text stringlengths 5 1.13k |
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ResNet50 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 21:42:05, Epoch 0, Iteration 7, loss 0.892 (0.843), acc 98.077 (90.200) |
2020-01-31 21:42:05, Epoch 30, Iteration 7, loss 0.155 (0.082), acc 98.077 (98.800) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-37.514507, -28.76503, -22.987087, -0.7173318, -39.209152, -29.824991, 22.154846, -30.747126, 24.852787, -91.78272], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 21:42:07 Epoch 59, Val iteration 0, acc 91.800 (91.800) |
2020-01-31 21:42:11 Epoch 59, Val iteration 19, acc 93.600 (92.730) |
* Prec: 92.73000144958496 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 21:42:13, Epoch 0, Iteration 7, loss 2.338 (2.380), acc 75.000 (72.200) |
2020-01-31 21:42:13, Epoch 30, Iteration 7, loss 0.092 (0.084), acc 98.077 (98.200) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-23.126953, -8.325205, -12.042802, 8.005905, -67.1255, -24.023602, 26.121704, -42.51954, 26.211662, -13.880123], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 21:42:15 Epoch 59, Val iteration 0, acc 93.600 (93.600) |
2020-01-31 21:42:19 Epoch 59, Val iteration 19, acc 93.000 (93.150) |
* Prec: 93.15000114440917 |
-------- |
GoogLeNet |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 21:42:21, Epoch 0, Iteration 7, loss 0.393 (0.377), acc 90.385 (89.800) |
2020-01-31 21:42:22, Epoch 30, Iteration 7, loss 0.028 (0.070), acc 98.077 (97.400) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-18.432835, -6.2493887, -9.964614, 0.29903194, -11.726366, -3.6388135, 13.212432, -14.640512, 10.939515, -8.351794], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 21:42:24 Epoch 59, Val iteration 0, acc 91.800 (91.800) |
2020-01-31 21:42:29 Epoch 59, Val iteration 19, acc 91.600 (91.880) |
* Prec: 91.88000183105468 |
-------- |
MobileNetV2 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 21:42:31, Epoch 0, Iteration 7, loss 2.195 (3.694), acc 63.462 (57.400) |
2020-01-31 21:42:31, Epoch 30, Iteration 7, loss 0.148 (0.311), acc 96.154 (94.400) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[8.472802, -5.197592, -1.4159108, 19.858067, -21.365225, 2.0658398, 35.466644, -36.391003, 29.614807, -12.052587], Poisons' Predictions:[8, 8, 6, 8, 6] |
2020-01-31 21:42:32 Epoch 59, Val iteration 0, acc 89.000 (89.000) |
2020-01-31 21:42:34 Epoch 59, Val iteration 19, acc 88.800 (87.730) |
* Prec: 87.73000221252441 |
-------- |
ResNet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 21:42:36, Epoch 0, Iteration 7, loss 0.642 (0.549), acc 86.538 (88.200) |
2020-01-31 21:42:36, Epoch 30, Iteration 7, loss 0.068 (0.042), acc 96.154 (98.400) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-21.440796, -3.97088, -18.955355, 0.71239465, -41.216022, -2.838943, 11.2640705, -14.239597, 9.025126, -37.201527], Poisons' Predictions:[8, 8, 8, 8, 6] |
2020-01-31 21:42:37 Epoch 59, Val iteration 0, acc 93.000 (93.000) |
2020-01-31 21:42:39 Epoch 59, Val iteration 19, acc 92.800 (92.490) |
* Prec: 92.4900016784668 |
-------- |
DenseNet121 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 21:42:42, Epoch 0, Iteration 7, loss 0.811 (0.454), acc 88.462 (91.600) |
