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

📌 S Retain class distribution for seed 10:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 10:
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: 0.7337	LR: 0.000000
Training Epoch: 1 [512/9756]	Loss: 0.7192	LR: 0.002564
Training Epoch: 1 [768/9756]	Loss: 0.6977	LR: 0.005128
Training Epoch: 1 [1024/9756]	Loss: 0.7234	LR: 0.007692
Training Epoch: 1 [1280/9756]	Loss: 0.7814	LR: 0.010256
Training Epoch: 1 [1536/9756]	Loss: 0.7454	LR: 0.012821
Training Epoch: 1 [1792/9756]	Loss: 0.8034	LR: 0.015385
Training Epoch: 1 [2048/9756]	Loss: 0.8228	LR: 0.017949
Training Epoch: 1 [2304/9756]	Loss: 0.8234	LR: 0.020513
Training Epoch: 1 [2560/9756]	Loss: 0.9601	LR: 0.023077
Training Epoch: 1 [2816/9756]	Loss: 0.7287	LR: 0.025641
Training Epoch: 1 [3072/9756]	Loss: 1.1938	LR: 0.028205
Training Epoch: 1 [3328/9756]	Loss: 1.1895	LR: 0.030769
Training Epoch: 1 [3584/9756]	Loss: 0.8786	LR: 0.033333
Training Epoch: 1 [3840/9756]	Loss: 0.8226	LR: 0.035897
Training Epoch: 1 [4096/9756]	Loss: 0.9970	LR: 0.038462
Training Epoch: 1 [4352/9756]	Loss: 1.3781	LR: 0.041026
Training Epoch: 1 [4608/9756]	Loss: 0.7393	LR: 0.043590
Training Epoch: 1 [4864/9756]	Loss: 0.8882	LR: 0.046154
Training Epoch: 1 [5120/9756]	Loss: 0.6670	LR: 0.048718
Training Epoch: 1 [5376/9756]	Loss: 0.8563	LR: 0.051282
Training Epoch: 1 [5632/9756]	Loss: 0.7063	LR: 0.053846
Training Epoch: 1 [5888/9756]	Loss: 0.8072	LR: 0.056410
Training Epoch: 1 [6144/9756]	Loss: 0.7063	LR: 0.058974
Training Epoch: 1 [6400/9756]	Loss: 0.8911	LR: 0.061538
Training Epoch: 1 [6656/9756]	Loss: 1.0087	LR: 0.064103
Training Epoch: 1 [6912/9756]	Loss: 0.7678	LR: 0.066667
Training Epoch: 1 [7168/9756]	Loss: 0.7511	LR: 0.069231
Training Epoch: 1 [7424/9756]	Loss: 0.8098	LR: 0.071795
Training Epoch: 1 [7680/9756]	Loss: 0.7298	LR: 0.074359
Training Epoch: 1 [7936/9756]	Loss: 0.7383	LR: 0.076923
Training Epoch: 1 [8192/9756]	Loss: 0.8458	LR: 0.079487
Training Epoch: 1 [8448/9756]	Loss: 0.6746	LR: 0.082051
Training Epoch: 1 [8704/9756]	Loss: 0.8503	LR: 0.084615
Training Epoch: 1 [8960/9756]	Loss: 1.0571	LR: 0.087179
Training Epoch: 1 [9216/9756]	Loss: 1.7106	LR: 0.089744
Training Epoch: 1 [9472/9756]	Loss: 1.2089	LR: 0.092308
Training Epoch: 1 [9728/9756]	Loss: 1.1424	LR: 0.094872
Training Epoch: 1 [9756/9756]	Loss: 1.2521	LR: 0.097436
Epoch 1 - Average Train Loss: 0.8841, Train Accuracy: 0.5194
Epoch 1 training time consumed: 333.29s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0169, Accuracy: 0.4508, Time consumed:7.84s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-1-best.pth
Training Epoch: 2 [256/9756]	Loss: 0.6960	LR: 0.100000
Training Epoch: 2 [512/9756]	Loss: 1.0487	LR: 0.100000
Training Epoch: 2 [768/9756]	Loss: 0.9718	LR: 0.100000
Training Epoch: 2 [1024/9756]	Loss: 0.8867	LR: 0.100000
Training Epoch: 2 [1280/9756]	Loss: 0.7504	LR: 0.100000
Training Epoch: 2 [1536/9756]	Loss: 0.7430	LR: 0.100000
Training Epoch: 2 [1792/9756]	Loss: 0.7304	LR: 0.100000
Training Epoch: 2 [2048/9756]	Loss: 0.7513	LR: 0.100000
Training Epoch: 2 [2304/9756]	Loss: 0.7734	LR: 0.100000
Training Epoch: 2 [2560/9756]	Loss: 0.7356	LR: 0.100000
Training Epoch: 2 [2816/9756]	Loss: 0.7484	LR: 0.100000
Training Epoch: 2 [3072/9756]	Loss: 0.6873	LR: 0.100000
Training Epoch: 2 [3328/9756]	Loss: 0.7284	LR: 0.100000
Training Epoch: 2 [3584/9756]	Loss: 0.6762	LR: 0.100000
Training Epoch: 2 [3840/9756]	Loss: 0.6891	LR: 0.100000
Training Epoch: 2 [4096/9756]	Loss: 0.6944	LR: 0.100000
Training Epoch: 2 [4352/9756]	Loss: 0.6868	LR: 0.100000
Training Epoch: 2 [4608/9756]	Loss: 0.7253	LR: 0.100000
Training Epoch: 2 [4864/9756]	Loss: 0.6990	LR: 0.100000
Training Epoch: 2 [5120/9756]	Loss: 0.6957	LR: 0.100000
Training Epoch: 2 [5376/9756]	Loss: 0.6982	LR: 0.100000
Training Epoch: 2 [5632/9756]	Loss: 0.7211	LR: 0.100000
Training Epoch: 2 [5888/9756]	Loss: 0.7147	LR: 0.100000
Training Epoch: 2 [6144/9756]	Loss: 0.7464	LR: 0.100000
Training Epoch: 2 [6400/9756]	Loss: 0.6904	LR: 0.100000
Training Epoch: 2 [6656/9756]	Loss: 0.7275	LR: 0.100000
Training Epoch: 2 [6912/9756]	Loss: 0.7035	LR: 0.100000
Training Epoch: 2 [7168/9756]	Loss: 0.6669	LR: 0.100000
Training Epoch: 2 [7424/9756]	Loss: 0.7182	LR: 0.100000
Training Epoch: 2 [7680/9756]	Loss: 0.7232	LR: 0.100000
Training Epoch: 2 [7936/9756]	Loss: 0.6793	LR: 0.100000
Training Epoch: 2 [8192/9756]	Loss: 0.7379	LR: 0.100000
Training Epoch: 2 [8448/9756]	Loss: 0.6993	LR: 0.100000
Training Epoch: 2 [8704/9756]	Loss: 0.7149	LR: 0.100000
Training Epoch: 2 [8960/9756]	Loss: 0.6813	LR: 0.100000
Training Epoch: 2 [9216/9756]	Loss: 0.7270	LR: 0.100000
Training Epoch: 2 [9472/9756]	Loss: 0.7478	LR: 0.100000
Training Epoch: 2 [9728/9756]	Loss: 0.8783	LR: 0.100000
Training Epoch: 2 [9756/9756]	Loss: 0.7646	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7394, Train Accuracy: 0.5297
Epoch 2 training time consumed: 142.33s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0037, Accuracy: 0.5550, Time consumed:8.14s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-2-best.pth
Training Epoch: 3 [256/9756]	Loss: 0.7203	LR: 0.100000
Training Epoch: 3 [512/9756]	Loss: 0.8647	LR: 0.100000
Training Epoch: 3 [768/9756]	Loss: 0.7719	LR: 0.100000
Training Epoch: 3 [1024/9756]	Loss: 0.7102	LR: 0.100000
Training Epoch: 3 [1280/9756]	Loss: 0.7596	LR: 0.100000
Training Epoch: 3 [1536/9756]	Loss: 0.8270	LR: 0.100000
Training Epoch: 3 [1792/9756]	Loss: 0.7860	LR: 0.100000
Training Epoch: 3 [2048/9756]	Loss: 0.7707	LR: 0.100000
Training Epoch: 3 [2304/9756]	Loss: 0.6866	LR: 0.100000
Training Epoch: 3 [2560/9756]	Loss: 0.7125	LR: 0.100000
Training Epoch: 3 [2816/9756]	Loss: 0.7598	LR: 0.100000
Training Epoch: 3 [3072/9756]	Loss: 0.7425	LR: 0.100000
Training Epoch: 3 [3328/9756]	Loss: 0.7778	LR: 0.100000
Training Epoch: 3 [3584/9756]	Loss: 0.6967	LR: 0.100000
Training Epoch: 3 [3840/9756]	Loss: 0.7073	LR: 0.100000
Training Epoch: 3 [4096/9756]	Loss: 0.6835	LR: 0.100000
Training Epoch: 3 [4352/9756]	Loss: 0.6756	LR: 0.100000
Training Epoch: 3 [4608/9756]	Loss: 0.7813	LR: 0.100000
Training Epoch: 3 [4864/9756]	Loss: 0.7515	LR: 0.100000
Training Epoch: 3 [5120/9756]	Loss: 0.7091	LR: 0.100000
Training Epoch: 3 [5376/9756]	Loss: 0.6774	LR: 0.100000
Training Epoch: 3 [5632/9756]	Loss: 0.6691	LR: 0.100000
Training Epoch: 3 [5888/9756]	Loss: 0.7901	LR: 0.100000
Training Epoch: 3 [6144/9756]	Loss: 0.6760	LR: 0.100000
Training Epoch: 3 [6400/9756]	Loss: 0.6963	LR: 0.100000
Training Epoch: 3 [6656/9756]	Loss: 0.7119	LR: 0.100000
Training Epoch: 3 [6912/9756]	Loss: 0.6991	LR: 0.100000
Training Epoch: 3 [7168/9756]	Loss: 0.7499	LR: 0.100000
Training Epoch: 3 [7424/9756]	Loss: 0.6952	LR: 0.100000
Training Epoch: 3 [7680/9756]	Loss: 0.6782	LR: 0.100000
Training Epoch: 3 [7936/9756]	Loss: 0.6778	LR: 0.100000
Training Epoch: 3 [8192/9756]	Loss: 0.6897	LR: 0.100000
Training Epoch: 3 [8448/9756]	Loss: 0.6809	LR: 0.100000
Training Epoch: 3 [8704/9756]	Loss: 0.6793	LR: 0.100000
Training Epoch: 3 [8960/9756]	Loss: 0.6848	LR: 0.100000
Training Epoch: 3 [9216/9756]	Loss: 0.6765	LR: 0.100000
Training Epoch: 3 [9472/9756]	Loss: 0.6911	LR: 0.100000
Training Epoch: 3 [9728/9756]	Loss: 0.6741	LR: 0.100000
Training Epoch: 3 [9756/9756]	Loss: 0.6871	LR: 0.100000
Epoch 3 - Average Train Loss: 0.7207, Train Accuracy: 0.5442
Epoch 3 training time consumed: 141.48s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0031, Accuracy: 0.5215, Time consumed:8.08s
Training Epoch: 4 [256/9756]	Loss: 0.6850	LR: 0.100000
Training Epoch: 4 [512/9756]	Loss: 0.6980	LR: 0.100000
Training Epoch: 4 [768/9756]	Loss: 0.6920	LR: 0.100000
Training Epoch: 4 [1024/9756]	Loss: 0.6848	LR: 0.100000
Training Epoch: 4 [1280/9756]	Loss: 0.6797	LR: 0.100000
Training Epoch: 4 [1536/9756]	Loss: 0.6947	LR: 0.100000
Training Epoch: 4 [1792/9756]	Loss: 0.6697	LR: 0.100000
Training Epoch: 4 [2048/9756]	Loss: 0.6736	LR: 0.100000
Training Epoch: 4 [2304/9756]	Loss: 0.6705	LR: 0.100000
Training Epoch: 4 [2560/9756]	Loss: 0.6841	LR: 0.100000
Training Epoch: 4 [2816/9756]	Loss: 0.6564	LR: 0.100000
Training Epoch: 4 [3072/9756]	Loss: 0.6669	LR: 0.100000
Training Epoch: 4 [3328/9756]	Loss: 0.6641	LR: 0.100000
Training Epoch: 4 [3584/9756]	Loss: 0.6732	LR: 0.100000
Training Epoch: 4 [3840/9756]	Loss: 0.7020	LR: 0.100000
Training Epoch: 4 [4096/9756]	Loss: 0.6584	LR: 0.100000
Training Epoch: 4 [4352/9756]	Loss: 0.6890	LR: 0.100000
Training Epoch: 4 [4608/9756]	Loss: 0.6913	LR: 0.100000
Training Epoch: 4 [4864/9756]	Loss: 0.6506	LR: 0.100000
Training Epoch: 4 [5120/9756]	Loss: 0.6723	LR: 0.100000
Training Epoch: 4 [5376/9756]	Loss: 0.6856	LR: 0.100000
Training Epoch: 4 [5632/9756]	Loss: 0.6910	LR: 0.100000
Training Epoch: 4 [5888/9756]	Loss: 0.6762	LR: 0.100000
Training Epoch: 4 [6144/9756]	Loss: 0.6684	LR: 0.100000
Training Epoch: 4 [6400/9756]	Loss: 0.6736	LR: 0.100000
Training Epoch: 4 [6656/9756]	Loss: 0.6795	LR: 0.100000
Training Epoch: 4 [6912/9756]	Loss: 0.6687	LR: 0.100000
Training Epoch: 4 [7168/9756]	Loss: 0.6831	LR: 0.100000
Training Epoch: 4 [7424/9756]	Loss: 0.6804	LR: 0.100000
Training Epoch: 4 [7680/9756]	Loss: 0.6920	LR: 0.100000
Training Epoch: 4 [7936/9756]	Loss: 0.6897	LR: 0.100000
Training Epoch: 4 [8192/9756]	Loss: 0.6809	LR: 0.100000
Training Epoch: 4 [8448/9756]	Loss: 0.6646	LR: 0.100000
Training Epoch: 4 [8704/9756]	Loss: 0.6924	LR: 0.100000
Training Epoch: 4 [8960/9756]	Loss: 0.6724	LR: 0.100000
Training Epoch: 4 [9216/9756]	Loss: 0.6581	LR: 0.100000
Training Epoch: 4 [9472/9756]	Loss: 0.6519	LR: 0.100000
Training Epoch: 4 [9728/9756]	Loss: 0.6925	LR: 0.100000
