text stringlengths 5 1.13k |
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Files already downloaded and verified |
2020-02-04 23:15:27, Epoch 0, Iteration 7, loss 2.018 (3.214), acc 78.846 (63.800) |
2020-02-04 23:15:28, Epoch 30, Iteration 7, loss 0.139 (0.071), acc 96.154 (97.800) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-29.239113, -2.7244375, -21.69123, 8.974104, -80.85972, -36.160683, 24.116268, -29.05644, 26.703463, -27.535017], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 23:15:34 Epoch 59, Val iteration 0, acc 93.600 (93.600) |
2020-02-04 23:15:54 Epoch 59, Val iteration 19, acc 93.400 (93.080) |
* Prec: 93.08000144958496 |
-------- |
GoogLeNet |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:16:03, Epoch 0, Iteration 7, loss 0.100 (0.451), acc 98.077 (91.400) |
2020-02-04 23:16:03, Epoch 30, Iteration 7, loss 0.050 (0.053), acc 98.077 (98.400) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-22.874144, -5.1855865, -12.700701, -3.0007179, -11.683479, -9.365342, 8.803119, -3.5353098, 12.15925, -19.066133], Poisons' Predictions:[8, 8, 6, 8, 8] |
2020-02-04 23:16:18 Epoch 59, Val iteration 0, acc 91.600 (91.600) |
2020-02-04 23:16:53 Epoch 59, Val iteration 19, acc 92.000 (92.200) |
* Prec: 92.20000076293945 |
-------- |
MobileNetV2 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:16:58, Epoch 0, Iteration 7, loss 1.353 (3.841), acc 82.692 (60.000) |
2020-02-04 23:16:59, Epoch 30, Iteration 7, loss 1.744 (0.786), acc 84.615 (91.800) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-3.9585552, -23.444368, -7.0047474, 5.800369, -25.82168, -22.900616, 27.591545, -45.53626, 26.816402, -43.146477], Poisons' Predictions:[8, 8, 6, 8, 8] |
2020-02-04 23:17:02 Epoch 59, Val iteration 0, acc 90.200 (90.200) |
2020-02-04 23:17:10 Epoch 59, Val iteration 19, acc 89.000 (87.710) |
* Prec: 87.71000213623047 |
-------- |
ResNet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:17:13, Epoch 0, Iteration 7, loss 1.003 (0.735), acc 90.385 (86.400) |
2020-02-04 23:17:14, Epoch 30, Iteration 7, loss 0.005 (0.053), acc 100.000 (98.400) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-34.53253, -7.0625663, -20.673697, -2.8814526, -44.98263, -11.441255, 3.9468656, -26.037336, 4.8560824, -49.21774], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 23:17:14 Epoch 59, Val iteration 0, acc 93.600 (93.600) |
2020-02-04 23:17:21 Epoch 59, Val iteration 19, acc 93.600 (92.620) |
* Prec: 92.62000160217285 |
-------- |
DenseNet121 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:17:29, Epoch 0, Iteration 7, loss 0.436 (0.456), acc 96.154 (92.000) |
2020-02-04 23:17:29, Epoch 30, Iteration 7, loss 0.015 (0.005), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-11.32942, -8.07976, -10.710932, -5.1111617, -8.961667, -6.504562, 3.500308, -29.190186, 7.2460313, -18.136395], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 23:17:40 Epoch 59, Val iteration 0, acc 94.000 (94.000) |
2020-02-04 23:18:06 Epoch 59, Val iteration 19, acc 92.400 (92.980) |
* Prec: 92.98000144958496 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 112 |
TARGET INDEX: 47 |
DPN92 1 |
SENet18 0 |
ResNet50 1 |
ResNeXt29_2x64d 1 |
GoogLeNet 1 |
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='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=48, 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/4000/48 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-02-04 21:20:18 Iteration 0 Training Loss: 1.063e+00 Loss in Target Net: 3.597e-01 |
