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2020-01-31 19:08:06 Iteration 3700 Training Loss: 8.454e-02 Loss in Target Net: 2.339e-02 |
2020-01-31 19:08:28 Iteration 3750 Training Loss: 8.662e-02 Loss in Target Net: 2.325e-02 |
2020-01-31 19:08:50 Iteration 3800 Training Loss: 8.569e-02 Loss in Target Net: 1.932e-02 |
2020-01-31 19:09:11 Iteration 3850 Training Loss: 8.676e-02 Loss in Target Net: 2.092e-02 |
2020-01-31 19:09:34 Iteration 3900 Training Loss: 9.160e-02 Loss in Target Net: 3.093e-02 |
2020-01-31 19:09:55 Iteration 3950 Training Loss: 8.538e-02 Loss in Target Net: 2.148e-02 |
2020-01-31 19:10:16 Iteration 3999 Training Loss: 7.972e-02 Loss in Target Net: 2.415e-02 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:10:20, Epoch 0, Iteration 7, loss 1.169 (3.119), acc 90.385 (72.600) |
2020-01-31 19:10:20, Epoch 30, Iteration 7, loss 0.110 (0.120), acc 94.231 (98.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[8.034739, -13.285031, -32.13242, 4.1977997, -29.40093, -7.9846115, 8.275462, -40.567703, 24.164865, -68.098175], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:10:24 Epoch 59, Val iteration 0, acc 91.200 (91.200) |
2020-01-31 19:10:31 Epoch 59, Val iteration 19, acc 92.600 (92.020) |
* Prec: 92.02000122070312 |
-------- |
SENet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:10:34, Epoch 0, Iteration 7, loss 0.499 (1.015), acc 88.462 (84.000) |
2020-01-31 19:10:34, Epoch 30, Iteration 7, loss 0.069 (0.135), acc 98.077 (96.600) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-7.5098658, 3.3544016, -11.467077, -3.9649744, 2.2093546, -6.598544, 15.293654, -2.3511388, 15.734785, -19.15101], Poisons' Predictions:[6, 8, 6, 8, 6] |
2020-01-31 19:10:35 Epoch 59, Val iteration 0, acc 91.600 (91.600) |
2020-01-31 19:10:37 Epoch 59, Val iteration 19, acc 92.200 (91.270) |
* Prec: 91.27000122070312 |
-------- |
ResNet50 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:10:39, Epoch 0, Iteration 7, loss 0.000 (1.459), acc 100.000 (85.800) |
2020-01-31 19:10:39, Epoch 30, Iteration 7, loss 0.000 (0.002), acc 100.000 (99.800) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-48.495724, -45.291313, -57.604336, -21.810987, -22.671831, -61.684917, -1.6084318, -16.658573, 10.463716, -61.229008], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:10:40 Epoch 59, Val iteration 0, acc 91.600 (91.600) |
2020-01-31 19:10:44 Epoch 59, Val iteration 19, acc 91.800 (92.260) |
* Prec: 92.26000099182129 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:10:47, Epoch 0, Iteration 7, loss 1.349 (2.237), acc 86.538 (72.600) |
2020-01-31 19:10:47, Epoch 30, Iteration 7, loss 0.160 (0.171), acc 98.077 (96.200) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-37.030502, -5.7114353, -12.339488, -10.653952, -87.06889, -39.446995, 12.932351, -22.03096, 18.419493, -17.731228], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:10:48 Epoch 59, Val iteration 0, acc 92.400 (92.400) |
2020-01-31 19:10:52 Epoch 59, Val iteration 19, acc 93.000 (93.200) |
* Prec: 93.20000190734864 |
-------- |
GoogLeNet |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:10:55, Epoch 0, Iteration 7, loss 0.580 (0.477), acc 90.385 (89.600) |
2020-01-31 19:10:55, Epoch 30, Iteration 7, loss 0.061 (0.070), acc 94.231 (97.400) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-30.457163, -9.443321, -24.63806, -3.7229795, -12.193459, -9.000307, 12.365289, -13.119127, 11.887924, -20.96149], Poisons' Predictions:[8, 8, 6, 8, 8] |
