4118	LR: 0.020000
Training Epoch: 13 [5888/9756]	Loss: 0.3380	LR: 0.020000
Training Epoch: 13 [6144/9756]	Loss: 0.4647	LR: 0.020000
Training Epoch: 13 [6400/9756]	Loss: 0.4212	LR: 0.020000
Training Epoch: 13 [6656/9756]	Loss: 0.4629	LR: 0.020000
Training Epoch: 13 [6912/9756]	Loss: 0.3643	LR: 0.020000
Training Epoch: 13 [7168/9756]	Loss: 0.3528	LR: 0.020000
Training Epoch: 13 [7424/9756]	Loss: 0.3406	LR: 0.020000
Training Epoch: 13 [7680/9756]	Loss: 0.4080	LR: 0.020000
Training Epoch: 13 [7936/9756]	Loss: 0.4504	LR: 0.020000
Training Epoch: 13 [8192/9756]	Loss: 0.3786	LR: 0.020000
Training Epoch: 13 [8448/9756]	Loss: 0.3234	LR: 0.020000
Training Epoch: 13 [8704/9756]	Loss: 0.3925	LR: 0.020000
Training Epoch: 13 [8960/9756]	Loss: 0.3934	LR: 0.020000
Training Epoch: 13 [9216/9756]	Loss: 0.3781	LR: 0.020000
Training Epoch: 13 [9472/9756]	Loss: 0.3268	LR: 0.020000
Training Epoch: 13 [9728/9756]	Loss: 0.3892	LR: 0.020000
Training Epoch: 13 [9756/9756]	Loss: 0.3259	LR: 0.020000
Epoch 13 - Average Train Loss: 0.3918, Train Accuracy: 0.8248
Epoch 13 training time consumed: 140.56s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0014, Accuracy: 0.8625, Time consumed:8.23s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-13-best.pth
Training Epoch: 14 [256/9756]	Loss: 0.3204	LR: 0.020000
Training Epoch: 14 [512/9756]	Loss: 0.3827	LR: 0.020000
Training Epoch: 14 [768/9756]	Loss: 0.3727	LR: 0.020000
Training Epoch: 14 [1024/9756]	Loss: 0.3800	LR: 0.020000
Training Epoch: 14 [1280/9756]	Loss: 0.3604	LR: 0.020000
Training Epoch: 14 [1536/9756]	Loss: 0.4115	LR: 0.020000
Training Epoch: 14 [1792/9756]	Loss: 0.4659	LR: 0.020000
Training Epoch: 14 [2048/9756]	Loss: 0.3445	LR: 0.020000
Training Epoch: 14 [2304/9756]	Loss: 0.3715	LR: 0.020000
Training Epoch: 14 [2560/9756]	Loss: 0.3468	LR: 0.020000
Training Epoch: 14 [2816/9756]	Loss: 0.3551	LR: 0.020000
Training Epoch: 14 [3072/9756]	Loss: 0.3111	LR: 0.020000
Training Epoch: 14 [3328/9756]	Loss: 0.3941	LR: 0.020000
Training Epoch: 14 [3584/9756]	Loss: 0.4177	LR: 0.020000
Training Epoch: 14 [3840/9756]	Loss: 0.4019	LR: 0.020000
Training Epoch: 14 [4096/9756]	Loss: 0.3789	LR: 0.020000
Training Epoch: 14 [4352/9756]	Loss: 0.3703	LR: 0.020000
Training Epoch: 14 [4608/9756]	Loss: 0.3247	LR: 0.020000
Training Epoch: 14 [4864/9756]	Loss: 0.3666	LR: 0.020000
Training Epoch: 14 [5120/9756]	Loss: 0.3131	LR: 0.020000
Training Epoch: 14 [5376/9756]	Loss: 0.3437	LR: 0.020000
Training Epoch: 14 [5632/9756]	Loss: 0.3500	LR: 0.020000
Training Epoch: 14 [5888/9756]	Loss: 0.3839	LR: 0.020000
Training Epoch: 14 [6144/9756]	Loss: 0.3515	LR: 0.020000
Training Epoch: 14 [6400/9756]	Loss: 0.4003	LR: 0.020000
Training Epoch: 14 [6656/9756]	Loss: 0.3435	LR: 0.020000
Training Epoch: 14 [6912/9756]	Loss: 0.4001	LR: 0.020000
Training Epoch: 14 [7168/9756]	Loss: 0.3223	LR: 0.020000
Training Epoch: 14 [7424/9756]	Loss: 0.3313	LR: 0.020000
Training Epoch: 14 [7680/9756]	Loss: 0.3173	LR: 0.020000
Training Epoch: 14 [7936/9756]	Loss: 0.3446	LR: 0.020000
Training Epoch: 14 [8192/9756]	Loss: 0.3809	LR: 0.020000
Training Epoch: 14 [8448/9756]	Loss: 0.3913	LR: 0.020000
Training Epoch: 14 [8704/9756]	Loss: 0.2920	LR: 0.020000
Training Epoch: 14 [8960/9756]	Loss: 0.3657	LR: 0.020000
Training Epoch: 14 [9216/9756]	Loss: 0.3835	LR: 0.020000
Training Epoch: 14 [9472/9756]	Loss: 0.3204	LR: 0.020000
Training Epoch: 14 [9728/9756]	Loss: 0.3326	LR: 0.020000
Training Epoch: 14 [9756/9756]	Loss: 0.1978	LR: 0.020000
Epoch 14 - Average Train Loss: 0.3612, Train Accuracy: 0.8374
Epoch 14 training time consumed: 140.85s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0025, Accuracy: 0.7317, Time consumed:7.99s
Training Epoch: 15 [256/9756]	Loss: 0.3507	LR: 0.020000
Training Epoch: 15 [512/9756]	Loss: 0.3217	LR: 0.020000
Training Epoch: 15 [768/9756]	Loss: 0.3692	LR: 0.020000
Training Epoch: 15 [1024/9756]	Loss: 0.3056	LR: 0.020000
Training Epoch: 15 [1280/9756]	Loss: 0.3502	LR: 0.020000
Training Epoch: 15 [1536/9756]	Loss: 0.3477	LR: 0.020000
Training Epoch: 15 [1792/9756]	Loss: 0.2868	LR: 0.020000
Training Epoch: 15 [2048/9756]	Loss: 0.3130	LR: 0.020000
Training Epoch: 15 [2304/9756]	Loss: 0.3300	LR: 0.020000
Training Epoch: 15 [2560/9756]	Loss: 0.3457	LR: 0.020000
Training Epoch: 15 [2816/9756]	Loss: 0.3388	LR: 0.020000
Training Epoch: 15 [3072/9756]	Loss: 0.2868	LR: 0.020000
Training Epoch: 15 [3328/9756]	Loss: 0.3376	LR: 0.020000
Training Epoch: 15 [3584/9756]	Loss: 0.3290	LR: 0.020000
Training Epoch: 15 [3840/9756]	Loss: 0.3183	LR: 0.020000
Training Epoch: 15 [4096/9756]	Loss: 0.3131	LR: 0.020000
Training Epoch: 15 [4352/9756]	Loss: 0.2805	LR: 0.020000
Training Epoch: 15 [4608/9756]	Loss: 0.2937	LR: 0.020000
Training Epoch: 15 [4864/9756]	Loss: 0.3363	LR: 0.020000
Training Epoch: 15 [5120/9756]	Loss: 0.3331	LR: 0.020000
Training Epoch: 15 [5376/9756]	Loss: 0.2955	LR: 0.020000
Training Epoch: 15 [5632/9756]	Loss: 0.2891	LR: 0.020000
Training Epoch: 15 [5888/9756]	Loss: 0.3305	LR: 0.020000
Training Epoch: 15 [6144/9756]	Loss: 0.2983	LR: 0.020000
Training Epoch: 15 [6400/9756]	Loss: 0.3024	LR: 0.020000
Training Epoch: 15 [6656/9756]	Loss: 0.3464	LR: 0.020000
Training Epoch: 15 [6912/9756]	Loss: 0.3133	LR: 0.020000
Training Epoch: 15 [7168/9756]	Loss: 0.3184	LR: 0.020000
Training Epoch: 15 [7424/9756]	Loss: 0.2936	LR: 0.020000
Training Epoch: 15 [7680/9756]	Loss: 0.2959	LR: 0.020000
Training Epoch: 15 [7936/9756]	Loss: 0.2614	LR: 0.020000
Training Epoch: 15 [8192/9756]	Loss: 0.3192	LR: 0.020000
Training Epoch: 15 [8448/9756]	Loss: 0.3308	LR: 0.020000
Training Epoch: 15 [8704/9756]	Loss: 0.3440	LR: 0.020000
Training Epoch: 15 [8960/9756]	Loss: 0.2353	LR: 0.020000
Training Epoch: 15 [9216/9756]	Loss: 0.3251	LR: 0.020000