Training Epoch: 4 [9756/9756]	Loss: 0.7877	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6781, Train Accuracy: 0.5776
Epoch 4 training time consumed: 141.81s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0032, Accuracy: 0.5554, Time consumed:7.79s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-4-best.pth
Training Epoch: 5 [256/9756]	Loss: 0.6602	LR: 0.100000
Training Epoch: 5 [512/9756]	Loss: 0.6774	LR: 0.100000
Training Epoch: 5 [768/9756]	Loss: 0.6790	LR: 0.100000
Training Epoch: 5 [1024/9756]	Loss: 0.7078	LR: 0.100000
Training Epoch: 5 [1280/9756]	Loss: 0.6669	LR: 0.100000
Training Epoch: 5 [1536/9756]	Loss: 0.6773	LR: 0.100000
Training Epoch: 5 [1792/9756]	Loss: 0.7146	LR: 0.100000
Training Epoch: 5 [2048/9756]	Loss: 0.6880	LR: 0.100000
Training Epoch: 5 [2304/9756]	Loss: 0.7072	LR: 0.100000
Training Epoch: 5 [2560/9756]	Loss: 0.7005	LR: 0.100000
Training Epoch: 5 [2816/9756]	Loss: 0.6776	LR: 0.100000
Training Epoch: 5 [3072/9756]	Loss: 0.6914	LR: 0.100000
Training Epoch: 5 [3328/9756]	Loss: 0.6922	LR: 0.100000
Training Epoch: 5 [3584/9756]	Loss: 0.6998	LR: 0.100000
Training Epoch: 5 [3840/9756]	Loss: 0.6755	LR: 0.100000
Training Epoch: 5 [4096/9756]	Loss: 0.6754	LR: 0.100000
Training Epoch: 5 [4352/9756]	Loss: 0.6776	LR: 0.100000
Training Epoch: 5 [4608/9756]	Loss: 0.6906	LR: 0.100000
Training Epoch: 5 [4864/9756]	Loss: 0.6656	LR: 0.100000
Training Epoch: 5 [5120/9756]	Loss: 0.6750	LR: 0.100000
Training Epoch: 5 [5376/9756]	Loss: 0.6771	LR: 0.100000
Training Epoch: 5 [5632/9756]	Loss: 0.6550	LR: 0.100000
Training Epoch: 5 [5888/9756]	Loss: 0.6660	LR: 0.100000
Training Epoch: 5 [6144/9756]	Loss: 0.7031	LR: 0.100000
Training Epoch: 5 [6400/9756]	Loss: 0.6846	LR: 0.100000
Training Epoch: 5 [6656/9756]	Loss: 0.6537	LR: 0.100000
Training Epoch: 5 [6912/9756]	Loss: 0.6760	LR: 0.100000
Training Epoch: 5 [7168/9756]	Loss: 0.6566	LR: 0.100000
Training Epoch: 5 [7424/9756]	Loss: 0.6476	LR: 0.100000
Training Epoch: 5 [7680/9756]	Loss: 0.6926	LR: 0.100000
Training Epoch: 5 [7936/9756]	Loss: 0.7307	LR: 0.100000
Training Epoch: 5 [8192/9756]	Loss: 0.6849	LR: 0.100000
Training Epoch: 5 [8448/9756]	Loss: 0.6802	LR: 0.100000
Training Epoch: 5 [8704/9756]	Loss: 0.6747	LR: 0.100000
Training Epoch: 5 [8960/9756]	Loss: 0.6857	LR: 0.100000
Training Epoch: 5 [9216/9756]	Loss: 0.6855	LR: 0.100000
Training Epoch: 5 [9472/9756]	Loss: 0.6773	LR: 0.100000
Training Epoch: 5 [9728/9756]	Loss: 0.7054	LR: 0.100000
Training Epoch: 5 [9756/9756]	Loss: 0.6631	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6825, Train Accuracy: 0.5723
Epoch 5 training time consumed: 141.66s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0030, Accuracy: 0.5569, Time consumed:8.03s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-5-best.pth
Training Epoch: 6 [256/9756]	Loss: 0.6640	LR: 0.100000
Training Epoch: 6 [512/9756]	Loss: 0.6857	LR: 0.100000
Training Epoch: 6 [768/9756]	Loss: 0.6767	LR: 0.100000
Training Epoch: 6 [1024/9756]	Loss: 0.6628	LR: 0.100000
Training Epoch: 6 [1280/9756]	Loss: 0.6856	LR: 0.100000
Training Epoch: 6 [1536/9756]	Loss: 0.6570	LR: 0.100000
Training Epoch: 6 [1792/9756]	Loss: 0.6623	LR: 0.100000
Training Epoch: 6 [2048/9756]	Loss: 0.6523	LR: 0.100000
Training Epoch: 6 [2304/9756]	Loss: 0.6718	LR: 0.100000
Training Epoch: 6 [2560/9756]	Loss: 0.6446	LR: 0.100000
Training Epoch: 6 [2816/9756]	Loss: 0.6586	LR: 0.100000
Training Epoch: 6 [3072/9756]	Loss: 0.6578	LR: 0.100000
Training Epoch: 6 [3328/9756]	Loss: 0.6956	LR: 0.100000
Training Epoch: 6 [3584/9756]	Loss: 0.6522	LR: 0.100000
Training Epoch: 6 [3840/9756]	Loss: 0.6856	LR: 0.100000
Training Epoch: 6 [4096/9756]	Loss: 0.6898	LR: 0.100000
Training Epoch: 6 [4352/9756]	Loss: 0.6982	LR: 0.100000
Training Epoch: 6 [4608/9756]	Loss: 0.6857	LR: 0.100000
Training Epoch: 6 [4864/9756]	Loss: 0.6781	LR: 0.100000
Training Epoch: 6 [5120/9756]	Loss: 0.6750	LR: 0.100000
Training Epoch: 6 [5376/9756]	Loss: 0.6727	LR: 0.100000
Training Epoch: 6 [5632/9756]	Loss: 0.6654	LR: 0.100000
Training Epoch: 6 [5888/9756]	Loss: 0.6852	LR: 0.100000
Training Epoch: 6 [6144/9756]	Loss: 0.6609	LR: 0.100000
Training Epoch: 6 [6400/9756]	Loss: 0.6697	LR: 0.100000
Training Epoch: 6 [6656/9756]	Loss: 0.6692	LR: 0.100000
Training Epoch: 6 [6912/9756]	Loss: 0.6633	LR: 0.100000
Training Epoch: 6 [7168/9756]	Loss: 0.6780	LR: 0.100000
Training Epoch: 6 [7424/9756]	Loss: 0.6535	LR: 0.100000
Training Epoch: 6 [7680/9756]	Loss: 0.6786	LR: 0.100000
Training Epoch: 6 [7936/9756]	Loss: 0.7246	LR: 0.100000
Training Epoch: 6 [8192/9756]	Loss: 0.6592	LR: 0.100000
Training Epoch: 6 [8448/9756]	Loss: 0.6801	LR: 0.100000
Training Epoch: 6 [8704/9756]	Loss: 0.6766	LR: 0.100000
Training Epoch: 6 [8960/9756]	Loss: 0.6497	LR: 0.100000
Training Epoch: 6 [9216/9756]	Loss: 0.6446	LR: 0.100000
Training Epoch: 6 [9472/9756]	Loss: 0.6672	LR: 0.100000
Training Epoch: 6 [9728/9756]	Loss: 0.6430	LR: 0.100000
Training Epoch: 6 [9756/9756]	Loss: 0.6709	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6705, Train Accuracy: 0.5940
Epoch 6 training time consumed: 141.50s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0030, Accuracy: 0.5719, Time consumed:8.20s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-6-best.pth
Training Epoch: 7 [256/9756]	Loss: 0.6564	LR: 0.100000
Training Epoch: 7 [512/9756]	Loss: 0.6903	LR: 0.100000
Training Epoch: 7 [768/9756]	Loss: 0.6618	LR: 0.100000
Training Epoch: 7 [1024/9756]	Loss: 0.6564	LR: 0.100000
Training Epoch: 7 [1280/9756]	Loss: 0.7037	LR: 0.100000
Training Epoch: 7 [1536/9756]	Loss: 0.6966	LR: 0.100000
Training Epoch: 7 [1792/9756]	Loss: 0.6873	LR: 0.100000
Training Epoch: 7 [2048/9756]	Loss: 0.6810	LR: 0.100000
Training Epoch: 7 [2304/9756]	Loss: 0.6844	LR: 0.100000
Training Epoch: 7 [2560/9756]	Loss: 0.6723	LR: 0.100000
Training Epoch: 7 [2816/9756]	Loss: 0.6663	LR: 0.100000
Training Epoch: 7 [3072/9756]	Loss: 0.6643	LR: 0.100000
Training Epoch: 7 [3328/9756]	Loss: 0.6697	LR: 0.100000
Training Epoch: 7 [3584/9756]	Loss: 0.6687	LR: 0.100000
Training Epoch: 7 [3840/9756]	Loss: 0.6784	LR: 0.100000
Training Epoch: 7 [4096/9756]	Loss: 0.6959	LR: 0.100000
Training Epoch: 7 [4352/9756]	Loss: 0.7010	LR: 0.100000
Training Epoch: 7 [4608/9756]	Loss: 0.6670	LR: 0.100000
Training Epoch: 7 [4864/9756]	Loss: 0.6667	LR: 0.100000
Training Epoch: 7 [5120/9756]	Loss: 0.6720	LR: 0.100000
Training Epoch: 7 [5376/9756]	Loss: 0.6705	LR: 0.100000
Training Epoch: 7 [5632/9756]	Loss: 0.6780	LR: 0.100000
Training Epoch: 7 [5888/9756]	Loss: 0.7036	LR: 0.100000
Training Epoch: 7 [6144/9756]	Loss: 0.6758	LR: 0.100000
Training Epoch: 7 [6400/9756]	Loss: 0.6636	LR: 0.100000
Training Epoch: 7 [6656/9756]	Loss: 0.6596	LR: 0.100000
Training Epoch: 7 [6912/9756]	Loss: 0.6714	LR: 0.100000
Training Epoch: 7 [7168/9756]	Loss: 0.6540	LR: 0.100000
Training Epoch: 7 [7424/9756]	Loss: 0.6583	LR: 0.100000
Training Epoch: 7 [7680/9756]	Loss: 0.6563	LR: 0.100000
Training Epoch: 7 [7936/9756]	Loss: 0.6637	LR: 0.100000
Training Epoch: 7 [8192/9756]	Loss: 0.6316	LR: 0.100000
Training Epoch: 7 [8448/9756]	Loss: 0.6909	LR: 0.100000
Training Epoch: 7 [8704/9756]	Loss: 0.6617	LR: 0.100000
Training Epoch: 7 [8960/9756]	Loss: 0.6336	LR: 0.100000
Training Epoch: 7 [9216/9756]	Loss: 0.6378	LR: 0.100000
Training Epoch: 7 [9472/9756]	Loss: 0.6840	LR: 0.100000
Training Epoch: 7 [9728/9756]	Loss: 0.6555	LR: 0.100000
Training Epoch: 7 [9756/9756]	Loss: 0.6361	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6707, Train Accuracy: 0.5964
Epoch 7 training time consumed: 141.72s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0030, Accuracy: 0.6063, Time consumed:7.86s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-7-best.pth
Training Epoch: 8 [256/9756]	Loss: 0.6389	LR: 0.100000
Training Epoch: 8 [512/9756]	Loss: 0.6903	LR: 0.100000
Training Epoch: 8 [768/9756]	Loss: 0.6702	LR: 0.100000
Training Epoch: 8 [1024/9756]	Loss: 0.6768	LR: 0.100000
Training Epoch: 8 [1280/9756]	Loss: 0.6557	LR: 0.100000
Training Epoch: 8 [1536/9756]	Loss: 0.6633	LR: 0.100000
Training Epoch: 8 [1792/9756]	Loss: 0.6569	LR: 0.100000
Training Epoch: 8 [2048/9756]	Loss: 0.6795	LR: 0.100000
Training Epoch: 8 [2304/9756]	Loss: 0.6392	LR: 0.100000
Training Epoch: 8 [2560/9756]	Loss: 0.6665	LR: 0.100000
Training Epoch: 8 [2816/9756]	Loss: 0.6731	LR: 0.100000
Training Epoch: 8 [3072/9756]	Loss: 0.6834	LR: 0.100000
Training Epoch: 8 [3328/9756]	Loss: 0.6501	LR: 0.100000
Training Epoch: 8 [3584/9756]	Loss: 0.6591	LR: 0.100000
Training Epoch: 8 [3840/9756]	Loss: 0.6533	LR: 0.100000
Training Epoch: 8 [4096/9756]	Loss: 0.6681	LR: 0.100000
Training Epoch: 8 [4352/9756]	Loss: 0.6575	LR: 0.100000
Training Epoch: 8 [4608/9756]	Loss: 0.6598	LR: 0.100000
Training Epoch: 8 [4864/9756]	Loss: 0.6681	LR: 0.100000
Training Epoch: 8 [5120/9756]	Loss: 0.6594	LR: 0.100000
Training Epoch: 8 [5376/9756]	Loss: 0.6579	LR: 0.100000
Training Epoch: 8 [5632/9756]	Loss: 0.6944	LR: 0.100000
Training Epoch: 8 [5888/9756]	Loss: 0.6221	LR: 0.100000
Training Epoch: 8 [6144/9756]	Loss: 0.6404	LR: 0.100000
Training Epoch: 8 [6400/9756]	Loss: 0.6737	LR: 0.100000
Training Epoch: 8 [6656/9756]	Loss: 0.6854	LR: 0.100000
Training Epoch: 8 [6912/9756]	Loss: 0.6593	LR: 0.100000
Training Epoch: 8 [7168/9756]	Loss: 0.6672	LR: 0.100000
Training Epoch: 8 [7424/9756]	Loss: 0.6875	LR: 0.100000
Training Epoch: 8 [7680/9756]	Loss: 0.6476	LR: 0.100000
Training Epoch: 8 [7936/9756]	Loss: 0.6548	LR: 0.100000
Training Epoch: 8 [8192/9756]	Loss: 0.6687	LR: 0.100000
Training Epoch: 8 [8448/9756]	Loss: 0.6540	LR: 0.100000
Training Epoch: 8 [8704/9756]	Loss: 0.6711	LR: 0.100000
Training Epoch: 8 [8960/9756]	Loss: 0.6463	LR: 0.100000
Training Epoch: 8 [9216/9756]	Loss: 0.6653	LR: 0.100000