2020-01-31 19:10:58 Epoch 59, Val iteration 0, acc 90.800 (90.800) |
2020-01-31 19:11:03 Epoch 59, Val iteration 19, acc 89.800 (91.610) |
* Prec: 91.61000175476075 |
-------- |
MobileNetV2 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:11:05, Epoch 0, Iteration 7, loss 1.646 (3.189), acc 76.923 (62.800) |
2020-01-31 19:11:05, Epoch 30, Iteration 7, loss 0.097 (0.155), acc 94.231 (95.400) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-4.748723, -7.209488, -14.269563, 3.8927665, -54.82984, -13.76715, 7.56238, -49.226, 9.092798, 2.3067503], Poisons' Predictions:[6, 8, 8, 8, 8] |
2020-01-31 19:11:06 Epoch 59, Val iteration 0, acc 88.200 (88.200) |
2020-01-31 19:11:08 Epoch 59, Val iteration 19, acc 88.400 (86.940) |
* Prec: 86.94000129699707 |
-------- |
ResNet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:11:10, Epoch 0, Iteration 7, loss 0.685 (0.953), acc 92.308 (84.400) |
2020-01-31 19:11:10, Epoch 30, Iteration 7, loss 0.020 (0.042), acc 98.077 (98.200) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-34.963276, -14.264009, -40.796482, -1.1590352, -32.31042, -7.8571954, 4.973434, -15.101957, 13.121766, -30.690508], Poisons' Predictions:[6, 8, 8, 8, 8] |
2020-01-31 19:11:11 Epoch 59, Val iteration 0, acc 93.200 (93.200) |
2020-01-31 19:11:12 Epoch 59, Val iteration 19, acc 93.200 (92.420) |
* Prec: 92.42000236511231 |
-------- |
DenseNet121 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:11:15, Epoch 0, Iteration 7, loss 0.251 (0.373), acc 96.154 (92.000) |
2020-01-31 19:11:16, Epoch 30, Iteration 7, loss 0.003 (0.004), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-10.787153, -17.535675, -11.012052, -3.6390555, -11.817119, -15.711652, 3.6043217, -39.939518, 2.2847245, -14.521113], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:11:17 Epoch 59, Val iteration 0, acc 94.000 (94.000) |
2020-01-31 19:11:22 Epoch 59, Val iteration 19, acc 93.400 (92.880) |
* Prec: 92.88000144958497 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 28 |
TARGET INDEX: 15 |
DPN92 1 |
SENet18 1 |
ResNet50 1 |
ResNeXt29_2x64d 1 |
GoogLeNet 0 |
MobileNetV2 1 |
ResNet18 1 |
DenseNet121 0 |
Namespace(chk_path='chk-black-ourmean/', chk_subdir='poisons', device='cuda', dset_path='datasets', end2end=False, eval_poison_path='', gpu='0', lr_decay_epoch=[30, 45], mode='mean', model_resume_path='model-chks', nearest=False, net_repeat=1, num_per_class=50, original_grad=True, poison_decay_ites=[], poison_decay_ratio=0.1, poison_epsilon=0.1, poison_ites=4000, poison_label=8, poison_lr=0.04, poison_momentum=0.9, poison_num=5, poison_opt='adam', resume_poison_ite=0, retrain_bsize=64, retrain_epochs=60, retrain_lr=0.1, retrain_momentum=0.9, retrain_opt='adam', retrain_wd=0, subs_chk_name=['ckpt-%s-4800-dp0.200-droplayer0.000-seed1226.t7', 'ckpt-%s-4800-dp0.250-droplayer0.000-seed1226.t7', 'ckpt-%s-4800-dp0.300-droplayer0.000.t7'], subs_dp=[0.2, 0.25, 0.3], subset_group=0, substitute_nets=['DPN92', 'SENet18', 'ResNet50', 'ResNeXt29_2x64d', 'GoogLeNet', 'MobileNetV2'], target_index=16, target_label=6, target_net=['DPN92', 'SENet18', 'ResNet50', 'ResNeXt29_2x64d', 'GoogLeNet', 'MobileNetV2', 'ResNet18', 'DenseNet121'], test_chk_name='ckpt-%s-4800.t7', tol=1e-06, train_data_path='datasets/CIFAR10_TRAIN_Split.pth') |
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