Training Epoch: 15 [9472/9756]	Loss: 0.3146	LR: 0.020000
Training Epoch: 15 [9728/9756]	Loss: 0.2828	LR: 0.020000
Training Epoch: 15 [9756/9756]	Loss: 0.2216	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3151, Train Accuracy: 0.8662
Epoch 15 training time consumed: 140.68s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0022, Accuracy: 0.7719, Time consumed:8.02s
Training Epoch: 16 [256/9756]	Loss: 0.2608	LR: 0.020000
Training Epoch: 16 [512/9756]	Loss: 0.3149	LR: 0.020000
Training Epoch: 16 [768/9756]	Loss: 0.3495	LR: 0.020000
Training Epoch: 16 [1024/9756]	Loss: 0.2763	LR: 0.020000
Training Epoch: 16 [1280/9756]	Loss: 0.2959	LR: 0.020000
Training Epoch: 16 [1536/9756]	Loss: 0.3566	LR: 0.020000
Training Epoch: 16 [1792/9756]	Loss: 0.2697	LR: 0.020000
Training Epoch: 16 [2048/9756]	Loss: 0.2399	LR: 0.020000
Training Epoch: 16 [2304/9756]	Loss: 0.2997	LR: 0.020000
Training Epoch: 16 [2560/9756]	Loss: 0.2412	LR: 0.020000
Training Epoch: 16 [2816/9756]	Loss: 0.3651	LR: 0.020000
Training Epoch: 16 [3072/9756]	Loss: 0.2363	LR: 0.020000
Training Epoch: 16 [3328/9756]	Loss: 0.3021	LR: 0.020000
Training Epoch: 16 [3584/9756]	Loss: 0.3114	LR: 0.020000
Training Epoch: 16 [3840/9756]	Loss: 0.3253	LR: 0.020000
Training Epoch: 16 [4096/9756]	Loss: 0.3684	LR: 0.020000
Training Epoch: 16 [4352/9756]	Loss: 0.3059	LR: 0.020000
Training Epoch: 16 [4608/9756]	Loss: 0.2992	LR: 0.020000
Training Epoch: 16 [4864/9756]	Loss: 0.2891	LR: 0.020000
Training Epoch: 16 [5120/9756]	Loss: 0.2731	LR: 0.020000
Training Epoch: 16 [5376/9756]	Loss: 0.2858	LR: 0.020000
Training Epoch: 16 [5632/9756]	Loss: 0.3416	LR: 0.020000
Training Epoch: 16 [5888/9756]	Loss: 0.3041	LR: 0.020000
Training Epoch: 16 [6144/9756]	Loss: 0.2433	LR: 0.020000
Training Epoch: 16 [6400/9756]	Loss: 0.2770	LR: 0.020000
Training Epoch: 16 [6656/9756]	Loss: 0.3267	LR: 0.020000
Training Epoch: 16 [6912/9756]	Loss: 0.2909	LR: 0.020000
Training Epoch: 16 [7168/9756]	Loss: 0.3209	LR: 0.020000
Training Epoch: 16 [7424/9756]	Loss: 0.2663	LR: 0.020000
Training Epoch: 16 [7680/9756]	Loss: 0.2775	LR: 0.020000
Training Epoch: 16 [7936/9756]	Loss: 0.2235	LR: 0.020000
Training Epoch: 16 [8192/9756]	Loss: 0.2652	LR: 0.020000
Training Epoch: 16 [8448/9756]	Loss: 0.2708	LR: 0.020000
Training Epoch: 16 [8704/9756]	Loss: 0.2854	LR: 0.020000
Training Epoch: 16 [8960/9756]	Loss: 0.2690	LR: 0.020000
Training Epoch: 16 [9216/9756]	Loss: 0.3162	LR: 0.020000
Training Epoch: 16 [9472/9756]	Loss: 0.2678	LR: 0.020000
Training Epoch: 16 [9728/9756]	Loss: 0.2576	LR: 0.020000
Training Epoch: 16 [9756/9756]	Loss: 0.1769	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2910, Train Accuracy: 0.8763
Epoch 16 training time consumed: 140.52s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0026, Accuracy: 0.7317, Time consumed:7.79s
Training Epoch: 17 [256/9756]	Loss: 0.2500	LR: 0.020000
Training Epoch: 17 [512/9756]	Loss: 0.2068	LR: 0.020000
Training Epoch: 17 [768/9756]	Loss: 0.2943	LR: 0.020000
Training Epoch: 17 [1024/9756]	Loss: 0.2697	LR: 0.020000
Training Epoch: 17 [1280/9756]	Loss: 0.2417	LR: 0.020000
Training Epoch: 17 [1536/9756]	Loss: 0.2802	LR: 0.020000
Training Epoch: 17 [1792/9756]	Loss: 0.2993	LR: 0.020000
Training Epoch: 17 [2048/9756]	Loss: 0.3143	LR: 0.020000
Training Epoch: 17 [2304/9756]	Loss: 0.2367	LR: 0.020000
Training Epoch: 17 [2560/9756]	Loss: 0.2503	LR: 0.020000
Training Epoch: 17 [2816/9756]	Loss: 0.2877	LR: 0.020000
Training Epoch: 17 [3072/9756]	Loss: 0.2572	LR: 0.020000
Training Epoch: 17 [3328/9756]	Loss: 0.2488	LR: 0.020000
Training Epoch: 17 [3584/9756]	Loss: 0.2474	LR: 0.020000
Training Epoch: 17 [3840/9756]	Loss: 0.2691	LR: 0.020000
Training Epoch: 17 [4096/9756]	Loss: 0.2419	LR: 0.020000
Training Epoch: 17 [4352/9756]	Loss: 0.3113	LR: 0.020000
Training Epoch: 17 [4608/9756]	Loss: 0.2209	LR: 0.020000
Training Epoch: 17 [4864/9756]	Loss: 0.2335	LR: 0.020000
Training Epoch: 17 [5120/9756]	Loss: 0.2803	LR: 0.020000
Training Epoch: 17 [5376/9756]	Loss: 0.2327	LR: 0.020000
Training Epoch: 17 [5632/9756]	Loss: 0.3245	LR: 0.020000
Training Epoch: 17 [5888/9756]	Loss: 0.2679	LR: 0.020000
Training Epoch: 17 [6144/9756]	Loss: 0.2436	LR: 0.020000
Training Epoch: 17 [6400/9756]	Loss: 0.2300	LR: 0.020000
Training Epoch: 17 [6656/9756]	Loss: 0.1935	LR: 0.020000
Training Epoch: 17 [6912/9756]	Loss: 0.2192	LR: 0.020000
Training Epoch: 17 [7168/9756]	Loss: 0.2387	LR: 0.020000
Training Epoch: 17 [7424/9756]	Loss: 0.2488	LR: 0.020000
Training Epoch: 17 [7680/9756]	Loss: 0.2166	LR: 0.020000
Training Epoch: 17 [7936/9756]	Loss: 0.2291	LR: 0.020000
Training Epoch: 17 [8192/9756]	Loss: 0.2633	LR: 0.020000
Training Epoch: 17 [8448/9756]	Loss: 0.2799	LR: 0.020000
Training Epoch: 17 [8704/9756]	Loss: 0.2707	LR: 0.020000
Training Epoch: 17 [8960/9756]	Loss: 0.2603	LR: 0.020000
Training Epoch: 17 [9216/9756]	Loss: 0.1705	LR: 0.020000
Training Epoch: 17 [9472/9756]	Loss: 0.2599	LR: 0.020000
Training Epoch: 17 [9728/9756]	Loss: 0.2487	LR: 0.020000
Training Epoch: 17 [9756/9756]	Loss: 0.2196	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2536, Train Accuracy: 0.8952
Epoch 17 training time consumed: 140.41s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0023, Accuracy: 0.8053, Time consumed:7.94s
Training Epoch: 18 [256/9756]	Loss: 0.2241	LR: 0.020000
Training Epoch: 18 [512/9756]	Loss: 0.3390	LR: 0.020000
Training Epoch: 18 [768/9756]	Loss: 0.2766	LR: 0.020000
Training Epoch: 18 [1024/9756]	Loss: 0.2441	LR: 0.020000
Training Epoch: 18 [1280/9756]	Loss: 0.2442	LR: 0.020000
Training Epoch: 18 [1536/9756]	Loss: 0.2380	LR: 0.020000
Training Epoch: 18 [1792/9756]	Loss: 0.2822	LR: 0.020000
Training Epoch: 18 [2048/9756]	Loss: 0.2592	LR: 0.020000
Training Epoch: 18 [2304/9756]	Loss: 0.2740	LR: 0.020000
