text stringlengths 5 1.13k |
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2020-02-04 23:15:45 Epoch 59, Val iteration 0, acc 87.600 (87.600) |
2020-02-04 23:15:54 Epoch 59, Val iteration 19, acc 88.000 (86.630) |
* Prec: 86.6300006866455 |
-------- |
ResNet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:15:56, Epoch 0, Iteration 7, loss 0.223 (0.748), acc 90.385 (83.400) |
2020-02-04 23:15:57, Epoch 30, Iteration 7, loss 0.015 (0.023), acc 100.000 (98.800) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-39.240307, -6.504316, -10.84534, 3.052294, -29.225151, -3.001804, 8.725115, -22.438992, 12.082639, -27.141394], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 23:15:58 Epoch 59, Val iteration 0, acc 92.800 (92.800) |
2020-02-04 23:16:04 Epoch 59, Val iteration 19, acc 93.600 (92.610) |
* Prec: 92.61000137329101 |
-------- |
DenseNet121 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:16:12, Epoch 0, Iteration 7, loss 0.048 (0.438), acc 96.154 (91.200) |
2020-02-04 23:16:13, Epoch 30, Iteration 7, loss 0.001 (0.002), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-3.8906531, -20.062126, -15.766743, -2.8586793, -18.434946, -6.2375555, 1.3481308, -29.675678, 3.2883425, -18.27353], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 23:16:24 Epoch 59, Val iteration 0, acc 93.800 (93.800) |
2020-02-04 23:16:57 Epoch 59, Val iteration 19, acc 93.800 (93.170) |
* Prec: 93.17000122070313 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 111 |
TARGET INDEX: 48 |
DPN92 0 |
SENet18 1 |
ResNet50 1 |
ResNeXt29_2x64d 0 |
GoogLeNet 0 |
MobileNetV2 0 |
ResNet18 1 |
DenseNet121 1 |
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=49, 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/4000/49 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-02-04 21:20:51 Iteration 0 Training Loss: 1.046e+00 Loss in Target Net: 4.094e-01 |
2020-02-04 21:22:04 Iteration 50 Training Loss: 1.276e-01 Loss in Target Net: 3.563e-02 |
2020-02-04 21:23:20 Iteration 100 Training Loss: 1.126e-01 Loss in Target Net: 3.723e-02 |
2020-02-04 21:24:35 Iteration 150 Training Loss: 1.098e-01 Loss in Target Net: 2.207e-02 |
2020-02-04 21:25:51 Iteration 200 Training Loss: 1.028e-01 Loss in Target Net: 6.653e-02 |
2020-02-04 21:27:07 Iteration 250 Training Loss: 9.597e-02 Loss in Target Net: 2.316e-02 |
2020-02-04 21:28:23 Iteration 300 Training Loss: 9.663e-02 Loss in Target Net: 3.064e-02 |
2020-02-04 21:29:39 Iteration 350 Training Loss: 9.672e-02 Loss in Target Net: 2.628e-02 |
2020-02-04 21:30:56 Iteration 400 Training Loss: 9.962e-02 Loss in Target Net: 2.485e-02 |
2020-02-04 21:32:12 Iteration 450 Training Loss: 9.563e-02 Loss in Target Net: 2.045e-02 |
2020-02-04 21:33:28 Iteration 500 Training Loss: 1.015e-01 Loss in Target Net: 3.249e-02 |
2020-02-04 21:34:45 Iteration 550 Training Loss: 9.827e-02 Loss in Target Net: 3.926e-02 |
2020-02-04 21:36:01 Iteration 600 Training Loss: 9.922e-02 Loss in Target Net: 3.637e-02 |
2020-02-04 21:37:18 Iteration 650 Training Loss: 9.894e-02 Loss in Target Net: 2.377e-02 |
2020-02-04 21:38:34 Iteration 700 Training Loss: 9.860e-02 Loss in Target Net: 3.235e-02 |
2020-02-04 21:39:52 Iteration 750 Training Loss: 1.046e-01 Loss in Target Net: 9.837e-03 |
2020-02-04 21:41:16 Iteration 800 Training Loss: 1.002e-01 Loss in Target Net: 2.654e-02 |
2020-02-04 21:42:44 Iteration 850 Training Loss: 8.994e-02 Loss in Target Net: 2.979e-02 |
2020-02-04 21:44:12 Iteration 900 Training Loss: 1.025e-01 Loss in Target Net: 1.802e-02 |
2020-02-04 21:45:41 Iteration 950 Training Loss: 1.008e-01 Loss in Target Net: 1.662e-02 |
2020-02-04 21:47:09 Iteration 1000 Training Loss: 1.000e-01 Loss in Target Net: 2.615e-02 |
