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2020-01-31 19:45:32 Epoch 59, Val iteration 0, acc 92.000 (92.000) |
2020-01-31 19:45:35 Epoch 59, Val iteration 19, acc 92.800 (91.330) |
* Prec: 91.33000221252442 |
-------- |
ResNet50 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:45:37, Epoch 0, Iteration 7, loss 0.129 (0.717), acc 96.154 (88.000) |
2020-01-31 19:45:37, Epoch 30, Iteration 7, loss 0.000 (0.018), acc 100.000 (99.400) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-17.37535, -37.61862, -7.694463, -9.739318, -40.56836, -41.71021, 24.96041, -11.37548, 21.795544, 0.3740155], Poisons' Predictions:[8, 8, 8, 6, 8] |
2020-01-31 19:45:39 Epoch 59, Val iteration 0, acc 93.000 (93.000) |
2020-01-31 19:45:43 Epoch 59, Val iteration 19, acc 92.400 (92.370) |
* Prec: 92.37000122070313 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:45:45, Epoch 0, Iteration 7, loss 0.272 (1.933), acc 96.154 (77.200) |
2020-01-31 19:45:45, Epoch 30, Iteration 7, loss 0.015 (0.035), acc 98.077 (98.200) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-28.736992, 7.584054, -8.99926, 14.567998, -89.159, -27.129454, 32.10237, -31.01875, 25.40679, -28.777256], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:45:47 Epoch 59, Val iteration 0, acc 93.400 (93.400) |
2020-01-31 19:45:51 Epoch 59, Val iteration 19, acc 92.400 (92.780) |
* Prec: 92.78000144958496 |
-------- |
GoogLeNet |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:45:53, Epoch 0, Iteration 7, loss 0.471 (0.469), acc 88.462 (88.600) |
2020-01-31 19:45:54, Epoch 30, Iteration 7, loss 0.061 (0.078), acc 98.077 (97.600) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-15.733282, -4.5869627, -10.271608, -1.3060622, -12.750443, -4.586568, 9.945782, -5.010804, 9.007038, -21.047483], Poisons' Predictions:[8, 6, 6, 6, 6] |
2020-01-31 19:45:56 Epoch 59, Val iteration 0, acc 91.800 (91.800) |
2020-01-31 19:46:01 Epoch 59, Val iteration 19, acc 91.400 (91.950) |
* Prec: 91.9500015258789 |
-------- |
MobileNetV2 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:46:03, Epoch 0, Iteration 7, loss 1.629 (3.358), acc 80.769 (59.200) |
2020-01-31 19:46:03, Epoch 30, Iteration 7, loss 0.894 (0.377), acc 86.538 (92.600) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-3.2102032, -1.4409312, -21.185898, 2.4879436, -37.84942, -10.145981, 19.239002, -29.545057, 16.984531, -27.608585], Poisons' Predictions:[8, 8, 8, 6, 8] |
2020-01-31 19:46:04 Epoch 59, Val iteration 0, acc 88.200 (88.200) |
2020-01-31 19:46:06 Epoch 59, Val iteration 19, acc 87.600 (86.750) |
* Prec: 86.75000114440918 |
-------- |
ResNet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:46:08, Epoch 0, Iteration 7, loss 0.393 (0.561), acc 92.308 (87.800) |
2020-01-31 19:46:08, Epoch 30, Iteration 7, loss 0.037 (0.100), acc 98.077 (98.800) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-32.196095, -19.086508, -6.4604354, 6.838498, -33.486885, -1.3919034, 14.97593, -32.099743, 12.337316, -35.437595], Poisons' Predictions:[8, 8, 6, 6, 6] |
2020-01-31 19:46:09 Epoch 59, Val iteration 0, acc 92.200 (92.200) |
2020-01-31 19:46:11 Epoch 59, Val iteration 19, acc 93.800 (92.260) |
* Prec: 92.26000175476074 |