Training Epoch: 18 [2560/9756]	Loss: 0.2724	LR: 0.020000
Training Epoch: 18 [2816/9756]	Loss: 0.2393	LR: 0.020000
Training Epoch: 18 [3072/9756]	Loss: 0.2031	LR: 0.020000
Training Epoch: 18 [3328/9756]	Loss: 0.2462	LR: 0.020000
Training Epoch: 18 [3584/9756]	Loss: 0.2052	LR: 0.020000
Training Epoch: 18 [3840/9756]	Loss: 0.2115	LR: 0.020000
Training Epoch: 18 [4096/9756]	Loss: 0.2032	LR: 0.020000
Training Epoch: 18 [4352/9756]	Loss: 0.1562	LR: 0.020000
Training Epoch: 18 [4608/9756]	Loss: 0.1880	LR: 0.020000
Training Epoch: 18 [4864/9756]	Loss: 0.2475	LR: 0.020000
Training Epoch: 18 [5120/9756]	Loss: 0.2572	LR: 0.020000
Training Epoch: 18 [5376/9756]	Loss: 0.2523	LR: 0.020000
Training Epoch: 18 [5632/9756]	Loss: 0.2506	LR: 0.020000
Training Epoch: 18 [5888/9756]	Loss: 0.2684	LR: 0.020000
Training Epoch: 18 [6144/9756]	Loss: 0.1870	LR: 0.020000
Training Epoch: 18 [6400/9756]	Loss: 0.2408	LR: 0.020000
Training Epoch: 18 [6656/9756]	Loss: 0.2552	LR: 0.020000
Training Epoch: 18 [6912/9756]	Loss: 0.2269	LR: 0.020000
Training Epoch: 18 [7168/9756]	Loss: 0.2339	LR: 0.020000
Training Epoch: 18 [7424/9756]	Loss: 0.2091	LR: 0.020000
Training Epoch: 18 [7680/9756]	Loss: 0.2175	LR: 0.020000
Training Epoch: 18 [7936/9756]	Loss: 0.2201	LR: 0.020000
Training Epoch: 18 [8192/9756]	Loss: 0.1975	LR: 0.020000
Training Epoch: 18 [8448/9756]	Loss: 0.2042	LR: 0.020000
Training Epoch: 18 [8704/9756]	Loss: 0.2197	LR: 0.020000
Training Epoch: 18 [8960/9756]	Loss: 0.1729	LR: 0.020000
Training Epoch: 18 [9216/9756]	Loss: 0.2244	LR: 0.020000
Training Epoch: 18 [9472/9756]	Loss: 0.2409	LR: 0.020000
Training Epoch: 18 [9728/9756]	Loss: 0.2395	LR: 0.020000
Training Epoch: 18 [9756/9756]	Loss: 0.0703	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2330, Train Accuracy: 0.9071
Epoch 18 training time consumed: 141.09s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0027, Accuracy: 0.7196, Time consumed:8.03s
Training Epoch: 19 [256/9756]	Loss: 0.2590	LR: 0.020000
Training Epoch: 19 [512/9756]	Loss: 0.2339	LR: 0.020000
Training Epoch: 19 [768/9756]	Loss: 0.2043	LR: 0.020000
Training Epoch: 19 [1024/9756]	Loss: 0.2548	LR: 0.020000
Training Epoch: 19 [1280/9756]	Loss: 0.1358	LR: 0.020000
Training Epoch: 19 [1536/9756]	Loss: 0.2895	LR: 0.020000
Training Epoch: 19 [1792/9756]	Loss: 0.1977	LR: 0.020000
Training Epoch: 19 [2048/9756]	Loss: 0.2292	LR: 0.020000
Training Epoch: 19 [2304/9756]	Loss: 0.1937	LR: 0.020000
Training Epoch: 19 [2560/9756]	Loss: 0.1833	LR: 0.020000
Training Epoch: 19 [2816/9756]	Loss: 0.1901	LR: 0.020000
Training Epoch: 19 [3072/9756]	Loss: 0.1892	LR: 0.020000
Training Epoch: 19 [3328/9756]	Loss: 0.2695	LR: 0.020000
Training Epoch: 19 [3584/9756]	Loss: 0.2652	LR: 0.020000
Training Epoch: 19 [3840/9756]	Loss: 0.1960	LR: 0.020000
Training Epoch: 19 [4096/9756]	Loss: 0.1928	LR: 0.020000
Training Epoch: 19 [4352/9756]	Loss: 0.2100	LR: 0.020000
Training Epoch: 19 [4608/9756]	Loss: 0.2609	LR: 0.020000
Training Epoch: 19 [4864/9756]	Loss: 0.1854	LR: 0.020000
Training Epoch: 19 [5120/9756]	Loss: 0.2249	LR: 0.020000
Training Epoch: 19 [5376/9756]	Loss: 0.1666	LR: 0.020000
Training Epoch: 19 [5632/9756]	Loss: 0.2238	LR: 0.020000
Training Epoch: 19 [5888/9756]	Loss: 0.2246	LR: 0.020000
Training Epoch: 19 [6144/9756]	Loss: 0.1930	LR: 0.020000
Training Epoch: 19 [6400/9756]	Loss: 0.1701	LR: 0.020000
Training Epoch: 19 [6656/9756]	Loss: 0.1989	LR: 0.020000
Training Epoch: 19 [6912/9756]	Loss: 0.1825	LR: 0.020000
Training Epoch: 19 [7168/9756]	Loss: 0.2308	LR: 0.020000
Training Epoch: 19 [7424/9756]	Loss: 0.1758	LR: 0.020000
Training Epoch: 19 [7680/9756]	Loss: 0.1640	LR: 0.020000
Training Epoch: 19 [7936/9756]	Loss: 0.2395	LR: 0.020000
Training Epoch: 19 [8192/9756]	Loss: 0.1356	LR: 0.020000
Training Epoch: 19 [8448/9756]	Loss: 0.1368	LR: 0.020000
Training Epoch: 19 [8704/9756]	Loss: 0.1847	LR: 0.020000
Training Epoch: 19 [8960/9756]	Loss: 0.2783	LR: 0.020000
Training Epoch: 19 [9216/9756]	Loss: 0.1563	LR: 0.020000
Training Epoch: 19 [9472/9756]	Loss: 0.2441	LR: 0.020000
Training Epoch: 19 [9728/9756]	Loss: 0.2508	LR: 0.020000
Training Epoch: 19 [9756/9756]	Loss: 0.2956	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2087, Train Accuracy: 0.9134
Epoch 19 training time consumed: 141.15s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0013, Accuracy: 0.8867, Time consumed:7.93s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-19-best.pth
Training Epoch: 20 [256/9756]	Loss: 0.2654	LR: 0.004000
Training Epoch: 20 [512/9756]	Loss: 0.1299	LR: 0.004000
Training Epoch: 20 [768/9756]	Loss: 0.1837	LR: 0.004000
Training Epoch: 20 [1024/9756]	Loss: 0.2337	LR: 0.004000
Training Epoch: 20 [1280/9756]	Loss: 0.1467	LR: 0.004000
Training Epoch: 20 [1536/9756]	Loss: 0.2167	LR: 0.004000
Training Epoch: 20 [1792/9756]	Loss: 0.1439	LR: 0.004000
Training Epoch: 20 [2048/9756]	Loss: 0.1661	LR: 0.004000
Training Epoch: 20 [2304/9756]	Loss: 0.1193	LR: 0.004000
Training Epoch: 20 [2560/9756]	Loss: 0.1511	LR: 0.004000
Training Epoch: 20 [2816/9756]	Loss: 0.1844	LR: 0.004000
Training Epoch: 20 [3072/9756]	Loss: 0.1466	LR: 0.004000
Training Epoch: 20 [3328/9756]	Loss: 0.1903	LR: 0.004000
Training Epoch: 20 [3584/9756]	Loss: 0.1862	LR: 0.004000
Training Epoch: 20 [3840/9756]	Loss: 0.2092	LR: 0.004000
Training Epoch: 20 [4096/9756]	Loss: 0.1795	LR: 0.004000
Training Epoch: 20 [4352/9756]	Loss: 0.1478	LR: 0.004000
Training Epoch: 20 [4608/9756]	Loss: 0.1851	LR: 0.004000
Training Epoch: 20 [4864/9756]	Loss: 0.1579	LR: 0.004000
Training Epoch: 20 [5120/9756]	Loss: 0.1365	LR: 0.004000
Training Epoch: 20 [5376/9756]	Loss: 0.1906	LR: 0.004000
Training Epoch: 20 [5632/9756]	Loss: 0.1314	LR: 0.004000
Training Epoch: 20 [5888/9756]	Loss: 0.1731	LR: 0.004000
Training Epoch: 20 [6144/9756]	Loss: 0.2123	LR: 0.004000
