text stringlengths 5 1.13k |
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2020-01-31 22:12:32 Epoch 59, Val iteration 0, acc 91.800 (91.800) |
2020-01-31 22:12:34 Epoch 59, Val iteration 19, acc 93.600 (91.510) |
* Prec: 91.51000099182129 |
-------- |
ResNet50 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 22:12:36, Epoch 0, Iteration 7, loss 0.000 (1.457), acc 100.000 (84.800) |
2020-01-31 22:12:37, Epoch 30, Iteration 7, loss 0.015 (0.002), acc 98.077 (99.800) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-54.60889, -37.799694, -26.760748, -34.466957, -46.479855, -24.209864, 16.234798, -23.071972, 4.358105, -38.84009], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 22:12:38 Epoch 59, Val iteration 0, acc 92.800 (92.800) |
2020-01-31 22:12:42 Epoch 59, Val iteration 19, acc 91.400 (92.100) |
* Prec: 92.10000228881836 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 22:12:44, Epoch 0, Iteration 7, loss 0.778 (2.213), acc 90.385 (71.400) |
2020-01-31 22:12:45, Epoch 30, Iteration 7, loss 0.341 (0.139), acc 96.154 (97.000) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-30.341324, -10.685913, -2.756036, 5.4683094, -54.154804, -13.362816, 17.860245, -13.149808, 17.76248, -19.81953], Poisons' Predictions:[8, 8, 8, 6, 8] |
2020-01-31 22:12:46 Epoch 59, Val iteration 0, acc 93.400 (93.400) |
2020-01-31 22:12:50 Epoch 59, Val iteration 19, acc 93.600 (92.720) |
* Prec: 92.72000122070312 |
-------- |
GoogLeNet |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 22:12:53, Epoch 0, Iteration 7, loss 0.225 (0.514), acc 98.077 (90.200) |
2020-01-31 22:12:53, Epoch 30, Iteration 7, loss 0.025 (0.076), acc 98.077 (97.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-26.784641, -8.457287, -5.2973, -0.048594356, -9.733205, -2.4226418, 6.3765073, -6.1083055, 8.071297, -17.992455], Poisons' Predictions:[6, 8, 6, 8, 8] |
2020-01-31 22:12:55 Epoch 59, Val iteration 0, acc 91.200 (91.200) |
2020-01-31 22:13:00 Epoch 59, Val iteration 19, acc 92.200 (91.650) |
* Prec: 91.65000228881836 |
-------- |
MobileNetV2 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 22:13:02, Epoch 0, Iteration 7, loss 0.554 (3.387), acc 88.462 (65.600) |
2020-01-31 22:13:03, Epoch 30, Iteration 7, loss 0.150 (0.189), acc 96.154 (94.200) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-10.430578, -12.501375, 7.389228, 14.570826, -10.466303, -1.5762236, 16.166218, -23.054264, 16.621126, -16.565613], Poisons' Predictions:[8, 8, 8, 8, 6] |
2020-01-31 22:13:03 Epoch 59, Val iteration 0, acc 88.000 (88.000) |
2020-01-31 22:13:05 Epoch 59, Val iteration 19, acc 89.400 (86.920) |
* Prec: 86.92000122070313 |
-------- |
ResNet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 22:13:08, Epoch 0, Iteration 7, loss 0.255 (0.756), acc 98.077 (86.000) |
2020-01-31 22:13:08, Epoch 30, Iteration 7, loss 0.003 (0.034), acc 100.000 (98.600) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-40.00686, -14.216795, -9.246256, 6.6728115, -44.791134, -3.3022075, 6.1344476, -34.82101, 7.6727448, -51.53291], Poisons' Predictions:[6, 8, 8, 6, 8] |
2020-01-31 22:13:08 Epoch 59, Val iteration 0, acc 92.600 (92.600) |