-------- |
DenseNet121 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:46:14, Epoch 0, Iteration 7, loss 0.185 (0.382), acc 90.385 (92.800) |
2020-01-31 19:46:14, Epoch 30, Iteration 7, loss 0.002 (0.009), acc 100.000 (99.800) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-2.9794848, -14.266707, -7.582068, -3.8935258, -8.364236, -6.1151605, 8.148629, -29.393742, 5.157317, -13.726772], Poisons' Predictions:[8, 8, 8, 6, 8] |
2020-01-31 19:46:16 Epoch 59, Val iteration 0, acc 93.800 (93.800) |
2020-01-31 19:46:20 Epoch 59, Val iteration 19, acc 92.400 (93.020) |
* Prec: 93.02000198364257 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 28 |
TARGET INDEX: 16 |
DPN92 1 |
SENet18 0 |
ResNet50 0 |
ResNeXt29_2x64d 0 |
GoogLeNet 0 |
MobileNetV2 0 |
ResNet18 0 |
DenseNet121 0 |
Namespace(chk_path='chk-black-ourmean/', chk_subdir='poisons', device='cuda', dset_path='datasets', end2end=False, eval_poison_path='', gpu='1', 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=17, 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') |
Path: chk-black-ourmean/mean/4000/17 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-01-31 19:12:39 Iteration 0 Training Loss: 1.102e+00 Loss in Target Net: 3.771e-01 |
2020-01-31 19:13:00 Iteration 50 Training Loss: 8.558e-02 Loss in Target Net: 7.979e-03 |
2020-01-31 19:13:22 Iteration 100 Training Loss: 7.459e-02 Loss in Target Net: 1.016e-02 |
2020-01-31 19:13:43 Iteration 150 Training Loss: 6.647e-02 Loss in Target Net: 6.975e-03 |
2020-01-31 19:14:05 Iteration 200 Training Loss: 6.971e-02 Loss in Target Net: 6.963e-03 |
2020-01-31 19:14:28 Iteration 250 Training Loss: 7.468e-02 Loss in Target Net: 5.764e-03 |
2020-01-31 19:14:49 Iteration 300 Training Loss: 7.446e-02 Loss in Target Net: 3.534e-03 |
2020-01-31 19:15:12 Iteration 350 Training Loss: 7.643e-02 Loss in Target Net: 4.883e-03 |
2020-01-31 19:15:33 Iteration 400 Training Loss: 7.188e-02 Loss in Target Net: 3.013e-03 |
2020-01-31 19:15:55 Iteration 450 Training Loss: 6.708e-02 Loss in Target Net: 3.350e-03 |
2020-01-31 19:16:17 Iteration 500 Training Loss: 7.017e-02 Loss in Target Net: 1.351e-03 |
2020-01-31 19:16:39 Iteration 550 Training Loss: 6.652e-02 Loss in Target Net: 2.473e-03 |
2020-01-31 19:17:00 Iteration 600 Training Loss: 6.446e-02 Loss in Target Net: 3.024e-03 |
2020-01-31 19:17:21 Iteration 650 Training Loss: 6.781e-02 Loss in Target Net: 2.458e-03 |
2020-01-31 19:17:43 Iteration 700 Training Loss: 7.136e-02 Loss in Target Net: 1.955e-03 |
2020-01-31 19:18:04 Iteration 750 Training Loss: 6.672e-02 Loss in Target Net: 1.315e-03 |
2020-01-31 19:18:25 Iteration 800 Training Loss: 7.293e-02 Loss in Target Net: 2.014e-03 |
2020-01-31 19:18:47 Iteration 850 Training Loss: 7.097e-02 Loss in Target Net: 1.752e-03 |
2020-01-31 19:19:08 Iteration 900 Training Loss: 7.227e-02 Loss in Target Net: 3.029e-03 |
2020-01-31 19:19:30 Iteration 950 Training Loss: 7.482e-02 Loss in Target Net: 1.865e-03 |
2020-01-31 19:19:51 Iteration 1000 Training Loss: 7.211e-02 Loss in Target Net: 1.582e-03 |
2020-01-31 19:20:13 Iteration 1050 Training Loss: 6.322e-02 Loss in Target Net: 1.808e-03 |
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