Training Epoch: 8 [9472/9756]	Loss: 0.6548	LR: 0.100000
Training Epoch: 8 [9728/9756]	Loss: 0.6797	LR: 0.100000
Training Epoch: 8 [9756/9756]	Loss: 0.6838	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6632, Train Accuracy: 0.6036
Epoch 8 training time consumed: 141.82s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0030, Accuracy: 0.5874, Time consumed:8.08s
Training Epoch: 9 [256/9756]	Loss: 0.6587	LR: 0.100000
Training Epoch: 9 [512/9756]	Loss: 0.6707	LR: 0.100000
Training Epoch: 9 [768/9756]	Loss: 0.6552	LR: 0.100000
Training Epoch: 9 [1024/9756]	Loss: 0.6636	LR: 0.100000
Training Epoch: 9 [1280/9756]	Loss: 0.6637	LR: 0.100000
Training Epoch: 9 [1536/9756]	Loss: 0.6595	LR: 0.100000
Training Epoch: 9 [1792/9756]	Loss: 0.6557	LR: 0.100000
Training Epoch: 9 [2048/9756]	Loss: 0.6576	LR: 0.100000
Training Epoch: 9 [2304/9756]	Loss: 0.6389	LR: 0.100000
Training Epoch: 9 [2560/9756]	Loss: 0.6225	LR: 0.100000
Training Epoch: 9 [2816/9756]	Loss: 0.6451	LR: 0.100000
Training Epoch: 9 [3072/9756]	Loss: 0.6833	LR: 0.100000
Training Epoch: 9 [3328/9756]	Loss: 0.6895	LR: 0.100000
Training Epoch: 9 [3584/9756]	Loss: 0.6589	LR: 0.100000
Training Epoch: 9 [3840/9756]	Loss: 0.6380	LR: 0.100000
Training Epoch: 9 [4096/9756]	Loss: 0.6396	LR: 0.100000
Training Epoch: 9 [4352/9756]	Loss: 0.6684	LR: 0.100000
Training Epoch: 9 [4608/9756]	Loss: 0.6491	LR: 0.100000
Training Epoch: 9 [4864/9756]	Loss: 0.6504	LR: 0.100000
Training Epoch: 9 [5120/9756]	Loss: 0.6314	LR: 0.100000
Training Epoch: 9 [5376/9756]	Loss: 0.6578	LR: 0.100000
Training Epoch: 9 [5632/9756]	Loss: 0.6869	LR: 0.100000
Training Epoch: 9 [5888/9756]	Loss: 0.6387	LR: 0.100000
Training Epoch: 9 [6144/9756]	Loss: 0.6863	LR: 0.100000
Training Epoch: 9 [6400/9756]	Loss: 0.6725	LR: 0.100000
Training Epoch: 9 [6656/9756]	Loss: 0.6583	LR: 0.100000
Training Epoch: 9 [6912/9756]	Loss: 0.6688	LR: 0.100000
Training Epoch: 9 [7168/9756]	Loss: 0.6792	LR: 0.100000
Training Epoch: 9 [7424/9756]	Loss: 0.6380	LR: 0.100000
Training Epoch: 9 [7680/9756]	Loss: 0.6619	LR: 0.100000
Training Epoch: 9 [7936/9756]	Loss: 0.6532	LR: 0.100000
Training Epoch: 9 [8192/9756]	Loss: 0.6524	LR: 0.100000
Training Epoch: 9 [8448/9756]	Loss: 0.6592	LR: 0.100000
Training Epoch: 9 [8704/9756]	Loss: 0.6722	LR: 0.100000
Training Epoch: 9 [8960/9756]	Loss: 0.6371	LR: 0.100000
Training Epoch: 9 [9216/9756]	Loss: 0.6473	LR: 0.100000
Training Epoch: 9 [9472/9756]	Loss: 0.6440	LR: 0.100000
Training Epoch: 9 [9728/9756]	Loss: 0.6628	LR: 0.100000
Training Epoch: 9 [9756/9756]	Loss: 0.6617	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6573, Train Accuracy: 0.6138
Epoch 9 training time consumed: 141.38s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0028, Accuracy: 0.6475, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-9-best.pth
Training Epoch: 10 [256/9756]	Loss: 0.6559	LR: 0.020000
Training Epoch: 10 [512/9756]	Loss: 0.6474	LR: 0.020000
Training Epoch: 10 [768/9756]	Loss: 0.6175	LR: 0.020000
Training Epoch: 10 [1024/9756]	Loss: 0.6582	LR: 0.020000
Training Epoch: 10 [1280/9756]	Loss: 0.6477	LR: 0.020000
Training Epoch: 10 [1536/9756]	Loss: 0.6394	LR: 0.020000
Training Epoch: 10 [1792/9756]	Loss: 0.6688	LR: 0.020000
Training Epoch: 10 [2048/9756]	Loss: 0.6343	LR: 0.020000
Training Epoch: 10 [2304/9756]	Loss: 0.6201	LR: 0.020000
Training Epoch: 10 [2560/9756]	Loss: 0.6475	LR: 0.020000
Training Epoch: 10 [2816/9756]	Loss: 0.6047	LR: 0.020000
Training Epoch: 10 [3072/9756]	Loss: 0.5996	LR: 0.020000
Training Epoch: 10 [3328/9756]	Loss: 0.6296	LR: 0.020000
Training Epoch: 10 [3584/9756]	Loss: 0.6569	LR: 0.020000
Training Epoch: 10 [3840/9756]	Loss: 0.6299	LR: 0.020000
Training Epoch: 10 [4096/9756]	Loss: 0.6344	LR: 0.020000
Training Epoch: 10 [4352/9756]	Loss: 0.6817	LR: 0.020000
Training Epoch: 10 [4608/9756]	Loss: 0.6320	LR: 0.020000
Training Epoch: 10 [4864/9756]	Loss: 0.6351	LR: 0.020000
Training Epoch: 10 [5120/9756]	Loss: 0.6381	LR: 0.020000
Training Epoch: 10 [5376/9756]	Loss: 0.6519	LR: 0.020000
Training Epoch: 10 [5632/9756]	Loss: 0.6563	LR: 0.020000
Training Epoch: 10 [5888/9756]	Loss: 0.6354	LR: 0.020000
Training Epoch: 10 [6144/9756]	Loss: 0.6357	LR: 0.020000
Training Epoch: 10 [6400/9756]	Loss: 0.6409	LR: 0.020000
Training Epoch: 10 [6656/9756]	Loss: 0.6430	LR: 0.020000
Training Epoch: 10 [6912/9756]	Loss: 0.6348	LR: 0.020000
Training Epoch: 10 [7168/9756]	Loss: 0.6340	LR: 0.020000
Training Epoch: 10 [7424/9756]	Loss: 0.6571	LR: 0.020000
Training Epoch: 10 [7680/9756]	Loss: 0.6163	LR: 0.020000
Training Epoch: 10 [7936/9756]	Loss: 0.6276	LR: 0.020000
Training Epoch: 10 [8192/9756]	Loss: 0.6030	LR: 0.020000
Training Epoch: 10 [8448/9756]	Loss: 0.6093	LR: 0.020000
Training Epoch: 10 [8704/9756]	Loss: 0.6509	LR: 0.020000
Training Epoch: 10 [8960/9756]	Loss: 0.5913	LR: 0.020000
Training Epoch: 10 [9216/9756]	Loss: 0.6188	LR: 0.020000
Training Epoch: 10 [9472/9756]	Loss: 0.6596	LR: 0.020000
Training Epoch: 10 [9728/9756]	Loss: 0.6175	LR: 0.020000
Training Epoch: 10 [9756/9756]	Loss: 0.6252	LR: 0.020000
Epoch 10 - Average Train Loss: 0.6358, Train Accuracy: 0.6460
Epoch 10 training time consumed: 141.80s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0027, Accuracy: 0.6610, Time consumed:7.86s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-10-best.pth
Training Epoch: 11 [256/9756]	Loss: 0.6191	LR: 0.020000
Training Epoch: 11 [512/9756]	Loss: 0.5836	LR: 0.020000
Training Epoch: 11 [768/9756]	Loss: 0.6275	LR: 0.020000
Training Epoch: 11 [1024/9756]	Loss: 0.6643	LR: 0.020000
Training Epoch: 11 [1280/9756]	Loss: 0.6141	LR: 0.020000
Training Epoch: 11 [1536/9756]	Loss: 0.5969	LR: 0.020000
Training Epoch: 11 [1792/9756]	Loss: 0.6196	LR: 0.020000
Training Epoch: 11 [2048/9756]	Loss: 0.6042	LR: 0.020000
Training Epoch: 11 [2304/9756]	Loss: 0.6210	LR: 0.020000
Training Epoch: 11 [2560/9756]	Loss: 0.6389	LR: 0.020000
Training Epoch: 11 [2816/9756]	Loss: 0.6676	LR: 0.020000
Training Epoch: 11 [3072/9756]	Loss: 0.5978	LR: 0.020000
Training Epoch: 11 [3328/9756]	Loss: 0.6109	LR: 0.020000
Training Epoch: 11 [3584/9756]	Loss: 0.6093	LR: 0.020000
Training Epoch: 11 [3840/9756]	Loss: 0.6218	LR: 0.020000
Training Epoch: 11 [4096/9756]	Loss: 0.6190	LR: 0.020000
Training Epoch: 11 [4352/9756]	Loss: 0.6495	LR: 0.020000
Training Epoch: 11 [4608/9756]	Loss: 0.5941	LR: 0.020000
Training Epoch: 11 [4864/9756]	Loss: 0.6278	LR: 0.020000
Training Epoch: 11 [5120/9756]	Loss: 0.5920	LR: 0.020000
Training Epoch: 11 [5376/9756]	Loss: 0.6408	LR: 0.020000
Training Epoch: 11 [5632/9756]	Loss: 0.5970	LR: 0.020000
Training Epoch: 11 [5888/9756]	Loss: 0.5861	LR: 0.020000
Training Epoch: 11 [6144/9756]	Loss: 0.5791	LR: 0.020000
Training Epoch: 11 [6400/9756]	Loss: 0.5999	LR: 0.020000
Training Epoch: 11 [6656/9756]	Loss: 0.5912	LR: 0.020000
Training Epoch: 11 [6912/9756]	Loss: 0.6125	LR: 0.020000
Training Epoch: 11 [7168/9756]	Loss: 0.6126	LR: 0.020000
Training Epoch: 11 [7424/9756]	Loss: 0.6232	LR: 0.020000
Training Epoch: 11 [7680/9756]	Loss: 0.6068	LR: 0.020000
Training Epoch: 11 [7936/9756]	Loss: 0.5887	LR: 0.020000
Training Epoch: 11 [8192/9756]	Loss: 0.5911	LR: 0.020000
Training Epoch: 11 [8448/9756]	Loss: 0.6050	LR: 0.020000
Training Epoch: 11 [8704/9756]	Loss: 0.6761	LR: 0.020000
Training Epoch: 11 [8960/9756]	Loss: 0.5635	LR: 0.020000
Training Epoch: 11 [9216/9756]	Loss: 0.6107	LR: 0.020000
Training Epoch: 11 [9472/9756]	Loss: 0.5876	LR: 0.020000
Training Epoch: 11 [9728/9756]	Loss: 0.5386	LR: 0.020000
Training Epoch: 11 [9756/9756]	Loss: 0.5057	LR: 0.020000
Epoch 11 - Average Train Loss: 0.6100, Train Accuracy: 0.6767
Epoch 11 training time consumed: 141.37s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0026, Accuracy: 0.6944, Time consumed:7.95s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-11-best.pth
Training Epoch: 12 [256/9756]	Loss: 0.5885	LR: 0.020000
Training Epoch: 12 [512/9756]	Loss: 0.5548	LR: 0.020000
Training Epoch: 12 [768/9756]	Loss: 0.5489	LR: 0.020000
Training Epoch: 12 [1024/9756]	Loss: 0.6124	LR: 0.020000
Training Epoch: 12 [1280/9756]	Loss: 0.5387	LR: 0.020000
Training Epoch: 12 [1536/9756]	Loss: 0.5541	LR: 0.020000
Training Epoch: 12 [1792/9756]	Loss: 0.5693	LR: 0.020000
Training Epoch: 12 [2048/9756]	Loss: 0.6060	LR: 0.020000
Training Epoch: 12 [2304/9756]	Loss: 0.5748	LR: 0.020000
Training Epoch: 12 [2560/9756]	Loss: 0.6197	LR: 0.020000
Training Epoch: 12 [2816/9756]	Loss: 0.6129	LR: 0.020000
Training Epoch: 12 [3072/9756]	Loss: 0.6165	LR: 0.020000
Training Epoch: 12 [3328/9756]	Loss: 0.6158	LR: 0.020000
Training Epoch: 12 [3584/9756]	Loss: 0.5564	LR: 0.020000
Training Epoch: 12 [3840/9756]	Loss: 0.6074	LR: 0.020000
Training Epoch: 12 [4096/9756]	Loss: 0.5765	LR: 0.020000
Training Epoch: 12 [4352/9756]	Loss: 0.5751	LR: 0.020000
Training Epoch: 12 [4608/9756]	Loss: 0.6117	LR: 0.020000
Training Epoch: 12 [4864/9756]	Loss: 0.5894	LR: 0.020000
Training Epoch: 12 [5120/9756]	Loss: 0.5756	LR: 0.020000
Training Epoch: 12 [5376/9756]	Loss: 0.5765	LR: 0.020000
Training Epoch: 12 [5632/9756]	Loss: 0.5735	LR: 0.020000
Training Epoch: 12 [5888/9756]	Loss: 0.5698	LR: 0.020000
Training Epoch: 12 [6144/9756]	Loss: 0.6551	LR: 0.020000
Training Epoch: 12 [6400/9756]	Loss: 0.5288	LR: 0.020000
Training Epoch: 12 [6656/9756]	Loss: 0.5640	LR: 0.020000
Training Epoch: 12 [6912/9756]	Loss: 0.5715	LR: 0.020000
Training Epoch: 12 [7168/9756]	Loss: 0.5821	LR: 0.020000
Training Epoch: 12 [7424/9756]	Loss: 0.5944	LR: 0.020000
Training Epoch: 12 [7680/9756]	Loss: 0.6072	LR: 0.020000
Training Epoch: 12 [7936/9756]	Loss: 0.5379	LR: 0.020000
Training Epoch: 12 [8192/9756]	Loss: 0.5920	LR: 0.020000
Training Epoch: 12 [8448/9756]	Loss: 0.5900	LR: 0.020000