2020-02-04 21:21:31 Iteration 50 Training Loss: 1.301e-01 Loss in Target Net: 2.349e-02 |
2020-02-04 21:22:45 Iteration 100 Training Loss: 1.116e-01 Loss in Target Net: 1.917e-02 |
2020-02-04 21:24:01 Iteration 150 Training Loss: 1.159e-01 Loss in Target Net: 1.218e-02 |
2020-02-04 21:25:17 Iteration 200 Training Loss: 1.191e-01 Loss in Target Net: 1.378e-02 |
2020-02-04 21:26:33 Iteration 250 Training Loss: 1.079e-01 Loss in Target Net: 1.738e-02 |
2020-02-04 21:27:49 Iteration 300 Training Loss: 1.169e-01 Loss in Target Net: 1.595e-02 |
2020-02-04 21:29:06 Iteration 350 Training Loss: 1.051e-01 Loss in Target Net: 1.551e-02 |
2020-02-04 21:30:22 Iteration 400 Training Loss: 1.135e-01 Loss in Target Net: 1.307e-02 |
2020-02-04 21:31:38 Iteration 450 Training Loss: 1.094e-01 Loss in Target Net: 1.290e-02 |
2020-02-04 21:32:55 Iteration 500 Training Loss: 9.790e-02 Loss in Target Net: 1.138e-02 |
2020-02-04 21:34:11 Iteration 550 Training Loss: 1.134e-01 Loss in Target Net: 1.407e-02 |
2020-02-04 21:35:28 Iteration 600 Training Loss: 1.094e-01 Loss in Target Net: 1.987e-02 |
2020-02-04 21:36:45 Iteration 650 Training Loss: 1.094e-01 Loss in Target Net: 1.788e-02 |
2020-02-04 21:38:01 Iteration 700 Training Loss: 1.006e-01 Loss in Target Net: 2.243e-02 |
2020-02-04 21:39:18 Iteration 750 Training Loss: 9.735e-02 Loss in Target Net: 1.938e-02 |
2020-02-04 21:40:40 Iteration 800 Training Loss: 1.008e-01 Loss in Target Net: 1.761e-02 |
2020-02-04 21:42:08 Iteration 850 Training Loss: 1.003e-01 Loss in Target Net: 1.899e-02 |
2020-02-04 21:43:38 Iteration 900 Training Loss: 1.069e-01 Loss in Target Net: 2.265e-02 |
2020-02-04 21:45:07 Iteration 950 Training Loss: 9.805e-02 Loss in Target Net: 2.543e-02 |
2020-02-04 21:46:35 Iteration 1000 Training Loss: 1.054e-01 Loss in Target Net: 2.149e-02 |
2020-02-04 21:48:04 Iteration 1050 Training Loss: 1.003e-01 Loss in Target Net: 2.401e-02 |
2020-02-04 21:49:31 Iteration 1100 Training Loss: 1.095e-01 Loss in Target Net: 2.066e-02 |
2020-02-04 21:50:55 Iteration 1150 Training Loss: 1.015e-01 Loss in Target Net: 2.066e-02 |
2020-02-04 21:52:19 Iteration 1200 Training Loss: 1.009e-01 Loss in Target Net: 1.442e-02 |
2020-02-04 21:53:43 Iteration 1250 Training Loss: 1.046e-01 Loss in Target Net: 1.724e-02 |
2020-02-04 21:55:08 Iteration 1300 Training Loss: 1.047e-01 Loss in Target Net: 2.029e-02 |
2020-02-04 21:56:32 Iteration 1350 Training Loss: 1.045e-01 Loss in Target Net: 1.256e-02 |
2020-02-04 21:57:56 Iteration 1400 Training Loss: 9.954e-02 Loss in Target Net: 7.717e-03 |
2020-02-04 21:59:19 Iteration 1450 Training Loss: 1.023e-01 Loss in Target Net: 1.131e-02 |
2020-02-04 22:00:41 Iteration 1500 Training Loss: 9.893e-02 Loss in Target Net: 1.744e-02 |
2020-02-04 22:02:03 Iteration 1550 Training Loss: 1.000e-01 Loss in Target Net: 1.102e-02 |
2020-02-04 22:03:26 Iteration 1600 Training Loss: 9.300e-02 Loss in Target Net: 1.354e-02 |
2020-02-04 22:04:49 Iteration 1650 Training Loss: 1.024e-01 Loss in Target Net: 1.243e-02 |
2020-02-04 22:06:13 Iteration 1700 Training Loss: 1.039e-01 Loss in Target Net: 1.842e-02 |
2020-02-04 22:07:35 Iteration 1750 Training Loss: 1.013e-01 Loss in Target Net: 1.744e-02 |
2020-02-04 22:08:56 Iteration 1800 Training Loss: 1.172e-01 Loss in Target Net: 1.465e-02 |
2020-02-04 22:10:18 Iteration 1850 Training Loss: 9.964e-02 Loss in Target Net: 1.832e-02 |
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