2020-01-31 22:13:11 Epoch 59, Val iteration 19, acc 93.600 (92.280) |
* Prec: 92.28000183105469 |
-------- |
DenseNet121 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 22:13:13, Epoch 0, Iteration 7, loss 0.702 (0.463), acc 86.538 (91.200) |
2020-01-31 22:13:14, Epoch 30, Iteration 7, loss 0.005 (0.005), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-9.780513, -20.970549, -11.91721, -2.2054114, -11.267849, -5.267479, 4.500871, -32.09175, 5.78165, -18.036716], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 22:13:16 Epoch 59, Val iteration 0, acc 93.800 (93.800) |
2020-01-31 22:13:20 Epoch 59, Val iteration 19, acc 92.800 (92.850) |
* Prec: 92.85000190734863 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 29 |
TARGET INDEX: 39 |
DPN92 1 |
SENet18 0 |
ResNet50 0 |
ResNeXt29_2x64d 0 |
GoogLeNet 1 |
MobileNetV2 1 |
ResNet18 1 |
DenseNet121 1 |
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=4, 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/4000/4 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-01-31 17:43:49 Iteration 0 Training Loss: 1.063e+00 Loss in Target Net: 4.045e-01 |
2020-01-31 17:44:11 Iteration 50 Training Loss: 8.453e-02 Loss in Target Net: 1.391e-02 |
2020-01-31 17:44:34 Iteration 100 Training Loss: 7.216e-02 Loss in Target Net: 1.156e-02 |
2020-01-31 17:44:54 Iteration 150 Training Loss: 7.757e-02 Loss in Target Net: 1.166e-02 |
2020-01-31 17:45:16 Iteration 200 Training Loss: 7.181e-02 Loss in Target Net: 1.207e-02 |
2020-01-31 17:45:38 Iteration 250 Training Loss: 7.113e-02 Loss in Target Net: 1.207e-02 |
2020-01-31 17:46:01 Iteration 300 Training Loss: 6.580e-02 Loss in Target Net: 1.379e-02 |
2020-01-31 17:46:23 Iteration 350 Training Loss: 6.629e-02 Loss in Target Net: 1.483e-02 |
2020-01-31 17:46:46 Iteration 400 Training Loss: 6.858e-02 Loss in Target Net: 1.246e-02 |
2020-01-31 17:47:08 Iteration 450 Training Loss: 6.558e-02 Loss in Target Net: 1.293e-02 |
2020-01-31 17:47:31 Iteration 500 Training Loss: 6.717e-02 Loss in Target Net: 1.377e-02 |
2020-01-31 17:47:53 Iteration 550 Training Loss: 6.759e-02 Loss in Target Net: 1.721e-02 |
2020-01-31 17:48:17 Iteration 600 Training Loss: 6.892e-02 Loss in Target Net: 1.340e-02 |
2020-01-31 17:48:39 Iteration 650 Training Loss: 6.461e-02 Loss in Target Net: 9.668e-03 |
2020-01-31 17:49:01 Iteration 700 Training Loss: 6.715e-02 Loss in Target Net: 1.386e-02 |
2020-01-31 17:49:25 Iteration 750 Training Loss: 6.749e-02 Loss in Target Net: 1.272e-02 |
2020-01-31 17:49:47 Iteration 800 Training Loss: 6.551e-02 Loss in Target Net: 1.071e-02 |
2020-01-31 17:50:09 Iteration 850 Training Loss: 6.457e-02 Loss in Target Net: 1.546e-02 |
2020-01-31 17:50:33 Iteration 900 Training Loss: 6.402e-02 Loss in Target Net: 1.114e-02 |
2020-01-31 17:50:54 Iteration 950 Training Loss: 7.298e-02 Loss in Target Net: 9.885e-03 |
2020-01-31 17:51:16 Iteration 1000 Training Loss: 6.891e-02 Loss in Target Net: 1.214e-02 |
2020-01-31 17:51:38 Iteration 1050 Training Loss: 7.452e-02 Loss in Target Net: 1.106e-02 |
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