Training Epoch: 12 [8704/9756]	Loss: 0.5711	LR: 0.020000
Training Epoch: 12 [8960/9756]	Loss: 0.5511	LR: 0.020000
Training Epoch: 12 [9216/9756]	Loss: 0.5587	LR: 0.020000
Training Epoch: 12 [9472/9756]	Loss: 0.6008	LR: 0.020000
Training Epoch: 12 [9728/9756]	Loss: 0.5484	LR: 0.020000
Training Epoch: 12 [9756/9756]	Loss: 0.5804	LR: 0.020000
Epoch 12 - Average Train Loss: 0.5810, Train Accuracy: 0.6991
Epoch 12 training time consumed: 141.88s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0024, Accuracy: 0.7409, Time consumed:7.97s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-12-best.pth
Training Epoch: 13 [256/9756]	Loss: 0.5143	LR: 0.020000
Training Epoch: 13 [512/9756]	Loss: 0.6002	LR: 0.020000
Training Epoch: 13 [768/9756]	Loss: 0.5728	LR: 0.020000
Training Epoch: 13 [1024/9756]	Loss: 0.5903	LR: 0.020000
Training Epoch: 13 [1280/9756]	Loss: 0.5373	LR: 0.020000
Training Epoch: 13 [1536/9756]	Loss: 0.5824	LR: 0.020000
Training Epoch: 13 [1792/9756]	Loss: 0.5494	LR: 0.020000
Training Epoch: 13 [2048/9756]	Loss: 0.5948	LR: 0.020000
Training Epoch: 13 [2304/9756]	Loss: 0.5867	LR: 0.020000
Training Epoch: 13 [2560/9756]	Loss: 0.5366	LR: 0.020000
Training Epoch: 13 [2816/9756]	Loss: 0.5629	LR: 0.020000
Training Epoch: 13 [3072/9756]	Loss: 0.5633	LR: 0.020000
Training Epoch: 13 [3328/9756]	Loss: 0.5278	LR: 0.020000
Training Epoch: 13 [3584/9756]	Loss: 0.5614	LR: 0.020000
Training Epoch: 13 [3840/9756]	Loss: 0.5002	LR: 0.020000
Training Epoch: 13 [4096/9756]	Loss: 0.5988	LR: 0.020000
Training Epoch: 13 [4352/9756]	Loss: 0.5110	LR: 0.020000
Training Epoch: 13 [4608/9756]	Loss: 0.5334	LR: 0.020000
Training Epoch: 13 [4864/9756]	Loss: 0.5059	LR: 0.020000
Training Epoch: 13 [5120/9756]	Loss: 0.5198	LR: 0.020000
Training Epoch: 13 [5376/9756]	Loss: 0.5328	LR: 0.020000
Training Epoch: 13 [5632/9756]	Loss: 0.5157	LR: 0.020000
Training Epoch: 13 [5888/9756]	Loss: 0.5221	LR: 0.020000
Training Epoch: 13 [6144/9756]	Loss: 0.5641	LR: 0.020000
Training Epoch: 13 [6400/9756]	Loss: 0.4957	LR: 0.020000
Training Epoch: 13 [6656/9756]	Loss: 0.4483	LR: 0.020000
Training Epoch: 13 [6912/9756]	Loss: 0.5559	LR: 0.020000
Training Epoch: 13 [7168/9756]	Loss: 0.4784	LR: 0.020000
Training Epoch: 13 [7424/9756]	Loss: 0.4656	LR: 0.020000
Training Epoch: 13 [7680/9756]	Loss: 0.5101	LR: 0.020000
Training Epoch: 13 [7936/9756]	Loss: 0.4817	LR: 0.020000
Training Epoch: 13 [8192/9756]	Loss: 0.4786	LR: 0.020000
Training Epoch: 13 [8448/9756]	Loss: 0.4792	LR: 0.020000
Training Epoch: 13 [8704/9756]	Loss: 0.4540	LR: 0.020000
Training Epoch: 13 [8960/9756]	Loss: 0.4668	LR: 0.020000
Training Epoch: 13 [9216/9756]	Loss: 0.4751	LR: 0.020000
Training Epoch: 13 [9472/9756]	Loss: 0.4880	LR: 0.020000
Training Epoch: 13 [9728/9756]	Loss: 0.5316	LR: 0.020000
Training Epoch: 13 [9756/9756]	Loss: 0.5955	LR: 0.020000
Epoch 13 - Average Train Loss: 0.5263, Train Accuracy: 0.7460
Epoch 13 training time consumed: 141.09s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0024, Accuracy: 0.7898, Time consumed:7.99s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-13-best.pth
Training Epoch: 14 [256/9756]	Loss: 0.5047	LR: 0.020000
Training Epoch: 14 [512/9756]	Loss: 0.6425	LR: 0.020000
Training Epoch: 14 [768/9756]	Loss: 0.4670	LR: 0.020000
Training Epoch: 14 [1024/9756]	Loss: 0.4678	LR: 0.020000
Training Epoch: 14 [1280/9756]	Loss: 0.4741	LR: 0.020000
Training Epoch: 14 [1536/9756]	Loss: 0.5124	LR: 0.020000
Training Epoch: 14 [1792/9756]	Loss: 0.5302	LR: 0.020000
Training Epoch: 14 [2048/9756]	Loss: 0.5673	LR: 0.020000
Training Epoch: 14 [2304/9756]	Loss: 0.5509	LR: 0.020000
Training Epoch: 14 [2560/9756]	Loss: 0.4890	LR: 0.020000
Training Epoch: 14 [2816/9756]	Loss: 0.5087	LR: 0.020000
Training Epoch: 14 [3072/9756]	Loss: 0.4694	LR: 0.020000
Training Epoch: 14 [3328/9756]	Loss: 0.4522	LR: 0.020000
Training Epoch: 14 [3584/9756]	Loss: 0.4953	LR: 0.020000
Training Epoch: 14 [3840/9756]	Loss: 0.5355	LR: 0.020000
Training Epoch: 14 [4096/9756]	Loss: 0.5383	LR: 0.020000
Training Epoch: 14 [4352/9756]	Loss: 0.4582	LR: 0.020000
Training Epoch: 14 [4608/9756]	Loss: 0.4640	LR: 0.020000
Training Epoch: 14 [4864/9756]	Loss: 0.4397	LR: 0.020000
Training Epoch: 14 [5120/9756]	Loss: 0.4679	LR: 0.020000
Training Epoch: 14 [5376/9756]	Loss: 0.5053	LR: 0.020000
Training Epoch: 14 [5632/9756]	Loss: 0.4142	LR: 0.020000
Training Epoch: 14 [5888/9756]	Loss: 0.4888	LR: 0.020000
Training Epoch: 14 [6144/9756]	Loss: 0.4787	LR: 0.020000
Training Epoch: 14 [6400/9756]	Loss: 0.4745	LR: 0.020000
Training Epoch: 14 [6656/9756]	Loss: 0.4582	LR: 0.020000
Training Epoch: 14 [6912/9756]	Loss: 0.4925	LR: 0.020000
Training Epoch: 14 [7168/9756]	Loss: 0.4240	LR: 0.020000
Training Epoch: 14 [7424/9756]	Loss: 0.4784	LR: 0.020000
Training Epoch: 14 [7680/9756]	Loss: 0.4594	LR: 0.020000
Training Epoch: 14 [7936/9756]	Loss: 0.4321	LR: 0.020000
Training Epoch: 14 [8192/9756]	Loss: 0.4100	LR: 0.020000
Training Epoch: 14 [8448/9756]	Loss: 0.3740	LR: 0.020000
Training Epoch: 14 [8704/9756]	Loss: 0.5139	LR: 0.020000
Training Epoch: 14 [8960/9756]	Loss: 0.4702	LR: 0.020000
Training Epoch: 14 [9216/9756]	Loss: 0.3647	LR: 0.020000
Training Epoch: 14 [9472/9756]	Loss: 0.4279	LR: 0.020000
Training Epoch: 14 [9728/9756]	Loss: 0.3840	LR: 0.020000
Training Epoch: 14 [9756/9756]	Loss: 0.3245	LR: 0.020000
Epoch 14 - Average Train Loss: 0.4755, Train Accuracy: 0.7825
Epoch 14 training time consumed: 141.96s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0022, Accuracy: 0.7676, Time consumed:7.94s
Training Epoch: 15 [256/9756]	Loss: 0.4537	LR: 0.020000
Training Epoch: 15 [512/9756]	Loss: 0.3970	LR: 0.020000
Training Epoch: 15 [768/9756]	Loss: 0.4396	LR: 0.020000
Training Epoch: 15 [1024/9756]	Loss: 0.4373	LR: 0.020000
Training Epoch: 15 [1280/9756]	Loss: 0.3561	LR: 0.020000
Training Epoch: 15 [1536/9756]	Loss: 0.4929	LR: 0.020000
Training Epoch: 15 [1792/9756]	Loss: 0.3843	LR: 0.020000
Training Epoch: 15 [2048/9756]	Loss: 0.4346	LR: 0.020000
Training Epoch: 15 [2304/9756]	Loss: 0.3615	LR: 0.020000
Training Epoch: 15 [2560/9756]	Loss: 0.4391	LR: 0.020000
Training Epoch: 15 [2816/9756]	Loss: 0.4635	LR: 0.020000
Training Epoch: 15 [3072/9756]	Loss: 0.4374	LR: 0.020000
Training Epoch: 15 [3328/9756]	Loss: 0.3692	LR: 0.020000
Training Epoch: 15 [3584/9756]	Loss: 0.3690	LR: 0.020000
Training Epoch: 15 [3840/9756]	Loss: 0.3881	LR: 0.020000
Training Epoch: 15 [4096/9756]	Loss: 0.3836	LR: 0.020000
Training Epoch: 15 [4352/9756]	Loss: 0.3803	LR: 0.020000
Training Epoch: 15 [4608/9756]	Loss: 0.3640	LR: 0.020000
Training Epoch: 15 [4864/9756]	Loss: 0.4501	LR: 0.020000
Training Epoch: 15 [5120/9756]	Loss: 0.3510	LR: 0.020000
Training Epoch: 15 [5376/9756]	Loss: 0.3530	LR: 0.020000
Training Epoch: 15 [5632/9756]	Loss: 0.4357	LR: 0.020000
Training Epoch: 15 [5888/9756]	Loss: 0.4462	LR: 0.020000
Training Epoch: 15 [6144/9756]	Loss: 0.3655	LR: 0.020000
Training Epoch: 15 [6400/9756]	Loss: 0.3494	LR: 0.020000
Training Epoch: 15 [6656/9756]	Loss: 0.3524	LR: 0.020000
Training Epoch: 15 [6912/9756]	Loss: 0.4501	LR: 0.020000
Training Epoch: 15 [7168/9756]	Loss: 0.3001	LR: 0.020000
Training Epoch: 15 [7424/9756]	Loss: 0.3374	LR: 0.020000
Training Epoch: 15 [7680/9756]	Loss: 0.4058	LR: 0.020000
Training Epoch: 15 [7936/9756]	Loss: 0.3944	LR: 0.020000
Training Epoch: 15 [8192/9756]	Loss: 0.3473	LR: 0.020000
Training Epoch: 15 [8448/9756]	Loss: 0.2803	LR: 0.020000
Training Epoch: 15 [8704/9756]	Loss: 0.3679	LR: 0.020000
Training Epoch: 15 [8960/9756]	Loss: 0.4802	LR: 0.020000
Training Epoch: 15 [9216/9756]	Loss: 0.4908	LR: 0.020000
Training Epoch: 15 [9472/9756]	Loss: 0.3681	LR: 0.020000
Training Epoch: 15 [9728/9756]	Loss: 0.5080	LR: 0.020000
Training Epoch: 15 [9756/9756]	Loss: 0.3990	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3996, Train Accuracy: 0.8224
Epoch 15 training time consumed: 141.55s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0019, Accuracy: 0.8116, Time consumed:8.14s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-15-best.pth
Training Epoch: 16 [256/9756]	Loss: 0.3290	LR: 0.020000
Training Epoch: 16 [512/9756]	Loss: 0.3551	LR: 0.020000
Training Epoch: 16 [768/9756]	Loss: 0.4042	LR: 0.020000
Training Epoch: 16 [1024/9756]	Loss: 0.3971	LR: 0.020000
Training Epoch: 16 [1280/9756]	Loss: 0.3897	LR: 0.020000
Training Epoch: 16 [1536/9756]	Loss: 0.4391	LR: 0.020000
Training Epoch: 16 [1792/9756]	Loss: 0.3536	LR: 0.020000
Training Epoch: 16 [2048/9756]	Loss: 0.3367	LR: 0.020000
Training Epoch: 16 [2304/9756]	Loss: 0.3617	LR: 0.020000
Training Epoch: 16 [2560/9756]	Loss: 0.4179	LR: 0.020000
Training Epoch: 16 [2816/9756]	Loss: 0.3226	LR: 0.020000
Training Epoch: 16 [3072/9756]	Loss: 0.3740	LR: 0.020000
Training Epoch: 16 [3328/9756]	Loss: 0.3774	LR: 0.020000
Training Epoch: 16 [3584/9756]	Loss: 0.3330	LR: 0.020000
Training Epoch: 16 [3840/9756]	Loss: 0.3461	LR: 0.020000
Training Epoch: 16 [4096/9756]	Loss: 0.3141	LR: 0.020000
Training Epoch: 16 [4352/9756]	Loss: 0.3882	LR: 0.020000
Training Epoch: 16 [4608/9756]	Loss: 0.3539	LR: 0.020000
Training Epoch: 16 [4864/9756]	Loss: 0.2880	LR: 0.020000
Training Epoch: 16 [5120/9756]	Loss: 0.3380	LR: 0.020000
Training Epoch: 16 [5376/9756]	Loss: 0.3329	LR: 0.020000
Training Epoch: 16 [5632/9756]	Loss: 0.2938	LR: 0.020000
Training Epoch: 16 [5888/9756]	Loss: 0.3212	LR: 0.020000
Training Epoch: 16 [6144/9756]	Loss: 0.3298	LR: 0.020000
Training Epoch: 16 [6400/9756]	Loss: 0.3279	LR: 0.020000
Training Epoch: 16 [6656/9756]	Loss: 0.3306	LR: 0.020000
Training Epoch: 16 [6912/9756]	Loss: 0.3362	LR: 0.020000
Training Epoch: 16 [7168/9756]	Loss: 0.3283	LR: 0.020000