Training Epoch: 20 [6400/9756]	Loss: 0.2272	LR: 0.004000
Training Epoch: 20 [6656/9756]	Loss: 0.1639	LR: 0.004000
Training Epoch: 20 [6912/9756]	Loss: 0.2085	LR: 0.004000
Training Epoch: 20 [7168/9756]	Loss: 0.1773	LR: 0.004000
Training Epoch: 20 [7424/9756]	Loss: 0.1718	LR: 0.004000
Training Epoch: 20 [7680/9756]	Loss: 0.1743	LR: 0.004000
Training Epoch: 20 [7936/9756]	Loss: 0.1587	LR: 0.004000
Training Epoch: 20 [8192/9756]	Loss: 0.1879	LR: 0.004000
Training Epoch: 20 [8448/9756]	Loss: 0.1883	LR: 0.004000
Training Epoch: 20 [8704/9756]	Loss: 0.1893	LR: 0.004000
Training Epoch: 20 [8960/9756]	Loss: 0.1524	LR: 0.004000
Training Epoch: 20 [9216/9756]	Loss: 0.1711	LR: 0.004000
Training Epoch: 20 [9472/9756]	Loss: 0.1647	LR: 0.004000
Training Epoch: 20 [9728/9756]	Loss: 0.2050	LR: 0.004000
Training Epoch: 20 [9756/9756]	Loss: 0.0499	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1767, Train Accuracy: 0.9295
Epoch 20 training time consumed: 141.04s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0007, Accuracy: 0.9303, Time consumed:7.99s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-20-best.pth
Training Epoch: 21 [256/9756]	Loss: 0.1735	LR: 0.004000
Training Epoch: 21 [512/9756]	Loss: 0.1364	LR: 0.004000
Training Epoch: 21 [768/9756]	Loss: 0.1647	LR: 0.004000
Training Epoch: 21 [1024/9756]	Loss: 0.1932	LR: 0.004000
Training Epoch: 21 [1280/9756]	Loss: 0.1666	LR: 0.004000
Training Epoch: 21 [1536/9756]	Loss: 0.0875	LR: 0.004000
Training Epoch: 21 [1792/9756]	Loss: 0.1889	LR: 0.004000
Training Epoch: 21 [2048/9756]	Loss: 0.1485	LR: 0.004000
Training Epoch: 21 [2304/9756]	Loss: 0.1421	LR: 0.004000
Training Epoch: 21 [2560/9756]	Loss: 0.1608	LR: 0.004000
Training Epoch: 21 [2816/9756]	Loss: 0.1480	LR: 0.004000
Training Epoch: 21 [3072/9756]	Loss: 0.1820	LR: 0.004000
Training Epoch: 21 [3328/9756]	Loss: 0.1662	LR: 0.004000
Training Epoch: 21 [3584/9756]	Loss: 0.1213	LR: 0.004000
Training Epoch: 21 [3840/9756]	Loss: 0.1847	LR: 0.004000
Training Epoch: 21 [4096/9756]	Loss: 0.2171	LR: 0.004000
Training Epoch: 21 [4352/9756]	Loss: 0.1935	LR: 0.004000
Training Epoch: 21 [4608/9756]	Loss: 0.1832	LR: 0.004000
Training Epoch: 21 [4864/9756]	Loss: 0.0937	LR: 0.004000
Training Epoch: 21 [5120/9756]	Loss: 0.1681	LR: 0.004000
Training Epoch: 21 [5376/9756]	Loss: 0.1340	LR: 0.004000
Training Epoch: 21 [5632/9756]	Loss: 0.1757	LR: 0.004000
Training Epoch: 21 [5888/9756]	Loss: 0.2355	LR: 0.004000
Training Epoch: 21 [6144/9756]	Loss: 0.1628	LR: 0.004000
Training Epoch: 21 [6400/9756]	Loss: 0.2017	LR: 0.004000
Training Epoch: 21 [6656/9756]	Loss: 0.1382	LR: 0.004000
Training Epoch: 21 [6912/9756]	Loss: 0.2133	LR: 0.004000
Training Epoch: 21 [7168/9756]	Loss: 0.1704	LR: 0.004000
Training Epoch: 21 [7424/9756]	Loss: 0.1366	LR: 0.004000
Training Epoch: 21 [7680/9756]	Loss: 0.1908	LR: 0.004000
Training Epoch: 21 [7936/9756]	Loss: 0.2100	LR: 0.004000
Training Epoch: 21 [8192/9756]	Loss: 0.1636	LR: 0.004000
Training Epoch: 21 [8448/9756]	Loss: 0.1517	LR: 0.004000
Training Epoch: 21 [8704/9756]	Loss: 0.1749	LR: 0.004000
Training Epoch: 21 [8960/9756]	Loss: 0.1988	LR: 0.004000
Training Epoch: 21 [9216/9756]	Loss: 0.1538	LR: 0.004000
Training Epoch: 21 [9472/9756]	Loss: 0.1379	LR: 0.004000
Training Epoch: 21 [9728/9756]	Loss: 0.1286	LR: 0.004000
Training Epoch: 21 [9756/9756]	Loss: 0.1173	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1656, Train Accuracy: 0.9302
Epoch 21 training time consumed: 141.11s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0007, Accuracy: 0.9308, Time consumed:8.17s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-21-best.pth
Training Epoch: 22 [256/9756]	Loss: 0.1956	LR: 0.004000
Training Epoch: 22 [512/9756]	Loss: 0.1599	LR: 0.004000
Training Epoch: 22 [768/9756]	Loss: 0.1573	LR: 0.004000
Training Epoch: 22 [1024/9756]	Loss: 0.1479	LR: 0.004000
Training Epoch: 22 [1280/9756]	Loss: 0.1591	LR: 0.004000
Training Epoch: 22 [1536/9756]	Loss: 0.1369	LR: 0.004000
Training Epoch: 22 [1792/9756]	Loss: 0.1147	LR: 0.004000
Training Epoch: 22 [2048/9756]	Loss: 0.1603	LR: 0.004000
Training Epoch: 22 [2304/9756]	Loss: 0.1369	LR: 0.004000
Training Epoch: 22 [2560/9756]	Loss: 0.1315	LR: 0.004000
Training Epoch: 22 [2816/9756]	Loss: 0.2300	LR: 0.004000
Training Epoch: 22 [3072/9756]	Loss: 0.1994	LR: 0.004000
Training Epoch: 22 [3328/9756]	Loss: 0.1619	LR: 0.004000
Training Epoch: 22 [3584/9756]	Loss: 0.1970	LR: 0.004000
Training Epoch: 22 [3840/9756]	Loss: 0.1510	LR: 0.004000
Training Epoch: 22 [4096/9756]	Loss: 0.2072	LR: 0.004000
Training Epoch: 22 [4352/9756]	Loss: 0.2004	LR: 0.004000
Training Epoch: 22 [4608/9756]	Loss: 0.1641	LR: 0.004000
Training Epoch: 22 [4864/9756]	Loss: 0.1495	LR: 0.004000
Training Epoch: 22 [5120/9756]	Loss: 0.1694	LR: 0.004000
Training Epoch: 22 [5376/9756]	Loss: 0.1540	LR: 0.004000
Training Epoch: 22 [5632/9756]	Loss: 0.1723	LR: 0.004000
Training Epoch: 22 [5888/9756]	Loss: 0.1699	LR: 0.004000
Training Epoch: 22 [6144/9756]	Loss: 0.1409	LR: 0.004000
Training Epoch: 22 [6400/9756]	Loss: 0.1721	LR: 0.004000
Training Epoch: 22 [6656/9756]	Loss: 0.2407	LR: 0.004000
Training Epoch: 22 [6912/9756]	Loss: 0.1366	LR: 0.004000
Training Epoch: 22 [7168/9756]	Loss: 0.1265	LR: 0.004000
Training Epoch: 22 [7424/9756]	Loss: 0.1719	LR: 0.004000
Training Epoch: 22 [7680/9756]	Loss: 0.1991	LR: 0.004000
Training Epoch: 22 [7936/9756]	Loss: 0.0978	LR: 0.004000
Training Epoch: 22 [8192/9756]	Loss: 0.1441	LR: 0.004000
Training Epoch: 22 [8448/9756]	Loss: 0.1207	LR: 0.004000
Training Epoch: 22 [8704/9756]	Loss: 0.1387	LR: 0.004000
Training Epoch: 22 [8960/9756]	Loss: 0.1777	LR: 0.004000
Training Epoch: 22 [9216/9756]	Loss: 0.1648	LR: 0.004000
Training Epoch: 22 [9472/9756]	Loss: 0.1642	LR: 0.004000
