text stringlengths 5 1.13k |
|---|
* Prec: 93.02000160217285 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:11:37, Epoch 0, Iteration 7, loss 0.596 (2.653), acc 88.462 (69.600) |
2020-01-31 18:11:37, Epoch 30, Iteration 7, loss 0.122 (0.050), acc 98.077 (98.800) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-21.267967, 9.662866, -18.613674, 6.3411317, -62.339256, -32.43233, 21.279114, -39.94048, 22.87748, -14.621545], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 18:11:38 Epoch 59, Val iteration 0, acc 93.600 (93.600) |
2020-01-31 18:11:42 Epoch 59, Val iteration 19, acc 93.000 (92.810) |
* Prec: 92.81000213623047 |
-------- |
GoogLeNet |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:11:45, Epoch 0, Iteration 7, loss 0.090 (0.398), acc 100.000 (91.600) |
2020-01-31 18:11:45, Epoch 30, Iteration 7, loss 0.048 (0.037), acc 96.154 (97.800) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-26.373363, -13.210057, -8.297762, -1.7892953, -10.764399, -6.9790716, 6.246864, -11.568774, 8.021535, -25.303629], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 18:11:48 Epoch 59, Val iteration 0, acc 90.200 (90.200) |
2020-01-31 18:11:52 Epoch 59, Val iteration 19, acc 90.200 (91.490) |
* Prec: 91.49000205993653 |
-------- |
MobileNetV2 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:11:55, Epoch 0, Iteration 7, loss 0.975 (2.864), acc 84.615 (66.200) |
2020-01-31 18:11:55, Epoch 30, Iteration 7, loss 0.477 (0.393), acc 88.462 (92.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[4.559383, 3.4167259, -2.5239103, 18.883118, -15.076527, -0.23645854, 31.688477, -30.792301, 33.6868, -32.564358], Poisons' Predictions:[8, 8, 6, 8, 6] |
2020-01-31 18:11:56 Epoch 59, Val iteration 0, acc 88.800 (88.800) |
2020-01-31 18:11:58 Epoch 59, Val iteration 19, acc 88.200 (87.140) |
* Prec: 87.14000129699707 |
-------- |
ResNet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:12:00, Epoch 0, Iteration 7, loss 0.626 (0.719), acc 92.308 (85.800) |
2020-01-31 18:12:00, Epoch 30, Iteration 7, loss 0.157 (0.045), acc 92.308 (98.400) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-28.112144, -5.950345, -11.837439, 1.8840563, -43.824753, -10.865148, 1.5741833, -30.335321, 7.2977514, -31.469028], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 18:12:00 Epoch 59, Val iteration 0, acc 93.200 (93.200) |
2020-01-31 18:12:02 Epoch 59, Val iteration 19, acc 94.000 (92.630) |
* Prec: 92.63000183105468 |
-------- |
DenseNet121 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:12:05, Epoch 0, Iteration 7, loss 0.255 (0.445), acc 92.308 (92.000) |
2020-01-31 18:12:05, Epoch 30, Iteration 7, loss 0.007 (0.004), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-11.108739, -19.3294, -11.542237, -4.214205, -10.953102, -5.507483, 7.2528396, -31.704403, 6.1440387, -13.695089], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 18:12:07 Epoch 59, Val iteration 0, acc 94.200 (94.200) |
2020-01-31 18:12:11 Epoch 59, Val iteration 19, acc 92.400 (93.000) |
* Prec: 93.0000015258789 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 28 |
TARGET INDEX: 6 |
DPN92 1 |
SENet18 1 |
ResNet50 1 |
ResNeXt29_2x64d 1 |
GoogLeNet 1 |