Training Epoch: 16 [7424/9756]	Loss: 0.3453	LR: 0.020000
Training Epoch: 16 [7680/9756]	Loss: 0.3504	LR: 0.020000
Training Epoch: 16 [7936/9756]	Loss: 0.3222	LR: 0.020000
Training Epoch: 16 [8192/9756]	Loss: 0.2973	LR: 0.020000
Training Epoch: 16 [8448/9756]	Loss: 0.3536	LR: 0.020000
Training Epoch: 16 [8704/9756]	Loss: 0.2987	LR: 0.020000
Training Epoch: 16 [8960/9756]	Loss: 0.3065	LR: 0.020000
Training Epoch: 16 [9216/9756]	Loss: 0.2726	LR: 0.020000
Training Epoch: 16 [9472/9756]	Loss: 0.3103	LR: 0.020000
Training Epoch: 16 [9728/9756]	Loss: 0.2757	LR: 0.020000
Training Epoch: 16 [9756/9756]	Loss: 0.2673	LR: 0.020000
Epoch 16 - Average Train Loss: 0.3407, Train Accuracy: 0.8533
Epoch 16 training time consumed: 141.28s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0017, Accuracy: 0.8383, Time consumed:8.09s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-16-best.pth
Training Epoch: 17 [256/9756]	Loss: 0.3375	LR: 0.020000
Training Epoch: 17 [512/9756]	Loss: 0.4086	LR: 0.020000
Training Epoch: 17 [768/9756]	Loss: 0.4454	LR: 0.020000
Training Epoch: 17 [1024/9756]	Loss: 0.4201	LR: 0.020000
Training Epoch: 17 [1280/9756]	Loss: 0.2924	LR: 0.020000
Training Epoch: 17 [1536/9756]	Loss: 0.3559	LR: 0.020000
Training Epoch: 17 [1792/9756]	Loss: 0.3442	LR: 0.020000
Training Epoch: 17 [2048/9756]	Loss: 0.3658	LR: 0.020000
Training Epoch: 17 [2304/9756]	Loss: 0.3573	LR: 0.020000
Training Epoch: 17 [2560/9756]	Loss: 0.3739	LR: 0.020000
Training Epoch: 17 [2816/9756]	Loss: 0.2612	LR: 0.020000
Training Epoch: 17 [3072/9756]	Loss: 0.3280	LR: 0.020000
Training Epoch: 17 [3328/9756]	Loss: 0.3597	LR: 0.020000
Training Epoch: 17 [3584/9756]	Loss: 0.3938	LR: 0.020000
Training Epoch: 17 [3840/9756]	Loss: 0.3413	LR: 0.020000
Training Epoch: 17 [4096/9756]	Loss: 0.3272	LR: 0.020000
Training Epoch: 17 [4352/9756]	Loss: 0.3288	LR: 0.020000
Training Epoch: 17 [4608/9756]	Loss: 0.3071	LR: 0.020000
Training Epoch: 17 [4864/9756]	Loss: 0.2835	LR: 0.020000
Training Epoch: 17 [5120/9756]	Loss: 0.2968	LR: 0.020000
Training Epoch: 17 [5376/9756]	Loss: 0.3083	LR: 0.020000
Training Epoch: 17 [5632/9756]	Loss: 0.2759	LR: 0.020000
Training Epoch: 17 [5888/9756]	Loss: 0.2319	LR: 0.020000
Training Epoch: 17 [6144/9756]	Loss: 0.2949	LR: 0.020000
Training Epoch: 17 [6400/9756]	Loss: 0.2559	LR: 0.020000
Training Epoch: 17 [6656/9756]	Loss: 0.3016	LR: 0.020000
Training Epoch: 17 [6912/9756]	Loss: 0.3702	LR: 0.020000
Training Epoch: 17 [7168/9756]	Loss: 0.2787	LR: 0.020000
Training Epoch: 17 [7424/9756]	Loss: 0.3200	LR: 0.020000
Training Epoch: 17 [7680/9756]	Loss: 0.2163	LR: 0.020000
Training Epoch: 17 [7936/9756]	Loss: 0.2840	LR: 0.020000
Training Epoch: 17 [8192/9756]	Loss: 0.2534	LR: 0.020000
Training Epoch: 17 [8448/9756]	Loss: 0.2857	LR: 0.020000
Training Epoch: 17 [8704/9756]	Loss: 0.2542	LR: 0.020000
Training Epoch: 17 [8960/9756]	Loss: 0.2864	LR: 0.020000
Training Epoch: 17 [9216/9756]	Loss: 0.2740	LR: 0.020000
Training Epoch: 17 [9472/9756]	Loss: 0.2677	LR: 0.020000
Training Epoch: 17 [9728/9756]	Loss: 0.2233	LR: 0.020000
Training Epoch: 17 [9756/9756]	Loss: 0.7045	LR: 0.020000
Epoch 17 - Average Train Loss: 0.3146, Train Accuracy: 0.8680
Epoch 17 training time consumed: 141.68s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0017, Accuracy: 0.8242, Time consumed:8.04s
Training Epoch: 18 [256/9756]	Loss: 0.3294	LR: 0.020000
Training Epoch: 18 [512/9756]	Loss: 0.2696	LR: 0.020000
Training Epoch: 18 [768/9756]	Loss: 0.3650	LR: 0.020000
Training Epoch: 18 [1024/9756]	Loss: 0.2509	LR: 0.020000
Training Epoch: 18 [1280/9756]	Loss: 0.3483	LR: 0.020000
Training Epoch: 18 [1536/9756]	Loss: 0.2866	LR: 0.020000
Training Epoch: 18 [1792/9756]	Loss: 0.3295	LR: 0.020000
Training Epoch: 18 [2048/9756]	Loss: 0.4037	LR: 0.020000
Training Epoch: 18 [2304/9756]	Loss: 0.3273	LR: 0.020000
Training Epoch: 18 [2560/9756]	Loss: 0.3372	LR: 0.020000
Training Epoch: 18 [2816/9756]	Loss: 0.2783	LR: 0.020000
Training Epoch: 18 [3072/9756]	Loss: 0.2358	LR: 0.020000
Training Epoch: 18 [3328/9756]	Loss: 0.3050	LR: 0.020000
Training Epoch: 18 [3584/9756]	Loss: 0.2519	LR: 0.020000
Training Epoch: 18 [3840/9756]	Loss: 0.2727	LR: 0.020000
Training Epoch: 18 [4096/9756]	Loss: 0.2734	LR: 0.020000
Training Epoch: 18 [4352/9756]	Loss: 0.2913	LR: 0.020000
Training Epoch: 18 [4608/9756]	Loss: 0.2435	LR: 0.020000
Training Epoch: 18 [4864/9756]	Loss: 0.3117	LR: 0.020000
Training Epoch: 18 [5120/9756]	Loss: 0.2503	LR: 0.020000
Training Epoch: 18 [5376/9756]	Loss: 0.2730	LR: 0.020000
Training Epoch: 18 [5632/9756]	Loss: 0.2946	LR: 0.020000
Training Epoch: 18 [5888/9756]	Loss: 0.2568	LR: 0.020000
Training Epoch: 18 [6144/9756]	Loss: 0.2338	LR: 0.020000
Training Epoch: 18 [6400/9756]	Loss: 0.2379	LR: 0.020000
Training Epoch: 18 [6656/9756]	Loss: 0.2760	LR: 0.020000
Training Epoch: 18 [6912/9756]	Loss: 0.2821	LR: 0.020000
Training Epoch: 18 [7168/9756]	Loss: 0.2605	LR: 0.020000
Training Epoch: 18 [7424/9756]	Loss: 0.3135	LR: 0.020000
Training Epoch: 18 [7680/9756]	Loss: 0.2299	LR: 0.020000
Training Epoch: 18 [7936/9756]	Loss: 0.2220	LR: 0.020000
Training Epoch: 18 [8192/9756]	Loss: 0.2086	LR: 0.020000
Training Epoch: 18 [8448/9756]	Loss: 0.2526	LR: 0.020000
Training Epoch: 18 [8704/9756]	Loss: 0.2586	LR: 0.020000
Training Epoch: 18 [8960/9756]	Loss: 0.2468	LR: 0.020000
Training Epoch: 18 [9216/9756]	Loss: 0.2158	LR: 0.020000
Training Epoch: 18 [9472/9756]	Loss: 0.3493	LR: 0.020000
Training Epoch: 18 [9728/9756]	Loss: 0.2861	LR: 0.020000
Training Epoch: 18 [9756/9756]	Loss: 0.1034	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2800, Train Accuracy: 0.8820
Epoch 18 training time consumed: 141.55s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0018, Accuracy: 0.8402, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-18-best.pth
Training Epoch: 19 [256/9756]	Loss: 0.2170	LR: 0.020000
Training Epoch: 19 [512/9756]	Loss: 0.2466	LR: 0.020000
Training Epoch: 19 [768/9756]	Loss: 0.3111	LR: 0.020000
Training Epoch: 19 [1024/9756]	Loss: 0.2214	LR: 0.020000
Training Epoch: 19 [1280/9756]	Loss: 0.1975	LR: 0.020000
Training Epoch: 19 [1536/9756]	Loss: 0.3561	LR: 0.020000
Training Epoch: 19 [1792/9756]	Loss: 0.2270	LR: 0.020000
Training Epoch: 19 [2048/9756]	Loss: 0.2407	LR: 0.020000
Training Epoch: 19 [2304/9756]	Loss: 0.2387	LR: 0.020000
Training Epoch: 19 [2560/9756]	Loss: 0.2156	LR: 0.020000
Training Epoch: 19 [2816/9756]	Loss: 0.2131	LR: 0.020000
Training Epoch: 19 [3072/9756]	Loss: 0.1886	LR: 0.020000
Training Epoch: 19 [3328/9756]	Loss: 0.2314	LR: 0.020000
Training Epoch: 19 [3584/9756]	Loss: 0.3126	LR: 0.020000
Training Epoch: 19 [3840/9756]	Loss: 0.2222	LR: 0.020000
Training Epoch: 19 [4096/9756]	Loss: 0.1721	LR: 0.020000
Training Epoch: 19 [4352/9756]	Loss: 0.2755	LR: 0.020000
Training Epoch: 19 [4608/9756]	Loss: 0.2420	LR: 0.020000
Training Epoch: 19 [4864/9756]	Loss: 0.2294	LR: 0.020000
Training Epoch: 19 [5120/9756]	Loss: 0.2678	LR: 0.020000
Training Epoch: 19 [5376/9756]	Loss: 0.2543	LR: 0.020000
Training Epoch: 19 [5632/9756]	Loss: 0.1896	LR: 0.020000
Training Epoch: 19 [5888/9756]	Loss: 0.2128	LR: 0.020000
Training Epoch: 19 [6144/9756]	Loss: 0.2763	LR: 0.020000
Training Epoch: 19 [6400/9756]	Loss: 0.2181	LR: 0.020000
Training Epoch: 19 [6656/9756]	Loss: 0.2359	LR: 0.020000
Training Epoch: 19 [6912/9756]	Loss: 0.2578	LR: 0.020000
Training Epoch: 19 [7168/9756]	Loss: 0.1707	LR: 0.020000
Training Epoch: 19 [7424/9756]	Loss: 0.2551	LR: 0.020000
Training Epoch: 19 [7680/9756]	Loss: 0.1489	LR: 0.020000
Training Epoch: 19 [7936/9756]	Loss: 0.2067	LR: 0.020000
Training Epoch: 19 [8192/9756]	Loss: 0.1877	LR: 0.020000
Training Epoch: 19 [8448/9756]	Loss: 0.1769	LR: 0.020000
Training Epoch: 19 [8704/9756]	Loss: 0.2583	LR: 0.020000
Training Epoch: 19 [8960/9756]	Loss: 0.2153	LR: 0.020000
Training Epoch: 19 [9216/9756]	Loss: 0.1791	LR: 0.020000
Training Epoch: 19 [9472/9756]	Loss: 0.2183	LR: 0.020000
Training Epoch: 19 [9728/9756]	Loss: 0.2097	LR: 0.020000
Training Epoch: 19 [9756/9756]	Loss: 0.2466	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2289, Train Accuracy: 0.9047
Epoch 19 training time consumed: 141.51s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0008, Accuracy: 0.9264, Time consumed:8.11s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-19-best.pth
Training Epoch: 20 [256/9756]	Loss: 0.2142	LR: 0.004000
Training Epoch: 20 [512/9756]	Loss: 0.2351	LR: 0.004000
Training Epoch: 20 [768/9756]	Loss: 0.2063	LR: 0.004000
Training Epoch: 20 [1024/9756]	Loss: 0.2527	LR: 0.004000
Training Epoch: 20 [1280/9756]	Loss: 0.1946	LR: 0.004000
Training Epoch: 20 [1536/9756]	Loss: 0.1977	LR: 0.004000
Training Epoch: 20 [1792/9756]	Loss: 0.1509	LR: 0.004000
Training Epoch: 20 [2048/9756]	Loss: 0.1865	LR: 0.004000
Training Epoch: 20 [2304/9756]	Loss: 0.2318	LR: 0.004000
Training Epoch: 20 [2560/9756]	Loss: 0.2185	LR: 0.004000
Training Epoch: 20 [2816/9756]	Loss: 0.2142	LR: 0.004000
Training Epoch: 20 [3072/9756]	Loss: 0.1736	LR: 0.004000
Training Epoch: 20 [3328/9756]	Loss: 0.1665	LR: 0.004000
Training Epoch: 20 [3584/9756]	Loss: 0.2026	LR: 0.004000
Training Epoch: 20 [3840/9756]	Loss: 0.1449	LR: 0.004000
Training Epoch: 20 [4096/9756]	Loss: 0.2030	LR: 0.004000
Training Epoch: 20 [4352/9756]	Loss: 0.2418	LR: 0.004000
Training Epoch: 20 [4608/9756]	Loss: 0.1937	LR: 0.004000
Training Epoch: 20 [4864/9756]	Loss: 0.2048	LR: 0.004000
Training Epoch: 20 [5120/9756]	Loss: 0.1878	LR: 0.004000
Training Epoch: 20 [5376/9756]	Loss: 0.1462	LR: 0.004000
Training Epoch: 20 [5632/9756]	Loss: 0.2185	LR: 0.004000
Training Epoch: 20 [5888/9756]	Loss: 0.2373	LR: 0.004000
Training Epoch: 20 [6144/9756]	Loss: 0.2113	LR: 0.004000