Training Epoch: 22 [9728/9756]	Loss: 0.1869	LR: 0.004000
Training Epoch: 22 [9756/9756]	Loss: 0.1247	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1633, Train Accuracy: 0.9328
Epoch 22 training time consumed: 140.97s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0007, Accuracy: 0.9317, Time consumed:8.07s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-22-best.pth
Training Epoch: 23 [256/9756]	Loss: 0.1359	LR: 0.004000
Training Epoch: 23 [512/9756]	Loss: 0.1670	LR: 0.004000
Training Epoch: 23 [768/9756]	Loss: 0.1208	LR: 0.004000
Training Epoch: 23 [1024/9756]	Loss: 0.1838	LR: 0.004000
Training Epoch: 23 [1280/9756]	Loss: 0.2005	LR: 0.004000
Training Epoch: 23 [1536/9756]	Loss: 0.1587	LR: 0.004000
Training Epoch: 23 [1792/9756]	Loss: 0.1699	LR: 0.004000
Training Epoch: 23 [2048/9756]	Loss: 0.1658	LR: 0.004000
Training Epoch: 23 [2304/9756]	Loss: 0.1640	LR: 0.004000
Training Epoch: 23 [2560/9756]	Loss: 0.1613	LR: 0.004000
Training Epoch: 23 [2816/9756]	Loss: 0.1440	LR: 0.004000
Training Epoch: 23 [3072/9756]	Loss: 0.1967	LR: 0.004000
Training Epoch: 23 [3328/9756]	Loss: 0.1417	LR: 0.004000
Training Epoch: 23 [3584/9756]	Loss: 0.1632	LR: 0.004000
Training Epoch: 23 [3840/9756]	Loss: 0.1550	LR: 0.004000
Training Epoch: 23 [4096/9756]	Loss: 0.1325	LR: 0.004000
Training Epoch: 23 [4352/9756]	Loss: 0.1856	LR: 0.004000
Training Epoch: 23 [4608/9756]	Loss: 0.1282	LR: 0.004000
Training Epoch: 23 [4864/9756]	Loss: 0.1279	LR: 0.004000
Training Epoch: 23 [5120/9756]	Loss: 0.1306	LR: 0.004000
Training Epoch: 23 [5376/9756]	Loss: 0.1720	LR: 0.004000
Training Epoch: 23 [5632/9756]	Loss: 0.1439	LR: 0.004000
Training Epoch: 23 [5888/9756]	Loss: 0.1367	LR: 0.004000
Training Epoch: 23 [6144/9756]	Loss: 0.1783	LR: 0.004000
Training Epoch: 23 [6400/9756]	Loss: 0.1571	LR: 0.004000
Training Epoch: 23 [6656/9756]	Loss: 0.1805	LR: 0.004000
Training Epoch: 23 [6912/9756]	Loss: 0.1847	LR: 0.004000
Training Epoch: 23 [7168/9756]	Loss: 0.1583	LR: 0.004000
Training Epoch: 23 [7424/9756]	Loss: 0.2148	LR: 0.004000
Training Epoch: 23 [7680/9756]	Loss: 0.0987	LR: 0.004000
Training Epoch: 23 [7936/9756]	Loss: 0.1287	LR: 0.004000
Training Epoch: 23 [8192/9756]	Loss: 0.1804	LR: 0.004000
Training Epoch: 23 [8448/9756]	Loss: 0.1396	LR: 0.004000
Training Epoch: 23 [8704/9756]	Loss: 0.1669	LR: 0.004000
Training Epoch: 23 [8960/9756]	Loss: 0.1695	LR: 0.004000
Training Epoch: 23 [9216/9756]	Loss: 0.1680	LR: 0.004000
Training Epoch: 23 [9472/9756]	Loss: 0.1371	LR: 0.004000
Training Epoch: 23 [9728/9756]	Loss: 0.1684	LR: 0.004000
Training Epoch: 23 [9756/9756]	Loss: 0.1265	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1582, Train Accuracy: 0.9345
Epoch 23 training time consumed: 141.14s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9375, Time consumed:7.83s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-23-best.pth
Training Epoch: 24 [256/9756]	Loss: 0.1923	LR: 0.004000
Training Epoch: 24 [512/9756]	Loss: 0.1163	LR: 0.004000
Training Epoch: 24 [768/9756]	Loss: 0.1655	LR: 0.004000
Training Epoch: 24 [1024/9756]	Loss: 0.1258	LR: 0.004000
Training Epoch: 24 [1280/9756]	Loss: 0.0919	LR: 0.004000
Training Epoch: 24 [1536/9756]	Loss: 0.1495	LR: 0.004000
Training Epoch: 24 [1792/9756]	Loss: 0.1929	LR: 0.004000
Training Epoch: 24 [2048/9756]	Loss: 0.2150	LR: 0.004000
Training Epoch: 24 [2304/9756]	Loss: 0.1483	LR: 0.004000
Training Epoch: 24 [2560/9756]	Loss: 0.1271	LR: 0.004000
Training Epoch: 24 [2816/9756]	Loss: 0.1403	LR: 0.004000
Training Epoch: 24 [3072/9756]	Loss: 0.1539	LR: 0.004000
Training Epoch: 24 [3328/9756]	Loss: 0.1560	LR: 0.004000
Training Epoch: 24 [3584/9756]	Loss: 0.1819	LR: 0.004000
Training Epoch: 24 [3840/9756]	Loss: 0.1419	LR: 0.004000
Training Epoch: 24 [4096/9756]	Loss: 0.1716	LR: 0.004000
Training Epoch: 24 [4352/9756]	Loss: 0.2052	LR: 0.004000
Training Epoch: 24 [4608/9756]	Loss: 0.1845	LR: 0.004000
Training Epoch: 24 [4864/9756]	Loss: 0.1531	LR: 0.004000
Training Epoch: 24 [5120/9756]	Loss: 0.1546	LR: 0.004000
Training Epoch: 24 [5376/9756]	Loss: 0.1346	LR: 0.004000
Training Epoch: 24 [5632/9756]	Loss: 0.1798	LR: 0.004000
Training Epoch: 24 [5888/9756]	Loss: 0.1425	LR: 0.004000
Training Epoch: 24 [6144/9756]	Loss: 0.1444	LR: 0.004000
Training Epoch: 24 [6400/9756]	Loss: 0.1583	LR: 0.004000
Training Epoch: 24 [6656/9756]	Loss: 0.1134	LR: 0.004000
Training Epoch: 24 [6912/9756]	Loss: 0.1393	LR: 0.004000
Training Epoch: 24 [7168/9756]	Loss: 0.1792	LR: 0.004000
Training Epoch: 24 [7424/9756]	Loss: 0.1746	LR: 0.004000
Training Epoch: 24 [7680/9756]	Loss: 0.1720	LR: 0.004000
Training Epoch: 24 [7936/9756]	Loss: 0.0969	LR: 0.004000
Training Epoch: 24 [8192/9756]	Loss: 0.1129	LR: 0.004000
Training Epoch: 24 [8448/9756]	Loss: 0.1304	LR: 0.004000
Training Epoch: 24 [8704/9756]	Loss: 0.1952	LR: 0.004000
Training Epoch: 24 [8960/9756]	Loss: 0.1423	LR: 0.004000
Training Epoch: 24 [9216/9756]	Loss: 0.1725	LR: 0.004000
Training Epoch: 24 [9472/9756]	Loss: 0.1920	LR: 0.004000
Training Epoch: 24 [9728/9756]	Loss: 0.1740	LR: 0.004000
Training Epoch: 24 [9756/9756]	Loss: 0.1296	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1558, Train Accuracy: 0.9355
Epoch 24 training time consumed: 140.80s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0007, Accuracy: 0.9293, Time consumed:7.88s
Training Epoch: 25 [256/9756]	Loss: 0.1414	LR: 0.004000
Training Epoch: 25 [512/9756]	Loss: 0.1356	LR: 0.004000
Training Epoch: 25 [768/9756]	Loss: 0.1031	LR: 0.004000
Training Epoch: 25 [1024/9756]	Loss: 0.1788	LR: 0.004000
Training Epoch: 25 [1280/9756]	Loss: 0.1754	LR: 0.004000
Training Epoch: 25 [1536/9756]	Loss: 0.1586	LR: 0.004000
Training Epoch: 25 [1792/9756]	Loss: 0.1870	LR: 0.004000
Training Epoch: 25 [2048/9756]	Loss: 0.1574	LR: 0.004000