2020-02-04 21:48:37 Iteration 1050 Training Loss: 9.440e-02 Loss in Target Net: 5.731e-02 |
2020-02-04 21:50:01 Iteration 1100 Training Loss: 1.010e-01 Loss in Target Net: 3.109e-02 |
2020-02-04 21:51:25 Iteration 1150 Training Loss: 9.974e-02 Loss in Target Net: 2.447e-02 |
2020-02-04 21:52:49 Iteration 1200 Training Loss: 1.022e-01 Loss in Target Net: 2.210e-02 |
2020-02-04 21:54:13 Iteration 1250 Training Loss: 9.327e-02 Loss in Target Net: 2.358e-02 |
2020-02-04 21:55:36 Iteration 1300 Training Loss: 9.214e-02 Loss in Target Net: 1.454e-02 |
2020-02-04 21:57:00 Iteration 1350 Training Loss: 1.009e-01 Loss in Target Net: 2.106e-02 |
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2020-02-04 21:59:45 Iteration 1450 Training Loss: 9.948e-02 Loss in Target Net: 2.527e-02 |
2020-02-04 22:01:06 Iteration 1500 Training Loss: 9.703e-02 Loss in Target Net: 2.852e-02 |
2020-02-04 22:02:28 Iteration 1550 Training Loss: 9.365e-02 Loss in Target Net: 2.339e-02 |
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2020-02-04 22:05:14 Iteration 1650 Training Loss: 9.270e-02 Loss in Target Net: 3.293e-02 |
2020-02-04 22:06:37 Iteration 1700 Training Loss: 1.033e-01 Loss in Target Net: 3.476e-02 |
2020-02-04 22:07:57 Iteration 1750 Training Loss: 9.682e-02 Loss in Target Net: 4.873e-02 |
2020-02-04 22:09:20 Iteration 1800 Training Loss: 9.597e-02 Loss in Target Net: 4.155e-02 |
2020-02-04 22:10:41 Iteration 1850 Training Loss: 9.288e-02 Loss in Target Net: 3.636e-02 |
2020-02-04 22:12:01 Iteration 1900 Training Loss: 9.347e-02 Loss in Target Net: 3.112e-02 |
2020-02-04 22:13:22 Iteration 1950 Training Loss: 9.652e-02 Loss in Target Net: 3.405e-02 |
2020-02-04 22:14:42 Iteration 2000 Training Loss: 9.771e-02 Loss in Target Net: 4.001e-02 |
2020-02-04 22:16:06 Iteration 2050 Training Loss: 8.526e-02 Loss in Target Net: 2.547e-02 |
2020-02-04 22:17:31 Iteration 2100 Training Loss: 8.868e-02 Loss in Target Net: 2.035e-02 |
2020-02-04 22:18:58 Iteration 2150 Training Loss: 1.081e-01 Loss in Target Net: 2.489e-02 |
2020-02-04 22:20:26 Iteration 2200 Training Loss: 9.388e-02 Loss in Target Net: 2.676e-02 |
2020-02-04 22:21:54 Iteration 2250 Training Loss: 1.019e-01 Loss in Target Net: 2.160e-02 |
2020-02-04 22:23:21 Iteration 2300 Training Loss: 9.165e-02 Loss in Target Net: 2.006e-02 |
2020-02-04 22:24:48 Iteration 2350 Training Loss: 9.453e-02 Loss in Target Net: 2.202e-02 |
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2020-02-04 22:27:41 Iteration 2450 Training Loss: 9.955e-02 Loss in Target Net: 1.888e-02 |
2020-02-04 22:29:05 Iteration 2500 Training Loss: 9.269e-02 Loss in Target Net: 2.793e-02 |
2020-02-04 22:30:30 Iteration 2550 Training Loss: 9.822e-02 Loss in Target Net: 2.397e-02 |
2020-02-04 22:31:53 Iteration 2600 Training Loss: 9.078e-02 Loss in Target Net: 1.810e-02 |
2020-02-04 22:33:19 Iteration 2650 Training Loss: 9.687e-02 Loss in Target Net: 2.577e-02 |
2020-02-04 22:34:44 Iteration 2700 Training Loss: 8.896e-02 Loss in Target Net: 1.889e-02 |
2020-02-04 22:36:12 Iteration 2750 Training Loss: 9.496e-02 Loss in Target Net: 2.193e-02 |
2020-02-04 22:37:38 Iteration 2800 Training Loss: 9.724e-02 Loss in Target Net: 2.202e-02 |
2020-02-04 22:39:04 Iteration 2850 Training Loss: 8.875e-02 Loss in Target Net: 2.877e-02 |
2020-02-04 22:40:31 Iteration 2900 Training Loss: 9.128e-02 Loss in Target Net: 1.836e-02 |
2020-02-04 22:41:54 Iteration 2950 Training Loss: 1.035e-01 Loss in Target Net: 2.591e-02 |
2020-02-04 22:43:18 Iteration 3000 Training Loss: 9.756e-02 Loss in Target Net: 2.696e-02 |
2020-02-04 22:44:42 Iteration 3050 Training Loss: 9.283e-02 Loss in Target Net: 2.392e-02 |
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