Training Epoch: 20 [6400/9756]	Loss: 0.2232	LR: 0.004000
Training Epoch: 20 [6656/9756]	Loss: 0.1724	LR: 0.004000
Training Epoch: 20 [6912/9756]	Loss: 0.1875	LR: 0.004000
Training Epoch: 20 [7168/9756]	Loss: 0.1893	LR: 0.004000
Training Epoch: 20 [7424/9756]	Loss: 0.1433	LR: 0.004000
Training Epoch: 20 [7680/9756]	Loss: 0.1782	LR: 0.004000
Training Epoch: 20 [7936/9756]	Loss: 0.2003	LR: 0.004000
Training Epoch: 20 [8192/9756]	Loss: 0.1557	LR: 0.004000
Training Epoch: 20 [8448/9756]	Loss: 0.1817	LR: 0.004000
Training Epoch: 20 [8704/9756]	Loss: 0.2103	LR: 0.004000
Training Epoch: 20 [8960/9756]	Loss: 0.1531	LR: 0.004000
Training Epoch: 20 [9216/9756]	Loss: 0.1729	LR: 0.004000
Training Epoch: 20 [9472/9756]	Loss: 0.2132	LR: 0.004000
Training Epoch: 20 [9728/9756]	Loss: 0.1900	LR: 0.004000
Training Epoch: 20 [9756/9756]	Loss: 0.1294	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1947, Train Accuracy: 0.9180
Epoch 20 training time consumed: 141.68s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0007, Accuracy: 0.9278, Time consumed:8.04s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-20-best.pth
Training Epoch: 21 [256/9756]	Loss: 0.1916	LR: 0.004000
Training Epoch: 21 [512/9756]	Loss: 0.1538	LR: 0.004000
Training Epoch: 21 [768/9756]	Loss: 0.1312	LR: 0.004000
Training Epoch: 21 [1024/9756]	Loss: 0.1518	LR: 0.004000
Training Epoch: 21 [1280/9756]	Loss: 0.1585	LR: 0.004000
Training Epoch: 21 [1536/9756]	Loss: 0.1882	LR: 0.004000
Training Epoch: 21 [1792/9756]	Loss: 0.1766	LR: 0.004000
Training Epoch: 21 [2048/9756]	Loss: 0.1770	LR: 0.004000
Training Epoch: 21 [2304/9756]	Loss: 0.1673	LR: 0.004000
Training Epoch: 21 [2560/9756]	Loss: 0.1390	LR: 0.004000
Training Epoch: 21 [2816/9756]	Loss: 0.1735	LR: 0.004000
Training Epoch: 21 [3072/9756]	Loss: 0.2994	LR: 0.004000
Training Epoch: 21 [3328/9756]	Loss: 0.1921	LR: 0.004000
Training Epoch: 21 [3584/9756]	Loss: 0.2306	LR: 0.004000
Training Epoch: 21 [3840/9756]	Loss: 0.1611	LR: 0.004000
Training Epoch: 21 [4096/9756]	Loss: 0.1881	LR: 0.004000
Training Epoch: 21 [4352/9756]	Loss: 0.1758	LR: 0.004000
Training Epoch: 21 [4608/9756]	Loss: 0.2327	LR: 0.004000
Training Epoch: 21 [4864/9756]	Loss: 0.2106	LR: 0.004000
Training Epoch: 21 [5120/9756]	Loss: 0.1914	LR: 0.004000
Training Epoch: 21 [5376/9756]	Loss: 0.2202	LR: 0.004000
Training Epoch: 21 [5632/9756]	Loss: 0.1613	LR: 0.004000
Training Epoch: 21 [5888/9756]	Loss: 0.2301	LR: 0.004000
Training Epoch: 21 [6144/9756]	Loss: 0.1497	LR: 0.004000
Training Epoch: 21 [6400/9756]	Loss: 0.2292	LR: 0.004000
Training Epoch: 21 [6656/9756]	Loss: 0.1907	LR: 0.004000
Training Epoch: 21 [6912/9756]	Loss: 0.1443	LR: 0.004000
Training Epoch: 21 [7168/9756]	Loss: 0.2271	LR: 0.004000
Training Epoch: 21 [7424/9756]	Loss: 0.1469	LR: 0.004000
Training Epoch: 21 [7680/9756]	Loss: 0.1749	LR: 0.004000
Training Epoch: 21 [7936/9756]	Loss: 0.1556	LR: 0.004000
Training Epoch: 21 [8192/9756]	Loss: 0.2154	LR: 0.004000
Training Epoch: 21 [8448/9756]	Loss: 0.1639	LR: 0.004000
Training Epoch: 21 [8704/9756]	Loss: 0.1956	LR: 0.004000
Training Epoch: 21 [8960/9756]	Loss: 0.2017	LR: 0.004000
Training Epoch: 21 [9216/9756]	Loss: 0.2219	LR: 0.004000
Training Epoch: 21 [9472/9756]	Loss: 0.1492	LR: 0.004000
Training Epoch: 21 [9728/9756]	Loss: 0.2008	LR: 0.004000
Training Epoch: 21 [9756/9756]	Loss: 0.1745	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1860, Train Accuracy: 0.9200
Epoch 21 training time consumed: 141.66s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0007, Accuracy: 0.9346, Time consumed:8.07s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-21-best.pth
Training Epoch: 22 [256/9756]	Loss: 0.1432	LR: 0.004000
Training Epoch: 22 [512/9756]	Loss: 0.1928	LR: 0.004000
Training Epoch: 22 [768/9756]	Loss: 0.1403	LR: 0.004000
Training Epoch: 22 [1024/9756]	Loss: 0.1229	LR: 0.004000
Training Epoch: 22 [1280/9756]	Loss: 0.1389	LR: 0.004000
Training Epoch: 22 [1536/9756]	Loss: 0.1767	LR: 0.004000
Training Epoch: 22 [1792/9756]	Loss: 0.1904	LR: 0.004000
Training Epoch: 22 [2048/9756]	Loss: 0.1445	LR: 0.004000
Training Epoch: 22 [2304/9756]	Loss: 0.2473	LR: 0.004000
Training Epoch: 22 [2560/9756]	Loss: 0.2268	LR: 0.004000
Training Epoch: 22 [2816/9756]	Loss: 0.2022	LR: 0.004000
Training Epoch: 22 [3072/9756]	Loss: 0.1361	LR: 0.004000
Training Epoch: 22 [3328/9756]	Loss: 0.1821	LR: 0.004000
Training Epoch: 22 [3584/9756]	Loss: 0.1680	LR: 0.004000
Training Epoch: 22 [3840/9756]	Loss: 0.1607	LR: 0.004000
Training Epoch: 22 [4096/9756]	Loss: 0.1665	LR: 0.004000
Training Epoch: 22 [4352/9756]	Loss: 0.2091	LR: 0.004000
Training Epoch: 22 [4608/9756]	Loss: 0.1461	LR: 0.004000
Training Epoch: 22 [4864/9756]	Loss: 0.1760	LR: 0.004000
Training Epoch: 22 [5120/9756]	Loss: 0.2201	LR: 0.004000
Training Epoch: 22 [5376/9756]	Loss: 0.1978	LR: 0.004000
Training Epoch: 22 [5632/9756]	Loss: 0.2036	LR: 0.004000
Training Epoch: 22 [5888/9756]	Loss: 0.1948	LR: 0.004000
Training Epoch: 22 [6144/9756]	Loss: 0.1837	LR: 0.004000
Training Epoch: 22 [6400/9756]	Loss: 0.1926	LR: 0.004000
Training Epoch: 22 [6656/9756]	Loss: 0.1761	LR: 0.004000
Training Epoch: 22 [6912/9756]	Loss: 0.1466	LR: 0.004000
Training Epoch: 22 [7168/9756]	Loss: 0.2068	LR: 0.004000
Training Epoch: 22 [7424/9756]	Loss: 0.2259	LR: 0.004000
Training Epoch: 22 [7680/9756]	Loss: 0.2995	LR: 0.004000
Training Epoch: 22 [7936/9756]	Loss: 0.1959	LR: 0.004000
Training Epoch: 22 [8192/9756]	Loss: 0.1953	LR: 0.004000
Training Epoch: 22 [8448/9756]	Loss: 0.1874	LR: 0.004000
Training Epoch: 22 [8704/9756]	Loss: 0.1434	LR: 0.004000
Training Epoch: 22 [8960/9756]	Loss: 0.1948	LR: 0.004000
Training Epoch: 22 [9216/9756]	Loss: 0.1481	LR: 0.004000
Training Epoch: 22 [9472/9756]	Loss: 0.2498	LR: 0.004000
Training Epoch: 22 [9728/9756]	Loss: 0.1864	LR: 0.004000
Training Epoch: 22 [9756/9756]	Loss: 0.0971	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1845, Train Accuracy: 0.9241
Epoch 22 training time consumed: 141.42s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0007, Accuracy: 0.9327, Time consumed:8.21s
Training Epoch: 23 [256/9756]	Loss: 0.1566	LR: 0.004000
Training Epoch: 23 [512/9756]	Loss: 0.1417	LR: 0.004000
Training Epoch: 23 [768/9756]	Loss: 0.1662	LR: 0.004000
Training Epoch: 23 [1024/9756]	Loss: 0.1323	LR: 0.004000
Training Epoch: 23 [1280/9756]	Loss: 0.1680	LR: 0.004000
Training Epoch: 23 [1536/9756]	Loss: 0.1834	LR: 0.004000
Training Epoch: 23 [1792/9756]	Loss: 0.2210	LR: 0.004000
Training Epoch: 23 [2048/9756]	Loss: 0.1706	LR: 0.004000
Training Epoch: 23 [2304/9756]	Loss: 0.1981	LR: 0.004000
Training Epoch: 23 [2560/9756]	Loss: 0.1735	LR: 0.004000
Training Epoch: 23 [2816/9756]	Loss: 0.1501	LR: 0.004000
Training Epoch: 23 [3072/9756]	Loss: 0.1586	LR: 0.004000
Training Epoch: 23 [3328/9756]	Loss: 0.1250	LR: 0.004000
Training Epoch: 23 [3584/9756]	Loss: 0.1679	LR: 0.004000
Training Epoch: 23 [3840/9756]	Loss: 0.2359	LR: 0.004000
Training Epoch: 23 [4096/9756]	Loss: 0.1321	LR: 0.004000
Training Epoch: 23 [4352/9756]	Loss: 0.1694	LR: 0.004000
Training Epoch: 23 [4608/9756]	Loss: 0.1066	LR: 0.004000
Training Epoch: 23 [4864/9756]	Loss: 0.1957	LR: 0.004000
Training Epoch: 23 [5120/9756]	Loss: 0.2353	LR: 0.004000
Training Epoch: 23 [5376/9756]	Loss: 0.1482	LR: 0.004000
Training Epoch: 23 [5632/9756]	Loss: 0.1747	LR: 0.004000
Training Epoch: 23 [5888/9756]	Loss: 0.1773	LR: 0.004000
Training Epoch: 23 [6144/9756]	Loss: 0.1658	LR: 0.004000
Training Epoch: 23 [6400/9756]	Loss: 0.1387	LR: 0.004000
Training Epoch: 23 [6656/9756]	Loss: 0.1283	LR: 0.004000
Training Epoch: 23 [6912/9756]	Loss: 0.1542	LR: 0.004000
Training Epoch: 23 [7168/9756]	Loss: 0.1986	LR: 0.004000
Training Epoch: 23 [7424/9756]	Loss: 0.1658	LR: 0.004000
Training Epoch: 23 [7680/9756]	Loss: 0.2119	LR: 0.004000
Training Epoch: 23 [7936/9756]	Loss: 0.1602	LR: 0.004000
Training Epoch: 23 [8192/9756]	Loss: 0.1856	LR: 0.004000
Training Epoch: 23 [8448/9756]	Loss: 0.1613	LR: 0.004000
Training Epoch: 23 [8704/9756]	Loss: 0.1982	LR: 0.004000
Training Epoch: 23 [8960/9756]	Loss: 0.1210	LR: 0.004000
Training Epoch: 23 [9216/9756]	Loss: 0.1477	LR: 0.004000
Training Epoch: 23 [9472/9756]	Loss: 0.1811	LR: 0.004000
Training Epoch: 23 [9728/9756]	Loss: 0.1956	LR: 0.004000
Training Epoch: 23 [9756/9756]	Loss: 0.2027	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1686, Train Accuracy: 0.9314
Epoch 23 training time consumed: 141.84s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0007, Accuracy: 0.9308, Time consumed:7.95s
Training Epoch: 24 [256/9756]	Loss: 0.1401	LR: 0.004000
Training Epoch: 24 [512/9756]	Loss: 0.1667	LR: 0.004000
Training Epoch: 24 [768/9756]	Loss: 0.1893	LR: 0.004000
Training Epoch: 24 [1024/9756]	Loss: 0.2166	LR: 0.004000
Training Epoch: 24 [1280/9756]	Loss: 0.2126	LR: 0.004000
Training Epoch: 24 [1536/9756]	Loss: 0.1929	LR: 0.004000
Training Epoch: 24 [1792/9756]	Loss: 0.2029	LR: 0.004000
Training Epoch: 24 [2048/9756]	Loss: 0.1553	LR: 0.004000
Training Epoch: 24 [2304/9756]	Loss: 0.1973	LR: 0.004000
Training Epoch: 24 [2560/9756]	Loss: 0.1474	LR: 0.004000
Training Epoch: 24 [2816/9756]	Loss: 0.1331	LR: 0.004000
Training Epoch: 24 [3072/9756]	Loss: 0.1281	LR: 0.004000
Training Epoch: 24 [3328/9756]	Loss: 0.1648	LR: 0.004000
Training Epoch: 24 [3584/9756]	Loss: 0.1770	LR: 0.004000
Training Epoch: 24 [3840/9756]	Loss: 0.1494	LR: 0.004000
Training Epoch: 24 [4096/9756]	Loss: 0.1872	LR: 0.004000
Training Epoch: 24 [4352/9756]	Loss: 0.1287	LR: 0.004000
Training Epoch: 24 [4608/9756]	Loss: 0.1791	LR: 0.004000
Training Epoch: 24 [4864/9756]	Loss: 0.1338	LR: 0.004000
Training Epoch: 24 [5120/9756]	Loss: 0.1689	LR: 0.004000
Training Epoch: 24 [5376/9756]	Loss: 0.1768	LR: 0.004000