Training Epoch: 25 [2304/9756]	Loss: 0.1226	LR: 0.004000
Training Epoch: 25 [2560/9756]	Loss: 0.1510	LR: 0.004000
Training Epoch: 25 [2816/9756]	Loss: 0.1600	LR: 0.004000
Training Epoch: 25 [3072/9756]	Loss: 0.1222	LR: 0.004000
Training Epoch: 25 [3328/9756]	Loss: 0.1972	LR: 0.004000
Training Epoch: 25 [3584/9756]	Loss: 0.1820	LR: 0.004000
Training Epoch: 25 [3840/9756]	Loss: 0.2162	LR: 0.004000
Training Epoch: 25 [4096/9756]	Loss: 0.2022	LR: 0.004000
Training Epoch: 25 [4352/9756]	Loss: 0.1044	LR: 0.004000
Training Epoch: 25 [4608/9756]	Loss: 0.1630	LR: 0.004000
Training Epoch: 25 [4864/9756]	Loss: 0.1275	LR: 0.004000
Training Epoch: 25 [5120/9756]	Loss: 0.1343	LR: 0.004000
Training Epoch: 25 [5376/9756]	Loss: 0.1378	LR: 0.004000
Training Epoch: 25 [5632/9756]	Loss: 0.1333	LR: 0.004000
Training Epoch: 25 [5888/9756]	Loss: 0.1411	LR: 0.004000
Training Epoch: 25 [6144/9756]	Loss: 0.1639	LR: 0.004000
Training Epoch: 25 [6400/9756]	Loss: 0.1229	LR: 0.004000
Training Epoch: 25 [6656/9756]	Loss: 0.1186	LR: 0.004000
Training Epoch: 25 [6912/9756]	Loss: 0.1810	LR: 0.004000
Training Epoch: 25 [7168/9756]	Loss: 0.1806	LR: 0.004000
Training Epoch: 25 [7424/9756]	Loss: 0.1957	LR: 0.004000
Training Epoch: 25 [7680/9756]	Loss: 0.1086	LR: 0.004000
Training Epoch: 25 [7936/9756]	Loss: 0.1539	LR: 0.004000
Training Epoch: 25 [8192/9756]	Loss: 0.1531	LR: 0.004000
Training Epoch: 25 [8448/9756]	Loss: 0.1108	LR: 0.004000
Training Epoch: 25 [8704/9756]	Loss: 0.1129	LR: 0.004000
Training Epoch: 25 [8960/9756]	Loss: 0.1635	LR: 0.004000
Training Epoch: 25 [9216/9756]	Loss: 0.1463	LR: 0.004000
Training Epoch: 25 [9472/9756]	Loss: 0.1687	LR: 0.004000
Training Epoch: 25 [9728/9756]	Loss: 0.1257	LR: 0.004000
Training Epoch: 25 [9756/9756]	Loss: 0.3632	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1516, Train Accuracy: 0.9370
Epoch 25 training time consumed: 140.92s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0007, Accuracy: 0.9308, Time consumed:8.03s
Training Epoch: 26 [256/9756]	Loss: 0.1651	LR: 0.004000
Training Epoch: 26 [512/9756]	Loss: 0.1372	LR: 0.004000
Training Epoch: 26 [768/9756]	Loss: 0.2065	LR: 0.004000
Training Epoch: 26 [1024/9756]	Loss: 0.1497	LR: 0.004000
Training Epoch: 26 [1280/9756]	Loss: 0.2033	LR: 0.004000
Training Epoch: 26 [1536/9756]	Loss: 0.1691	LR: 0.004000
Training Epoch: 26 [1792/9756]	Loss: 0.2144	LR: 0.004000
Training Epoch: 26 [2048/9756]	Loss: 0.1557	LR: 0.004000
Training Epoch: 26 [2304/9756]	Loss: 0.1418	LR: 0.004000
Training Epoch: 26 [2560/9756]	Loss: 0.1634	LR: 0.004000
Training Epoch: 26 [2816/9756]	Loss: 0.2447	LR: 0.004000
Training Epoch: 26 [3072/9756]	Loss: 0.2210	LR: 0.004000
Training Epoch: 26 [3328/9756]	Loss: 0.1950	LR: 0.004000
Training Epoch: 26 [3584/9756]	Loss: 0.1655	LR: 0.004000
Training Epoch: 26 [3840/9756]	Loss: 0.1609	LR: 0.004000
Training Epoch: 26 [4096/9756]	Loss: 0.1399	LR: 0.004000
Training Epoch: 26 [4352/9756]	Loss: 0.1389	LR: 0.004000
Training Epoch: 26 [4608/9756]	Loss: 0.1547	LR: 0.004000
Training Epoch: 26 [4864/9756]	Loss: 0.1270	LR: 0.004000
Training Epoch: 26 [5120/9756]	Loss: 0.1081	LR: 0.004000
Training Epoch: 26 [5376/9756]	Loss: 0.1796	LR: 0.004000
Training Epoch: 26 [5632/9756]	Loss: 0.1337	LR: 0.004000
Training Epoch: 26 [5888/9756]	Loss: 0.1319	LR: 0.004000
Training Epoch: 26 [6144/9756]	Loss: 0.1548	LR: 0.004000
Training Epoch: 26 [6400/9756]	Loss: 0.1774	LR: 0.004000
Training Epoch: 26 [6656/9756]	Loss: 0.1613	LR: 0.004000
Training Epoch: 26 [6912/9756]	Loss: 0.1523	LR: 0.004000
Training Epoch: 26 [7168/9756]	Loss: 0.1256	LR: 0.004000
Training Epoch: 26 [7424/9756]	Loss: 0.1280	LR: 0.004000
Training Epoch: 26 [7680/9756]	Loss: 0.1097	LR: 0.004000
Training Epoch: 26 [7936/9756]	Loss: 0.1707	LR: 0.004000
Training Epoch: 26 [8192/9756]	Loss: 0.1483	LR: 0.004000
Training Epoch: 26 [8448/9756]	Loss: 0.1444	LR: 0.004000
Training Epoch: 26 [8704/9756]	Loss: 0.1498	LR: 0.004000
Training Epoch: 26 [8960/9756]	Loss: 0.1148	LR: 0.004000
Training Epoch: 26 [9216/9756]	Loss: 0.1355	LR: 0.004000
Training Epoch: 26 [9472/9756]	Loss: 0.1128	LR: 0.004000
Training Epoch: 26 [9728/9756]	Loss: 0.1703	LR: 0.004000
Training Epoch: 26 [9756/9756]	Loss: 0.1994	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1570, Train Accuracy: 0.9336
Epoch 26 training time consumed: 140.49s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9380, Time consumed:8.03s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-26-best.pth
Training Epoch: 27 [256/9756]	Loss: 0.1260	LR: 0.004000
Training Epoch: 27 [512/9756]	Loss: 0.1382	LR: 0.004000
Training Epoch: 27 [768/9756]	Loss: 0.1342	LR: 0.004000
Training Epoch: 27 [1024/9756]	Loss: 0.1434	LR: 0.004000
Training Epoch: 27 [1280/9756]	Loss: 0.1276	LR: 0.004000
Training Epoch: 27 [1536/9756]	Loss: 0.1536	LR: 0.004000
Training Epoch: 27 [1792/9756]	Loss: 0.1435	LR: 0.004000
Training Epoch: 27 [2048/9756]	Loss: 0.1185	LR: 0.004000
Training Epoch: 27 [2304/9756]	Loss: 0.1524	LR: 0.004000
Training Epoch: 27 [2560/9756]	Loss: 0.1243	LR: 0.004000
Training Epoch: 27 [2816/9756]	Loss: 0.1365	LR: 0.004000
Training Epoch: 27 [3072/9756]	Loss: 0.1256	LR: 0.004000
Training Epoch: 27 [3328/9756]	Loss: 0.1416	LR: 0.004000
Training Epoch: 27 [3584/9756]	Loss: 0.1446	LR: 0.004000
Training Epoch: 27 [3840/9756]	Loss: 0.1320	LR: 0.004000
Training Epoch: 27 [4096/9756]	Loss: 0.1969	LR: 0.004000
Training Epoch: 27 [4352/9756]	Loss: 0.1461	LR: 0.004000
Training Epoch: 27 [4608/9756]	Loss: 0.0949	LR: 0.004000
Training Epoch: 27 [4864/9756]	Loss: 0.1497	LR: 0.004000
Training Epoch: 27 [5120/9756]	Loss: 0.1891	LR: 0.004000
Training Epoch: 27 [5376/9756]	Loss: 0.1432	LR: 0.004000
Training Epoch: 27 [5632/9756]	Loss: 0.1434	LR: 0.004000
Training Epoch: 27 [5888/9756]	Loss: 0.1318	LR: 0.004000