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='3', 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=7, 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/4000/7 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-01-31 17:40:16 Iteration 0 Training Loss: 1.190e+00 Loss in Target Net: 4.775e-01 |
2020-01-31 17:40:37 Iteration 50 Training Loss: 1.364e-01 Loss in Target Net: 2.150e-02 |
2020-01-31 17:40:57 Iteration 100 Training Loss: 1.124e-01 Loss in Target Net: 1.532e-02 |
2020-01-31 17:41:17 Iteration 150 Training Loss: 1.147e-01 Loss in Target Net: 1.616e-02 |
2020-01-31 17:41:40 Iteration 200 Training Loss: 9.708e-02 Loss in Target Net: 1.213e-02 |
2020-01-31 17:42:03 Iteration 250 Training Loss: 1.104e-01 Loss in Target Net: 1.875e-02 |
2020-01-31 17:42:26 Iteration 300 Training Loss: 9.615e-02 Loss in Target Net: 1.837e-02 |
2020-01-31 17:42:48 Iteration 350 Training Loss: 1.092e-01 Loss in Target Net: 1.637e-02 |
2020-01-31 17:43:09 Iteration 400 Training Loss: 9.614e-02 Loss in Target Net: 2.151e-02 |
2020-01-31 17:43:30 Iteration 450 Training Loss: 1.041e-01 Loss in Target Net: 1.947e-02 |
2020-01-31 17:43:50 Iteration 500 Training Loss: 1.008e-01 Loss in Target Net: 1.745e-02 |
2020-01-31 17:44:12 Iteration 550 Training Loss: 1.087e-01 Loss in Target Net: 3.396e-02 |
2020-01-31 17:44:32 Iteration 600 Training Loss: 9.554e-02 Loss in Target Net: 2.086e-02 |
2020-01-31 17:44:54 Iteration 650 Training Loss: 1.029e-01 Loss in Target Net: 2.701e-02 |
2020-01-31 17:45:16 Iteration 700 Training Loss: 1.061e-01 Loss in Target Net: 2.655e-02 |
2020-01-31 17:45:37 Iteration 750 Training Loss: 1.020e-01 Loss in Target Net: 3.415e-02 |
2020-01-31 17:45:58 Iteration 800 Training Loss: 9.102e-02 Loss in Target Net: 3.042e-02 |
2020-01-31 17:46:20 Iteration 850 Training Loss: 9.148e-02 Loss in Target Net: 1.989e-02 |
2020-01-31 17:46:41 Iteration 900 Training Loss: 1.001e-01 Loss in Target Net: 2.309e-02 |
2020-01-31 17:47:04 Iteration 950 Training Loss: 9.348e-02 Loss in Target Net: 1.770e-02 |
2020-01-31 17:47:27 Iteration 1000 Training Loss: 1.007e-01 Loss in Target Net: 1.753e-02 |
2020-01-31 17:47:49 Iteration 1050 Training Loss: 1.020e-01 Loss in Target Net: 1.975e-02 |
2020-01-31 17:48:10 Iteration 1100 Training Loss: 9.154e-02 Loss in Target Net: 2.703e-02 |
2020-01-31 17:48:32 Iteration 1150 Training Loss: 9.103e-02 Loss in Target Net: 1.858e-02 |
2020-01-31 17:48:54 Iteration 1200 Training Loss: 9.563e-02 Loss in Target Net: 3.056e-02 |
2020-01-31 17:49:16 Iteration 1250 Training Loss: 9.708e-02 Loss in Target Net: 1.770e-02 |
2020-01-31 17:49:39 Iteration 1300 Training Loss: 9.095e-02 Loss in Target Net: 2.948e-02 |
2020-01-31 17:50:02 Iteration 1350 Training Loss: 9.202e-02 Loss in Target Net: 2.490e-02 |
2020-01-31 17:50:23 Iteration 1400 Training Loss: 9.621e-02 Loss in Target Net: 2.006e-02 |
2020-01-31 17:50:46 Iteration 1450 Training Loss: 8.776e-02 Loss in Target Net: 1.842e-02 |
2020-01-31 17:51:11 Iteration 1500 Training Loss: 9.495e-02 Loss in Target Net: 1.032e-02 |
2020-01-31 17:51:35 Iteration 1550 Training Loss: 9.603e-02 Loss in Target Net: 8.567e-03 |
2020-01-31 17:51:56 Iteration 1600 Training Loss: 8.960e-02 Loss in Target Net: 2.141e-02 |
2020-01-31 17:52:18 Iteration 1650 Training Loss: 8.762e-02 Loss in Target Net: 1.056e-02 |
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