Training Epoch: 24 [5632/9756]	Loss: 0.1879	LR: 0.004000
Training Epoch: 24 [5888/9756]	Loss: 0.1561	LR: 0.004000
Training Epoch: 24 [6144/9756]	Loss: 0.2123	LR: 0.004000
Training Epoch: 24 [6400/9756]	Loss: 0.1267	LR: 0.004000
Training Epoch: 24 [6656/9756]	Loss: 0.2302	LR: 0.004000
Training Epoch: 24 [6912/9756]	Loss: 0.1781	LR: 0.004000
Training Epoch: 24 [7168/9756]	Loss: 0.1398	LR: 0.004000
Training Epoch: 24 [7424/9756]	Loss: 0.1691	LR: 0.004000
Training Epoch: 24 [7680/9756]	Loss: 0.1432	LR: 0.004000
Training Epoch: 24 [7936/9756]	Loss: 0.1720	LR: 0.004000
Training Epoch: 24 [8192/9756]	Loss: 0.1924	LR: 0.004000
Training Epoch: 24 [8448/9756]	Loss: 0.1497	LR: 0.004000
Training Epoch: 24 [8704/9756]	Loss: 0.1554	LR: 0.004000
Training Epoch: 24 [8960/9756]	Loss: 0.2461	LR: 0.004000
Training Epoch: 24 [9216/9756]	Loss: 0.2098	LR: 0.004000
Training Epoch: 24 [9472/9756]	Loss: 0.1375	LR: 0.004000
Training Epoch: 24 [9728/9756]	Loss: 0.1570	LR: 0.004000
Training Epoch: 24 [9756/9756]	Loss: 0.0498	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1710, Train Accuracy: 0.9297
Epoch 24 training time consumed: 141.52s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0007, Accuracy: 0.9312, Time consumed:8.07s
Training Epoch: 25 [256/9756]	Loss: 0.1326	LR: 0.004000
Training Epoch: 25 [512/9756]	Loss: 0.1830	LR: 0.004000
Training Epoch: 25 [768/9756]	Loss: 0.1781	LR: 0.004000
Training Epoch: 25 [1024/9756]	Loss: 0.1982	LR: 0.004000
Training Epoch: 25 [1280/9756]	Loss: 0.1645	LR: 0.004000
Training Epoch: 25 [1536/9756]	Loss: 0.1831	LR: 0.004000
Training Epoch: 25 [1792/9756]	Loss: 0.1833	LR: 0.004000
Training Epoch: 25 [2048/9756]	Loss: 0.1776	LR: 0.004000
Training Epoch: 25 [2304/9756]	Loss: 0.1535	LR: 0.004000
Training Epoch: 25 [2560/9756]	Loss: 0.1820	LR: 0.004000
Training Epoch: 25 [2816/9756]	Loss: 0.1749	LR: 0.004000
Training Epoch: 25 [3072/9756]	Loss: 0.1272	LR: 0.004000
Training Epoch: 25 [3328/9756]	Loss: 0.1277	LR: 0.004000
Training Epoch: 25 [3584/9756]	Loss: 0.1608	LR: 0.004000
Training Epoch: 25 [3840/9756]	Loss: 0.1450	LR: 0.004000
Training Epoch: 25 [4096/9756]	Loss: 0.1838	LR: 0.004000
Training Epoch: 25 [4352/9756]	Loss: 0.1653	LR: 0.004000
Training Epoch: 25 [4608/9756]	Loss: 0.1738	LR: 0.004000
Training Epoch: 25 [4864/9756]	Loss: 0.1896	LR: 0.004000
Training Epoch: 25 [5120/9756]	Loss: 0.1891	LR: 0.004000
Training Epoch: 25 [5376/9756]	Loss: 0.1569	LR: 0.004000
Training Epoch: 25 [5632/9756]	Loss: 0.1521	LR: 0.004000
Training Epoch: 25 [5888/9756]	Loss: 0.1406	LR: 0.004000
Training Epoch: 25 [6144/9756]	Loss: 0.1716	LR: 0.004000
Training Epoch: 25 [6400/9756]	Loss: 0.1266	LR: 0.004000
Training Epoch: 25 [6656/9756]	Loss: 0.2146	LR: 0.004000
Training Epoch: 25 [6912/9756]	Loss: 0.1688	LR: 0.004000
Training Epoch: 25 [7168/9756]	Loss: 0.1380	LR: 0.004000
Training Epoch: 25 [7424/9756]	Loss: 0.1694	LR: 0.004000
Training Epoch: 25 [7680/9756]	Loss: 0.1909	LR: 0.004000
Training Epoch: 25 [7936/9756]	Loss: 0.1427	LR: 0.004000
Training Epoch: 25 [8192/9756]	Loss: 0.1989	LR: 0.004000
Training Epoch: 25 [8448/9756]	Loss: 0.1846	LR: 0.004000
Training Epoch: 25 [8704/9756]	Loss: 0.1461	LR: 0.004000
Training Epoch: 25 [8960/9756]	Loss: 0.1327	LR: 0.004000
Training Epoch: 25 [9216/9756]	Loss: 0.1644	LR: 0.004000
Training Epoch: 25 [9472/9756]	Loss: 0.1484	LR: 0.004000
Training Epoch: 25 [9728/9756]	Loss: 0.1941	LR: 0.004000
Training Epoch: 25 [9756/9756]	Loss: 0.1064	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1660, Train Accuracy: 0.9321
Epoch 25 training time consumed: 142.52s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0007, Accuracy: 0.9351, Time consumed:8.10s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-25-best.pth
Training Epoch: 26 [256/9756]	Loss: 0.1360	LR: 0.004000
Training Epoch: 26 [512/9756]	Loss: 0.1260	LR: 0.004000
Training Epoch: 26 [768/9756]	Loss: 0.1894	LR: 0.004000
Training Epoch: 26 [1024/9756]	Loss: 0.1867	LR: 0.004000
Training Epoch: 26 [1280/9756]	Loss: 0.1786	LR: 0.004000
Training Epoch: 26 [1536/9756]	Loss: 0.2205	LR: 0.004000
Training Epoch: 26 [1792/9756]	Loss: 0.2029	LR: 0.004000
Training Epoch: 26 [2048/9756]	Loss: 0.1866	LR: 0.004000
Training Epoch: 26 [2304/9756]	Loss: 0.1709	LR: 0.004000
Training Epoch: 26 [2560/9756]	Loss: 0.1336	LR: 0.004000
Training Epoch: 26 [2816/9756]	Loss: 0.1835	LR: 0.004000
Training Epoch: 26 [3072/9756]	Loss: 0.1661	LR: 0.004000
Training Epoch: 26 [3328/9756]	Loss: 0.1613	LR: 0.004000
Training Epoch: 26 [3584/9756]	Loss: 0.1895	LR: 0.004000
Training Epoch: 26 [3840/9756]	Loss: 0.1421	LR: 0.004000
Training Epoch: 26 [4096/9756]	Loss: 0.2032	LR: 0.004000
Training Epoch: 26 [4352/9756]	Loss: 0.1289	LR: 0.004000
Training Epoch: 26 [4608/9756]	Loss: 0.1494	LR: 0.004000
Training Epoch: 26 [4864/9756]	Loss: 0.1279	LR: 0.004000
Training Epoch: 26 [5120/9756]	Loss: 0.1740	LR: 0.004000
Training Epoch: 26 [5376/9756]	Loss: 0.1643	LR: 0.004000
Training Epoch: 26 [5632/9756]	Loss: 0.1556	LR: 0.004000
Training Epoch: 26 [5888/9756]	Loss: 0.1777	LR: 0.004000
Training Epoch: 26 [6144/9756]	Loss: 0.1561	LR: 0.004000
Training Epoch: 26 [6400/9756]	Loss: 0.2047	LR: 0.004000
Training Epoch: 26 [6656/9756]	Loss: 0.1404	LR: 0.004000
Training Epoch: 26 [6912/9756]	Loss: 0.1404	LR: 0.004000
Training Epoch: 26 [7168/9756]	Loss: 0.1651	LR: 0.004000
Training Epoch: 26 [7424/9756]	Loss: 0.1783	LR: 0.004000
Training Epoch: 26 [7680/9756]	Loss: 0.1343	LR: 0.004000
Training Epoch: 26 [7936/9756]	Loss: 0.1143	LR: 0.004000
Training Epoch: 26 [8192/9756]	Loss: 0.1837	LR: 0.004000
Training Epoch: 26 [8448/9756]	Loss: 0.1785	LR: 0.004000
Training Epoch: 26 [8704/9756]	Loss: 0.1707	LR: 0.004000
Training Epoch: 26 [8960/9756]	Loss: 0.1288	LR: 0.004000
Training Epoch: 26 [9216/9756]	Loss: 0.1737	LR: 0.004000
Training Epoch: 26 [9472/9756]	Loss: 0.1650	LR: 0.004000
Training Epoch: 26 [9728/9756]	Loss: 0.1457	LR: 0.004000
Training Epoch: 26 [9756/9756]	Loss: 0.1539	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1640, Train Accuracy: 0.9315
Epoch 26 training time consumed: 142.48s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0008, Accuracy: 0.9298, Time consumed:8.04s
Training Epoch: 27 [256/9756]	Loss: 0.1629	LR: 0.004000
Training Epoch: 27 [512/9756]	Loss: 0.1931	LR: 0.004000
Training Epoch: 27 [768/9756]	Loss: 0.1190	LR: 0.004000
Training Epoch: 27 [1024/9756]	Loss: 0.1512	LR: 0.004000
Training Epoch: 27 [1280/9756]	Loss: 0.1863	LR: 0.004000
Training Epoch: 27 [1536/9756]	Loss: 0.1708	LR: 0.004000
Training Epoch: 27 [1792/9756]	Loss: 0.1900	LR: 0.004000
Training Epoch: 27 [2048/9756]	Loss: 0.1369	LR: 0.004000
Training Epoch: 27 [2304/9756]	Loss: 0.1374	LR: 0.004000
Training Epoch: 27 [2560/9756]	Loss: 0.1422	LR: 0.004000
Training Epoch: 27 [2816/9756]	Loss: 0.1283	LR: 0.004000
Training Epoch: 27 [3072/9756]	Loss: 0.1447	LR: 0.004000
Training Epoch: 27 [3328/9756]	Loss: 0.1307	LR: 0.004000
Training Epoch: 27 [3584/9756]	Loss: 0.1492	LR: 0.004000
Training Epoch: 27 [3840/9756]	Loss: 0.1539	LR: 0.004000
Training Epoch: 27 [4096/9756]	Loss: 0.1816	LR: 0.004000
Training Epoch: 27 [4352/9756]	Loss: 0.1815	LR: 0.004000
Training Epoch: 27 [4608/9756]	Loss: 0.2178	LR: 0.004000
Training Epoch: 27 [4864/9756]	Loss: 0.1571	LR: 0.004000
Training Epoch: 27 [5120/9756]	Loss: 0.1787	LR: 0.004000
Training Epoch: 27 [5376/9756]	Loss: 0.1472	LR: 0.004000
Training Epoch: 27 [5632/9756]	Loss: 0.1776	LR: 0.004000
Training Epoch: 27 [5888/9756]	Loss: 0.1948	LR: 0.004000
Training Epoch: 27 [6144/9756]	Loss: 0.1840	LR: 0.004000
Training Epoch: 27 [6400/9756]	Loss: 0.1313	LR: 0.004000
Training Epoch: 27 [6656/9756]	Loss: 0.2126	LR: 0.004000
Training Epoch: 27 [6912/9756]	Loss: 0.1716	LR: 0.004000
Training Epoch: 27 [7168/9756]	Loss: 0.1296	LR: 0.004000
Training Epoch: 27 [7424/9756]	Loss: 0.1339	LR: 0.004000
Training Epoch: 27 [7680/9756]	Loss: 0.1853	LR: 0.004000
Training Epoch: 27 [7936/9756]	Loss: 0.1876	LR: 0.004000
Training Epoch: 27 [8192/9756]	Loss: 0.1145	LR: 0.004000
Training Epoch: 27 [8448/9756]	Loss: 0.1263	LR: 0.004000
Training Epoch: 27 [8704/9756]	Loss: 0.1421	LR: 0.004000
Training Epoch: 27 [8960/9756]	Loss: 0.1434	LR: 0.004000
Training Epoch: 27 [9216/9756]	Loss: 0.1905	LR: 0.004000
Training Epoch: 27 [9472/9756]	Loss: 0.1687	LR: 0.004000
Training Epoch: 27 [9728/9756]	Loss: 0.1915	LR: 0.004000
Training Epoch: 27 [9756/9756]	Loss: 0.2313	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1619, Train Accuracy: 0.9337
Epoch 27 training time consumed: 142.39s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0007, Accuracy: 0.9346, Time consumed:7.95s
Training Epoch: 28 [256/9756]	Loss: 0.1560	LR: 0.004000
Training Epoch: 28 [512/9756]	Loss: 0.1649	LR: 0.004000
Training Epoch: 28 [768/9756]	Loss: 0.1203	LR: 0.004000
Training Epoch: 28 [1024/9756]	Loss: 0.1396	LR: 0.004000
Training Epoch: 28 [1280/9756]	Loss: 0.2260	LR: 0.004000
Training Epoch: 28 [1536/9756]	Loss: 0.1300	LR: 0.004000
Training Epoch: 28 [1792/9756]	Loss: 0.1087	LR: 0.004000
Training Epoch: 28 [2048/9756]	Loss: 0.1833	LR: 0.004000
Training Epoch: 28 [2304/9756]	Loss: 0.2106	LR: 0.004000
Training Epoch: 28 [2560/9756]	Loss: 0.1563	LR: 0.004000
Training Epoch: 28 [2816/9756]	Loss: 0.1848	LR: 0.004000
Training Epoch: 28 [3072/9756]	Loss: 0.1438	LR: 0.004000
Training Epoch: 28 [3328/9756]	Loss: 0.1780	LR: 0.004000
Training Epoch: 28 [3584/9756]	Loss: 0.1243	LR: 0.004000
Training Epoch: 28 [3840/9756]	Loss: 0.1784	LR: 0.004000
Training Epoch: 28 [4096/9756]	Loss: 0.1485	LR: 0.004000
Training Epoch: 28 [4352/9756]	Loss: 0.1392	LR: 0.004000
Training Epoch: 28 [4608/9756]	Loss: 0.1696	LR: 0.004000