2020-01-31 21:42:42, Epoch 30, Iteration 7, loss 0.001 (0.015), acc 100.000 (99.200) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-10.079089, -17.041368, -15.026478, -3.5633771, -6.707017, -5.717787, 7.2961707, -30.577707, 3.6254685, -19.268496], Poisons' Predictions:[8, 8, 8, 6, 8] |
2020-01-31 21:42:44 Epoch 59, Val iteration 0, acc 94.200 (94.200) |
2020-01-31 21:42:48 Epoch 59, Val iteration 19, acc 92.800 (93.020) |
* Prec: 93.0200008392334 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 30 |
TARGET INDEX: 35 |
DPN92 1 |
SENet18 0 |
ResNet50 1 |
ResNeXt29_2x64d 1 |
GoogLeNet 0 |
MobileNetV2 0 |
ResNet18 0 |
DenseNet121 0 |
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=36, 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/4000/36 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-01-31 21:47:36 Iteration 0 Training Loss: 1.144e+00 Loss in Target Net: 4.305e-01 |
2020-01-31 21:47:56 Iteration 50 Training Loss: 1.151e-01 Loss in Target Net: 3.640e-02 |
2020-01-31 21:48:16 Iteration 100 Training Loss: 9.349e-02 Loss in Target Net: 2.423e-02 |
2020-01-31 21:48:36 Iteration 150 Training Loss: 8.956e-02 Loss in Target Net: 1.894e-02 |
2020-01-31 21:48:56 Iteration 200 Training Loss: 9.076e-02 Loss in Target Net: 1.608e-02 |
2020-01-31 21:49:17 Iteration 250 Training Loss: 8.592e-02 Loss in Target Net: 1.914e-02 |
2020-01-31 21:49:37 Iteration 300 Training Loss: 9.221e-02 Loss in Target Net: 1.918e-02 |
2020-01-31 21:49:57 Iteration 350 Training Loss: 8.142e-02 Loss in Target Net: 1.487e-02 |
2020-01-31 21:50:17 Iteration 400 Training Loss: 8.095e-02 Loss in Target Net: 1.820e-02 |
2020-01-31 21:50:38 Iteration 450 Training Loss: 8.026e-02 Loss in Target Net: 1.978e-02 |
2020-01-31 21:50:58 Iteration 500 Training Loss: 8.529e-02 Loss in Target Net: 1.759e-02 |
2020-01-31 21:51:18 Iteration 550 Training Loss: 8.655e-02 Loss in Target Net: 1.734e-02 |
2020-01-31 21:51:38 Iteration 600 Training Loss: 7.433e-02 Loss in Target Net: 1.840e-02 |
2020-01-31 21:51:59 Iteration 650 Training Loss: 7.646e-02 Loss in Target Net: 1.833e-02 |
2020-01-31 21:52:20 Iteration 700 Training Loss: 8.656e-02 Loss in Target Net: 1.496e-02 |
2020-01-31 21:52:40 Iteration 750 Training Loss: 7.649e-02 Loss in Target Net: 1.646e-02 |
2020-01-31 21:53:01 Iteration 800 Training Loss: 8.502e-02 Loss in Target Net: 2.312e-02 |
2020-01-31 21:53:21 Iteration 850 Training Loss: 8.437e-02 Loss in Target Net: 2.006e-02 |
2020-01-31 21:53:41 Iteration 900 Training Loss: 8.036e-02 Loss in Target Net: 1.878e-02 |
2020-01-31 21:54:01 Iteration 950 Training Loss: 7.854e-02 Loss in Target Net: 1.873e-02 |
2020-01-31 21:54:21 Iteration 1000 Training Loss: 7.565e-02 Loss in Target Net: 1.762e-02 |
2020-01-31 21:54:42 Iteration 1050 Training Loss: 8.592e-02 Loss in Target Net: 2.719e-02 |
2020-01-31 21:55:02 Iteration 1100 Training Loss: 7.703e-02 Loss in Target Net: 2.083e-02 |
2020-01-31 21:55:22 Iteration 1150 Training Loss: 7.849e-02 Loss in Target Net: 1.758e-02 |
2020-01-31 21:55:43 Iteration 1200 Training Loss: 8.074e-02 Loss in Target Net: 1.422e-02 |
2020-01-31 21:56:03 Iteration 1250 Training Loss: 7.646e-02 Loss in Target Net: 1.230e-02 |
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