Training Epoch: 27 [6144/9756]	Loss: 0.1408	LR: 0.004000
Training Epoch: 27 [6400/9756]	Loss: 0.1481	LR: 0.004000
Training Epoch: 27 [6656/9756]	Loss: 0.1358	LR: 0.004000
Training Epoch: 27 [6912/9756]	Loss: 0.1202	LR: 0.004000
Training Epoch: 27 [7168/9756]	Loss: 0.1413	LR: 0.004000
Training Epoch: 27 [7424/9756]	Loss: 0.1471	LR: 0.004000
Training Epoch: 27 [7680/9756]	Loss: 0.1025	LR: 0.004000
Training Epoch: 27 [7936/9756]	Loss: 0.1293	LR: 0.004000
Training Epoch: 27 [8192/9756]	Loss: 0.1814	LR: 0.004000
Training Epoch: 27 [8448/9756]	Loss: 0.1474	LR: 0.004000
Training Epoch: 27 [8704/9756]	Loss: 0.1905	LR: 0.004000
Training Epoch: 27 [8960/9756]	Loss: 0.1459	LR: 0.004000
Training Epoch: 27 [9216/9756]	Loss: 0.2008	LR: 0.004000
Training Epoch: 27 [9472/9756]	Loss: 0.1529	LR: 0.004000
Training Epoch: 27 [9728/9756]	Loss: 0.1514	LR: 0.004000
Training Epoch: 27 [9756/9756]	Loss: 0.0355	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1437, Train Accuracy: 0.9410
Epoch 27 training time consumed: 140.61s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0007, Accuracy: 0.9264, Time consumed:7.97s
Training Epoch: 28 [256/9756]	Loss: 0.1628	LR: 0.004000
Training Epoch: 28 [512/9756]	Loss: 0.1237	LR: 0.004000
Training Epoch: 28 [768/9756]	Loss: 0.1067	LR: 0.004000
Training Epoch: 28 [1024/9756]	Loss: 0.1355	LR: 0.004000
Training Epoch: 28 [1280/9756]	Loss: 0.1386	LR: 0.004000
Training Epoch: 28 [1536/9756]	Loss: 0.1024	LR: 0.004000
Training Epoch: 28 [1792/9756]	Loss: 0.0905	LR: 0.004000
Training Epoch: 28 [2048/9756]	Loss: 0.1671	LR: 0.004000
Training Epoch: 28 [2304/9756]	Loss: 0.1939	LR: 0.004000
Training Epoch: 28 [2560/9756]	Loss: 0.1191	LR: 0.004000
Training Epoch: 28 [2816/9756]	Loss: 0.1491	LR: 0.004000
Training Epoch: 28 [3072/9756]	Loss: 0.1220	LR: 0.004000
Training Epoch: 28 [3328/9756]	Loss: 0.1440	LR: 0.004000
Training Epoch: 28 [3584/9756]	Loss: 0.1467	LR: 0.004000
Training Epoch: 28 [3840/9756]	Loss: 0.1592	LR: 0.004000
Training Epoch: 28 [4096/9756]	Loss: 0.1358	LR: 0.004000
Training Epoch: 28 [4352/9756]	Loss: 0.1415	LR: 0.004000
Training Epoch: 28 [4608/9756]	Loss: 0.1217	LR: 0.004000
Training Epoch: 28 [4864/9756]	Loss: 0.1900	LR: 0.004000
Training Epoch: 28 [5120/9756]	Loss: 0.1230	LR: 0.004000
Training Epoch: 28 [5376/9756]	Loss: 0.1453	LR: 0.004000
Training Epoch: 28 [5632/9756]	Loss: 0.1687	LR: 0.004000
Training Epoch: 28 [5888/9756]	Loss: 0.1276	LR: 0.004000
Training Epoch: 28 [6144/9756]	Loss: 0.1548	LR: 0.004000
Training Epoch: 28 [6400/9756]	Loss: 0.1692	LR: 0.004000
Training Epoch: 28 [6656/9756]	Loss: 0.1921	LR: 0.004000
Training Epoch: 28 [6912/9756]	Loss: 0.1676	LR: 0.004000
Training Epoch: 28 [7168/9756]	Loss: 0.1385	LR: 0.004000
Training Epoch: 28 [7424/9756]	Loss: 0.1906	LR: 0.004000
Training Epoch: 28 [7680/9756]	Loss: 0.1482	LR: 0.004000
Training Epoch: 28 [7936/9756]	Loss: 0.1412	LR: 0.004000
Training Epoch: 28 [8192/9756]	Loss: 0.0978	LR: 0.004000
Training Epoch: 28 [8448/9756]	Loss: 0.1219	LR: 0.004000
Training Epoch: 28 [8704/9756]	Loss: 0.1782	LR: 0.004000
Training Epoch: 28 [8960/9756]	Loss: 0.1518	LR: 0.004000
Training Epoch: 28 [9216/9756]	Loss: 0.1360	LR: 0.004000
Training Epoch: 28 [9472/9756]	Loss: 0.1423	LR: 0.004000
Training Epoch: 28 [9728/9756]	Loss: 0.1302	LR: 0.004000
Training Epoch: 28 [9756/9756]	Loss: 0.0632	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1439, Train Accuracy: 0.9395
Epoch 28 training time consumed: 140.52s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0006, Accuracy: 0.9400, Time consumed:7.87s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-28-best.pth
Training Epoch: 29 [256/9756]	Loss: 0.0944	LR: 0.004000
Training Epoch: 29 [512/9756]	Loss: 0.1660	LR: 0.004000
Training Epoch: 29 [768/9756]	Loss: 0.1211	LR: 0.004000
Training Epoch: 29 [1024/9756]	Loss: 0.1576	LR: 0.004000
Training Epoch: 29 [1280/9756]	Loss: 0.1071	LR: 0.004000
Training Epoch: 29 [1536/9756]	Loss: 0.1594	LR: 0.004000
Training Epoch: 29 [1792/9756]	Loss: 0.1483	LR: 0.004000
Training Epoch: 29 [2048/9756]	Loss: 0.1597	LR: 0.004000
Training Epoch: 29 [2304/9756]	Loss: 0.1257	LR: 0.004000
Training Epoch: 29 [2560/9756]	Loss: 0.0862	LR: 0.004000
Training Epoch: 29 [2816/9756]	Loss: 0.1500	LR: 0.004000
Training Epoch: 29 [3072/9756]	Loss: 0.1464	LR: 0.004000
Training Epoch: 29 [3328/9756]	Loss: 0.1226	LR: 0.004000
Training Epoch: 29 [3584/9756]	Loss: 0.1217	LR: 0.004000
Training Epoch: 29 [3840/9756]	Loss: 0.1398	LR: 0.004000
Training Epoch: 29 [4096/9756]	Loss: 0.1121	LR: 0.004000
Training Epoch: 29 [4352/9756]	Loss: 0.1275	LR: 0.004000
Training Epoch: 29 [4608/9756]	Loss: 0.1689	LR: 0.004000
Training Epoch: 29 [4864/9756]	Loss: 0.1147	LR: 0.004000
Training Epoch: 29 [5120/9756]	Loss: 0.1463	LR: 0.004000
Training Epoch: 29 [5376/9756]	Loss: 0.1166	LR: 0.004000
Training Epoch: 29 [5632/9756]	Loss: 0.1591	LR: 0.004000
Training Epoch: 29 [5888/9756]	Loss: 0.1303	LR: 0.004000
Training Epoch: 29 [6144/9756]	Loss: 0.1530	LR: 0.004000
Training Epoch: 29 [6400/9756]	Loss: 0.1815	LR: 0.004000
Training Epoch: 29 [6656/9756]	Loss: 0.1458	LR: 0.004000
Training Epoch: 29 [6912/9756]	Loss: 0.1417	LR: 0.004000
Training Epoch: 29 [7168/9756]	Loss: 0.1338	LR: 0.004000
Training Epoch: 29 [7424/9756]	Loss: 0.1330	LR: 0.004000
Training Epoch: 29 [7680/9756]	Loss: 0.2009	LR: 0.004000
Training Epoch: 29 [7936/9756]	Loss: 0.1448	LR: 0.004000
Training Epoch: 29 [8192/9756]	Loss: 0.1568	LR: 0.004000
Training Epoch: 29 [8448/9756]	Loss: 0.1774	LR: 0.004000
Training Epoch: 29 [8704/9756]	Loss: 0.1414	LR: 0.004000
Training Epoch: 29 [8960/9756]	Loss: 0.0965	LR: 0.004000
Training Epoch: 29 [9216/9756]	Loss: 0.1435	LR: 0.004000
Training Epoch: 29 [9472/9756]	Loss: 0.1543	LR: 0.004000
Training Epoch: 29 [9728/9756]	Loss: 0.1377	LR: 0.004000
