text stringlengths 5 1.13k |
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* Prec: 92.62000122070313 |
-------- |
DenseNet121 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 22:17:28, Epoch 0, Iteration 7, loss 0.310 (0.367), acc 92.308 (93.800) |
2020-01-31 22:17:28, Epoch 30, Iteration 7, loss 0.002 (0.005), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-9.583206, -11.067221, -17.171532, -7.469681, -10.464496, -9.003317, 9.333676, -40.625313, 6.6336813, -8.8538685], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 22:17:30 Epoch 59, Val iteration 0, acc 94.000 (94.000) |
2020-01-31 22:17:34 Epoch 59, Val iteration 19, acc 92.800 (93.040) |
* Prec: 93.04000129699708 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 30 |
TARGET INDEX: 37 |
DPN92 1 |
SENet18 0 |
ResNet50 1 |
ResNeXt29_2x64d 1 |
GoogLeNet 0 |
MobileNetV2 0 |
ResNet18 1 |
DenseNet121 0 |
Namespace(chk_path='chk-black-ourmean/', chk_subdir='poisons', device='cuda', dset_path='datasets', end2end=False, eval_poison_path='', gpu='2', 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=38, 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/4000/38 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-01-31 21:46:45 Iteration 0 Training Loss: 1.057e+00 Loss in Target Net: 4.106e-01 |
2020-01-31 21:47:06 Iteration 50 Training Loss: 9.563e-02 Loss in Target Net: 1.084e-02 |
2020-01-31 21:47:29 Iteration 100 Training Loss: 9.168e-02 Loss in Target Net: 1.935e-02 |
2020-01-31 21:47:53 Iteration 150 Training Loss: 9.165e-02 Loss in Target Net: 1.696e-02 |
2020-01-31 21:48:16 Iteration 200 Training Loss: 8.588e-02 Loss in Target Net: 1.579e-02 |
2020-01-31 21:48:37 Iteration 250 Training Loss: 8.538e-02 Loss in Target Net: 1.229e-02 |
2020-01-31 21:48:59 Iteration 300 Training Loss: 8.348e-02 Loss in Target Net: 1.282e-02 |
2020-01-31 21:49:21 Iteration 350 Training Loss: 8.701e-02 Loss in Target Net: 1.278e-02 |
2020-01-31 21:49:43 Iteration 400 Training Loss: 8.070e-02 Loss in Target Net: 1.315e-02 |
2020-01-31 21:50:04 Iteration 450 Training Loss: 8.157e-02 Loss in Target Net: 1.170e-02 |
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2020-01-31 21:50:46 Iteration 550 Training Loss: 7.625e-02 Loss in Target Net: 1.052e-02 |
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2020-01-31 22:04:30 Iteration 2450 Training Loss: 8.330e-02 Loss in Target Net: 9.169e-03 |
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2020-01-31 22:13:00 Iteration 3650 Training Loss: 7.683e-02 Loss in Target Net: 1.085e-02 |
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