Training Epoch: 28 [4864/9756]	Loss: 0.1500	LR: 0.004000
Training Epoch: 28 [5120/9756]	Loss: 0.1392	LR: 0.004000
Training Epoch: 28 [5376/9756]	Loss: 0.1242	LR: 0.004000
Training Epoch: 28 [5632/9756]	Loss: 0.1601	LR: 0.004000
Training Epoch: 28 [5888/9756]	Loss: 0.1789	LR: 0.004000
Training Epoch: 28 [6144/9756]	Loss: 0.1415	LR: 0.004000
Training Epoch: 28 [6400/9756]	Loss: 0.1649	LR: 0.004000
Training Epoch: 28 [6656/9756]	Loss: 0.1795	LR: 0.004000
Training Epoch: 28 [6912/9756]	Loss: 0.1701	LR: 0.004000
Training Epoch: 28 [7168/9756]	Loss: 0.1413	LR: 0.004000
Training Epoch: 28 [7424/9756]	Loss: 0.1563	LR: 0.004000
Training Epoch: 28 [7680/9756]	Loss: 0.1559	LR: 0.004000
Training Epoch: 28 [7936/9756]	Loss: 0.1357	LR: 0.004000
Training Epoch: 28 [8192/9756]	Loss: 0.1703	LR: 0.004000
Training Epoch: 28 [8448/9756]	Loss: 0.2022	LR: 0.004000
Training Epoch: 28 [8704/9756]	Loss: 0.1925	LR: 0.004000
Training Epoch: 28 [8960/9756]	Loss: 0.1046	LR: 0.004000
Training Epoch: 28 [9216/9756]	Loss: 0.1631	LR: 0.004000
Training Epoch: 28 [9472/9756]	Loss: 0.1640	LR: 0.004000
Training Epoch: 28 [9728/9756]	Loss: 0.1374	LR: 0.004000
Training Epoch: 28 [9756/9756]	Loss: 0.2525	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1580, Train Accuracy: 0.9331
Epoch 28 training time consumed: 144.37s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0008, Accuracy: 0.9104, Time consumed:8.17s
Training Epoch: 29 [256/9756]	Loss: 0.1764	LR: 0.004000
Training Epoch: 29 [512/9756]	Loss: 0.1208	LR: 0.004000
Training Epoch: 29 [768/9756]	Loss: 0.1476	LR: 0.004000
Training Epoch: 29 [1024/9756]	Loss: 0.1314	LR: 0.004000
Training Epoch: 29 [1280/9756]	Loss: 0.1525	LR: 0.004000
Training Epoch: 29 [1536/9756]	Loss: 0.1514	LR: 0.004000
Training Epoch: 29 [1792/9756]	Loss: 0.1528	LR: 0.004000
Training Epoch: 29 [2048/9756]	Loss: 0.1142	LR: 0.004000
Training Epoch: 29 [2304/9756]	Loss: 0.1538	LR: 0.004000
Training Epoch: 29 [2560/9756]	Loss: 0.1511	LR: 0.004000
Training Epoch: 29 [2816/9756]	Loss: 0.1863	LR: 0.004000
Training Epoch: 29 [3072/9756]	Loss: 0.1126	LR: 0.004000
Training Epoch: 29 [3328/9756]	Loss: 0.1564	LR: 0.004000
Training Epoch: 29 [3584/9756]	Loss: 0.1469	LR: 0.004000
Training Epoch: 29 [3840/9756]	Loss: 0.1409	LR: 0.004000
Training Epoch: 29 [4096/9756]	Loss: 0.1966	LR: 0.004000
Training Epoch: 29 [4352/9756]	Loss: 0.1247	LR: 0.004000
Training Epoch: 29 [4608/9756]	Loss: 0.1857	LR: 0.004000
Training Epoch: 29 [4864/9756]	Loss: 0.2135	LR: 0.004000
Training Epoch: 29 [5120/9756]	Loss: 0.1482	LR: 0.004000
Training Epoch: 29 [5376/9756]	Loss: 0.1055	LR: 0.004000
Training Epoch: 29 [5632/9756]	Loss: 0.1686	LR: 0.004000
Training Epoch: 29 [5888/9756]	Loss: 0.1766	LR: 0.004000
Training Epoch: 29 [6144/9756]	Loss: 0.1513	LR: 0.004000
Training Epoch: 29 [6400/9756]	Loss: 0.1479	LR: 0.004000
Training Epoch: 29 [6656/9756]	Loss: 0.1512	LR: 0.004000
Training Epoch: 29 [6912/9756]	Loss: 0.1514	LR: 0.004000
Training Epoch: 29 [7168/9756]	Loss: 0.1496	LR: 0.004000
Training Epoch: 29 [7424/9756]	Loss: 0.1391	LR: 0.004000
Training Epoch: 29 [7680/9756]	Loss: 0.1678	LR: 0.004000
Training Epoch: 29 [7936/9756]	Loss: 0.2015	LR: 0.004000
Training Epoch: 29 [8192/9756]	Loss: 0.2079	LR: 0.004000
Training Epoch: 29 [8448/9756]	Loss: 0.1643	LR: 0.004000
Training Epoch: 29 [8704/9756]	Loss: 0.1719	LR: 0.004000
Training Epoch: 29 [8960/9756]	Loss: 0.1562	LR: 0.004000
Training Epoch: 29 [9216/9756]	Loss: 0.1897	LR: 0.004000
Training Epoch: 29 [9472/9756]	Loss: 0.1448	LR: 0.004000
Training Epoch: 29 [9728/9756]	Loss: 0.1466	LR: 0.004000
Training Epoch: 29 [9756/9756]	Loss: 0.2114	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1569, Train Accuracy: 0.9339
Epoch 29 training time consumed: 144.02s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0008, Accuracy: 0.9235, Time consumed:8.17s
Training Epoch: 30 [256/9756]	Loss: 0.1284	LR: 0.004000
Training Epoch: 30 [512/9756]	Loss: 0.1402	LR: 0.004000
Training Epoch: 30 [768/9756]	Loss: 0.2481	LR: 0.004000
Training Epoch: 30 [1024/9756]	Loss: 0.1317	LR: 0.004000
Training Epoch: 30 [1280/9756]	Loss: 0.1907	LR: 0.004000
Training Epoch: 30 [1536/9756]	Loss: 0.2276	LR: 0.004000
Training Epoch: 30 [1792/9756]	Loss: 0.2360	LR: 0.004000
Training Epoch: 30 [2048/9756]	Loss: 0.1121	LR: 0.004000
Training Epoch: 30 [2304/9756]	Loss: 0.1623	LR: 0.004000
Training Epoch: 30 [2560/9756]	Loss: 0.1503	LR: 0.004000
Training Epoch: 30 [2816/9756]	Loss: 0.1476	LR: 0.004000
Training Epoch: 30 [3072/9756]	Loss: 0.1161	LR: 0.004000
Training Epoch: 30 [3328/9756]	Loss: 0.1872	LR: 0.004000
Training Epoch: 30 [3584/9756]	Loss: 0.1713	LR: 0.004000
Training Epoch: 30 [3840/9756]	Loss: 0.1408	LR: 0.004000
Training Epoch: 30 [4096/9756]	Loss: 0.1657	LR: 0.004000
Training Epoch: 30 [4352/9756]	Loss: 0.2099	LR: 0.004000
Training Epoch: 30 [4608/9756]	Loss: 0.1775	LR: 0.004000
Training Epoch: 30 [4864/9756]	Loss: 0.1601	LR: 0.004000
Training Epoch: 30 [5120/9756]	Loss: 0.2094	LR: 0.004000
Training Epoch: 30 [5376/9756]	Loss: 0.1585	LR: 0.004000
Training Epoch: 30 [5632/9756]	Loss: 0.1674	LR: 0.004000
Training Epoch: 30 [5888/9756]	Loss: 0.1419	LR: 0.004000
Training Epoch: 30 [6144/9756]	Loss: 0.1302	LR: 0.004000
Training Epoch: 30 [6400/9756]	Loss: 0.1563	LR: 0.004000
Training Epoch: 30 [6656/9756]	Loss: 0.1791	LR: 0.004000
Training Epoch: 30 [6912/9756]	Loss: 0.1258	LR: 0.004000
Training Epoch: 30 [7168/9756]	Loss: 0.1143	LR: 0.004000
Training Epoch: 30 [7424/9756]	Loss: 0.1647	LR: 0.004000
Training Epoch: 30 [7680/9756]	Loss: 0.1106	LR: 0.004000
Training Epoch: 30 [7936/9756]	Loss: 0.1637	LR: 0.004000
Training Epoch: 30 [8192/9756]	Loss: 0.1802	LR: 0.004000
Training Epoch: 30 [8448/9756]	Loss: 0.1735	LR: 0.004000
Training Epoch: 30 [8704/9756]	Loss: 0.1473	LR: 0.004000
Training Epoch: 30 [8960/9756]	Loss: 0.1269	LR: 0.004000
Training Epoch: 30 [9216/9756]	Loss: 0.1711	LR: 0.004000
Training Epoch: 30 [9472/9756]	Loss: 0.1657	LR: 0.004000
Training Epoch: 30 [9728/9756]	Loss: 0.1810	LR: 0.004000
Training Epoch: 30 [9756/9756]	Loss: 0.1882	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1625, Train Accuracy: 0.9332
Epoch 30 training time consumed: 146.07s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0007, Accuracy: 0.9278, Time consumed:7.90s
Training Epoch: 31 [256/9756]	Loss: 0.1723	LR: 0.004000
Training Epoch: 31 [512/9756]	Loss: 0.1223	LR: 0.004000
Training Epoch: 31 [768/9756]	Loss: 0.1444	LR: 0.004000
Training Epoch: 31 [1024/9756]	Loss: 0.1776	LR: 0.004000
Training Epoch: 31 [1280/9756]	Loss: 0.1994	LR: 0.004000
Training Epoch: 31 [1536/9756]	Loss: 0.1776	LR: 0.004000
Training Epoch: 31 [1792/9756]	Loss: 0.1539	LR: 0.004000
Training Epoch: 31 [2048/9756]	Loss: 0.1571	LR: 0.004000
Training Epoch: 31 [2304/9756]	Loss: 0.1323	LR: 0.004000
Training Epoch: 31 [2560/9756]	Loss: 0.1671	LR: 0.004000
Training Epoch: 31 [2816/9756]	Loss: 0.1412	LR: 0.004000
Training Epoch: 31 [3072/9756]	Loss: 0.1422	LR: 0.004000
Training Epoch: 31 [3328/9756]	Loss: 0.1850	LR: 0.004000
Training Epoch: 31 [3584/9756]	Loss: 0.1376	LR: 0.004000
Training Epoch: 31 [3840/9756]	Loss: 0.2085	LR: 0.004000
Training Epoch: 31 [4096/9756]	Loss: 0.1306	LR: 0.004000
Training Epoch: 31 [4352/9756]	Loss: 0.1486	LR: 0.004000
Training Epoch: 31 [4608/9756]	Loss: 0.1749	LR: 0.004000
Training Epoch: 31 [4864/9756]	Loss: 0.1408	LR: 0.004000
Training Epoch: 31 [5120/9756]	Loss: 0.1572	LR: 0.004000
Training Epoch: 31 [5376/9756]	Loss: 0.1742	LR: 0.004000
Training Epoch: 31 [5632/9756]	Loss: 0.1478	LR: 0.004000
Training Epoch: 31 [5888/9756]	Loss: 0.1023	LR: 0.004000
Training Epoch: 31 [6144/9756]	Loss: 0.1337	LR: 0.004000
Training Epoch: 31 [6400/9756]	Loss: 0.1702	LR: 0.004000
Training Epoch: 31 [6656/9756]	Loss: 0.1447	LR: 0.004000
Training Epoch: 31 [6912/9756]	Loss: 0.1788	LR: 0.004000
Training Epoch: 31 [7168/9756]	Loss: 0.1387	LR: 0.004000
Training Epoch: 31 [7424/9756]	Loss: 0.1526	LR: 0.004000
Training Epoch: 31 [7680/9756]	Loss: 0.1652	LR: 0.004000
Training Epoch: 31 [7936/9756]	Loss: 0.1272	LR: 0.004000
Training Epoch: 31 [8192/9756]	Loss: 0.1476	LR: 0.004000
Training Epoch: 31 [8448/9756]	Loss: 0.1444	LR: 0.004000
Training Epoch: 31 [8704/9756]	Loss: 0.2150	LR: 0.004000
Training Epoch: 31 [8960/9756]	Loss: 0.1388	LR: 0.004000
Training Epoch: 31 [9216/9756]	Loss: 0.2049	LR: 0.004000
Training Epoch: 31 [9472/9756]	Loss: 0.0873	LR: 0.004000
Training Epoch: 31 [9728/9756]	Loss: 0.1732	LR: 0.004000
Training Epoch: 31 [9756/9756]	Loss: 0.0656	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1555, Train Accuracy: 0.9375
Epoch 31 training time consumed: 142.34s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9433, Time consumed:8.09s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_11h_37m_58s/ResNet18-MUCAC-seed10-ret25-31-best.pth
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  9756
Forget Train Dl:  792
Retain Valid Dl:  9756
Forget Valid Dl:  792
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 792 samples
Set1 Distribution: 792 samples
Set2 Distribution: 792 samples
Set1 Distribution: 792 samples
Set2 Distribution: 792 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 94.31168365478516
Retain Accuracy: 94.13919830322266
Zero-Retain Forget (ZRF): 0.7894049882888794
Membership Inference Attack (MIA): 0.3409090909090909
Forget vs Retain Membership Inference Attack (MIA): 0.45110410094637227
Forget vs Test Membership Inference Attack (MIA): 0.5772870662460567
Test vs Retain Membership Inference Attack (MIA): 0.5290556900726392
Train vs Test Membership Inference Attack (MIA): 0.5230024213075061
Forget Set Accuracy (Df): 94.46614074707031
Method Execution Time: 5805.92 seconds