Training Epoch: 29 [9756/9756]	Loss: 0.1464	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1401, Train Accuracy: 0.9431
Epoch 29 training time consumed: 140.90s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0006, Accuracy: 0.9419, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_03h_30m_56s/ResNet18-MUCAC-seed5-ret25-29-best.pth
Training Epoch: 30 [256/9756]	Loss: 0.1098	LR: 0.004000
Training Epoch: 30 [512/9756]	Loss: 0.1635	LR: 0.004000
Training Epoch: 30 [768/9756]	Loss: 0.1293	LR: 0.004000
Training Epoch: 30 [1024/9756]	Loss: 0.1068	LR: 0.004000
Training Epoch: 30 [1280/9756]	Loss: 0.1681	LR: 0.004000
Training Epoch: 30 [1536/9756]	Loss: 0.1084	LR: 0.004000
Training Epoch: 30 [1792/9756]	Loss: 0.1123	LR: 0.004000
Training Epoch: 30 [2048/9756]	Loss: 0.1689	LR: 0.004000
Training Epoch: 30 [2304/9756]	Loss: 0.1362	LR: 0.004000
Training Epoch: 30 [2560/9756]	Loss: 0.1486	LR: 0.004000
Training Epoch: 30 [2816/9756]	Loss: 0.1560	LR: 0.004000
Training Epoch: 30 [3072/9756]	Loss: 0.1458	LR: 0.004000
Training Epoch: 30 [3328/9756]	Loss: 0.1259	LR: 0.004000
Training Epoch: 30 [3584/9756]	Loss: 0.1405	LR: 0.004000
Training Epoch: 30 [3840/9756]	Loss: 0.1445	LR: 0.004000
Training Epoch: 30 [4096/9756]	Loss: 0.1664	LR: 0.004000
Training Epoch: 30 [4352/9756]	Loss: 0.1185	LR: 0.004000
Training Epoch: 30 [4608/9756]	Loss: 0.1527	LR: 0.004000
Training Epoch: 30 [4864/9756]	Loss: 0.1664	LR: 0.004000
Training Epoch: 30 [5120/9756]	Loss: 0.1058	LR: 0.004000
Training Epoch: 30 [5376/9756]	Loss: 0.1362	LR: 0.004000
Training Epoch: 30 [5632/9756]	Loss: 0.1409	LR: 0.004000
Training Epoch: 30 [5888/9756]	Loss: 0.1042	LR: 0.004000
Training Epoch: 30 [6144/9756]	Loss: 0.1306	LR: 0.004000
Training Epoch: 30 [6400/9756]	Loss: 0.1521	LR: 0.004000
Training Epoch: 30 [6656/9756]	Loss: 0.1255	LR: 0.004000
Training Epoch: 30 [6912/9756]	Loss: 0.0895	LR: 0.004000
Training Epoch: 30 [7168/9756]	Loss: 0.1400	LR: 0.004000
Training Epoch: 30 [7424/9756]	Loss: 0.1205	LR: 0.004000
Training Epoch: 30 [7680/9756]	Loss: 0.0701	LR: 0.004000
Training Epoch: 30 [7936/9756]	Loss: 0.1547	LR: 0.004000
Training Epoch: 30 [8192/9756]	Loss: 0.1504	LR: 0.004000
Training Epoch: 30 [8448/9756]	Loss: 0.1810	LR: 0.004000
Training Epoch: 30 [8704/9756]	Loss: 0.1674	LR: 0.004000
Training Epoch: 30 [8960/9756]	Loss: 0.1778	LR: 0.004000
Training Epoch: 30 [9216/9756]	Loss: 0.1329	LR: 0.004000
Training Epoch: 30 [9472/9756]	Loss: 0.1232	LR: 0.004000
Training Epoch: 30 [9728/9756]	Loss: 0.1499	LR: 0.004000
Training Epoch: 30 [9756/9756]	Loss: 0.1440	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1374, Train Accuracy: 0.9444
Epoch 30 training time consumed: 140.92s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9366, Time consumed:7.95s
Training Epoch: 31 [256/9756]	Loss: 0.1111	LR: 0.004000
Training Epoch: 31 [512/9756]	Loss: 0.1243	LR: 0.004000
Training Epoch: 31 [768/9756]	Loss: 0.1101	LR: 0.004000
Training Epoch: 31 [1024/9756]	Loss: 0.1309	LR: 0.004000
Training Epoch: 31 [1280/9756]	Loss: 0.1373	LR: 0.004000
Training Epoch: 31 [1536/9756]	Loss: 0.1221	LR: 0.004000
Training Epoch: 31 [1792/9756]	Loss: 0.1481	LR: 0.004000
Training Epoch: 31 [2048/9756]	Loss: 0.1393	LR: 0.004000
Training Epoch: 31 [2304/9756]	Loss: 0.1020	LR: 0.004000
Training Epoch: 31 [2560/9756]	Loss: 0.1646	LR: 0.004000
Training Epoch: 31 [2816/9756]	Loss: 0.1902	LR: 0.004000
Training Epoch: 31 [3072/9756]	Loss: 0.1169	LR: 0.004000
Training Epoch: 31 [3328/9756]	Loss: 0.1483	LR: 0.004000
Training Epoch: 31 [3584/9756]	Loss: 0.1287	LR: 0.004000
Training Epoch: 31 [3840/9756]	Loss: 0.1266	LR: 0.004000
Training Epoch: 31 [4096/9756]	Loss: 0.1396	LR: 0.004000
Training Epoch: 31 [4352/9756]	Loss: 0.1370	LR: 0.004000
Training Epoch: 31 [4608/9756]	Loss: 0.1209	LR: 0.004000
Training Epoch: 31 [4864/9756]	Loss: 0.1132	LR: 0.004000
Training Epoch: 31 [5120/9756]	Loss: 0.1536	LR: 0.004000
Training Epoch: 31 [5376/9756]	Loss: 0.1301	LR: 0.004000
Training Epoch: 31 [5632/9756]	Loss: 0.1261	LR: 0.004000
Training Epoch: 31 [5888/9756]	Loss: 0.1390	LR: 0.004000
Training Epoch: 31 [6144/9756]	Loss: 0.1505	LR: 0.004000
Training Epoch: 31 [6400/9756]	Loss: 0.1624	LR: 0.004000
Training Epoch: 31 [6656/9756]	Loss: 0.1369	LR: 0.004000
Training Epoch: 31 [6912/9756]	Loss: 0.1533	LR: 0.004000
Training Epoch: 31 [7168/9756]	Loss: 0.1505	LR: 0.004000
Training Epoch: 31 [7424/9756]	Loss: 0.1574	LR: 0.004000
Training Epoch: 31 [7680/9756]	Loss: 0.1319	LR: 0.004000
Training Epoch: 31 [7936/9756]	Loss: 0.1513	LR: 0.004000
Training Epoch: 31 [8192/9756]	Loss: 0.1149	LR: 0.004000
Training Epoch: 31 [8448/9756]	Loss: 0.1788	LR: 0.004000
Training Epoch: 31 [8704/9756]	Loss: 0.1253	LR: 0.004000
Training Epoch: 31 [8960/9756]	Loss: 0.1469	LR: 0.004000
Training Epoch: 31 [9216/9756]	Loss: 0.1183	LR: 0.004000
Training Epoch: 31 [9472/9756]	Loss: 0.0789	LR: 0.004000
Training Epoch: 31 [9728/9756]	Loss: 0.0981	LR: 0.004000
Training Epoch: 31 [9756/9756]	Loss: 0.2116	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1348, Train Accuracy: 0.9446
Epoch 31 training time consumed: 140.55s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9312, Time consumed:7.95s
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: 93.83680725097656
Retain Accuracy: 94.25652313232422
Zero-Retain Forget (ZRF): 0.6999636888504028
Membership Inference Attack (MIA): 0.3434343434343434
Forget vs Retain Membership Inference Attack (MIA): 0.5425867507886435
Forget vs Test Membership Inference Attack (MIA): 0.5520504731861199
Test vs Retain Membership Inference Attack (MIA): 0.5048426150121066
Train vs Test Membership Inference Attack (MIA): 0.5266343825665859
Forget Set Accuracy (Df): 92.64323425292969
Method Execution Time: 5763.01 seconds
