text stringlengths 5 1.13k |
|---|
ResNet50 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:16:00, Epoch 0, Iteration 7, loss 1.239 (1.375), acc 98.077 (87.400) |
2020-01-31 19:16:00, Epoch 30, Iteration 7, loss 0.000 (0.003), acc 100.000 (99.800) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-44.217213, -62.451237, -79.09878, -26.031553, -48.955692, -92.1954, 16.652187, -80.38462, 22.092253, -49.990993], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:16:01 Epoch 59, Val iteration 0, acc 93.200 (93.200) |
2020-01-31 19:16:06 Epoch 59, Val iteration 19, acc 93.000 (93.180) |
* Prec: 93.18000183105468 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:16:08, Epoch 0, Iteration 7, loss 0.984 (2.182), acc 84.615 (74.000) |
2020-01-31 19:16:09, Epoch 30, Iteration 7, loss 0.049 (0.063), acc 98.077 (98.200) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-18.288609, -28.452286, -3.2343693, 2.8248582, -69.501785, -10.523266, 27.566824, -24.905928, 29.119324, -11.536506], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:16:10 Epoch 59, Val iteration 0, acc 93.600 (93.600) |
2020-01-31 19:16:14 Epoch 59, Val iteration 19, acc 94.000 (92.930) |
* Prec: 92.93000106811523 |
-------- |
GoogLeNet |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:16:17, Epoch 0, Iteration 7, loss 0.473 (0.385), acc 96.154 (90.800) |
2020-01-31 19:16:17, Epoch 30, Iteration 7, loss 0.009 (0.059), acc 100.000 (97.400) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-28.580788, -8.593496, -10.494123, -0.6767578, -12.310883, -4.608888, 10.022423, -9.189955, 6.909432, -36.686237], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:16:20 Epoch 59, Val iteration 0, acc 91.800 (91.800) |
2020-01-31 19:16:24 Epoch 59, Val iteration 19, acc 93.000 (92.480) |
* Prec: 92.4800018310547 |
-------- |
MobileNetV2 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:16:26, Epoch 0, Iteration 7, loss 1.149 (3.519), acc 73.077 (62.000) |
2020-01-31 19:16:27, Epoch 30, Iteration 7, loss 0.127 (0.341), acc 96.154 (92.600) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-5.9878144, -46.63283, 5.349029, 15.590833, -25.291813, 8.811747, 15.085906, -7.7270412, 17.918005, -41.00637], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:16:28 Epoch 59, Val iteration 0, acc 89.600 (89.600) |
2020-01-31 19:16:30 Epoch 59, Val iteration 19, acc 88.600 (87.790) |
* Prec: 87.7900016784668 |
-------- |
ResNet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:16:31, Epoch 0, Iteration 7, loss 1.169 (0.817), acc 84.615 (87.600) |
2020-01-31 19:16:32, Epoch 30, Iteration 7, loss 0.007 (0.020), acc 100.000 (99.200) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-30.154024, -11.406198, -12.537858, 2.2149808, -27.089966, -5.96735, 11.158428, -26.223124, 8.598501, -22.436687], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:16:32 Epoch 59, Val iteration 0, acc 93.600 (93.600) |
2020-01-31 19:16:34 Epoch 59, Val iteration 19, acc 94.400 (93.010) |
* Prec: 93.01000137329102 |
-------- |
DenseNet121 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:16:37, Epoch 0, Iteration 7, loss 0.507 (0.406), acc 86.538 (93.200) |
2020-01-31 19:16:37, Epoch 30, Iteration 7, loss 0.002 (0.003), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-13.218986, -19.224167, -12.988846, -4.090385, -14.940347, -0.33924755, 5.0010605, -42.949615, 6.3363895, -21.250078], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:16:39 Epoch 59, Val iteration 0, acc 93.800 (93.800) |
2020-01-31 19:16:43 Epoch 59, Val iteration 19, acc 94.200 (93.280) |
* Prec: 93.28000106811524 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 28 |
TARGET INDEX: 12 |
DPN92 1 |
SENet18 0 |
ResNet50 1 |
ResNeXt29_2x64d 1 |
GoogLeNet 0 |
MobileNetV2 1 |
ResNet18 0 |
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=13, 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/4000/13 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-01-31 18:42:20 Iteration 0 Training Loss: 1.130e+00 Loss in Target Net: 4.538e-01 |
2020-01-31 18:42:42 Iteration 50 Training Loss: 9.566e-02 Loss in Target Net: 2.242e-02 |
2020-01-31 18:43:05 Iteration 100 Training Loss: 8.484e-02 Loss in Target Net: 2.453e-02 |
2020-01-31 18:43:28 Iteration 150 Training Loss: 7.625e-02 Loss in Target Net: 2.855e-02 |
2020-01-31 18:43:52 Iteration 200 Training Loss: 6.956e-02 Loss in Target Net: 1.922e-02 |
2020-01-31 18:44:15 Iteration 250 Training Loss: 6.752e-02 Loss in Target Net: 1.442e-02 |
2020-01-31 18:44:38 Iteration 300 Training Loss: 7.107e-02 Loss in Target Net: 2.844e-02 |
2020-01-31 18:45:00 Iteration 350 Training Loss: 7.674e-02 Loss in Target Net: 1.748e-02 |
2020-01-31 18:45:23 Iteration 400 Training Loss: 7.042e-02 Loss in Target Net: 1.837e-02 |
2020-01-31 18:45:45 Iteration 450 Training Loss: 6.837e-02 Loss in Target Net: 2.169e-02 |
2020-01-31 18:46:08 Iteration 500 Training Loss: 8.460e-02 Loss in Target Net: 1.967e-02 |
2020-01-31 18:46:31 Iteration 550 Training Loss: 7.428e-02 Loss in Target Net: 2.026e-02 |
2020-01-31 18:46:53 Iteration 600 Training Loss: 7.307e-02 Loss in Target Net: 1.972e-02 |
2020-01-31 18:47:14 Iteration 650 Training Loss: 6.430e-02 Loss in Target Net: 1.555e-02 |
2020-01-31 18:47:37 Iteration 700 Training Loss: 6.898e-02 Loss in Target Net: 2.053e-02 |
2020-01-31 18:47:58 Iteration 750 Training Loss: 7.570e-02 Loss in Target Net: 1.404e-02 |
2020-01-31 18:48:19 Iteration 800 Training Loss: 6.862e-02 Loss in Target Net: 1.593e-02 |
2020-01-31 18:48:41 Iteration 850 Training Loss: 7.104e-02 Loss in Target Net: 2.320e-02 |
2020-01-31 18:49:05 Iteration 900 Training Loss: 7.252e-02 Loss in Target Net: 2.239e-02 |
2020-01-31 18:49:27 Iteration 950 Training Loss: 7.103e-02 Loss in Target Net: 2.602e-02 |
2020-01-31 18:49:49 Iteration 1000 Training Loss: 7.201e-02 Loss in Target Net: 2.503e-02 |
2020-01-31 18:50:10 Iteration 1050 Training Loss: 6.809e-02 Loss in Target Net: 1.788e-02 |
2020-01-31 18:50:32 Iteration 1100 Training Loss: 7.496e-02 Loss in Target Net: 2.229e-02 |
2020-01-31 18:50:53 Iteration 1150 Training Loss: 7.171e-02 Loss in Target Net: 1.834e-02 |
2020-01-31 18:51:14 Iteration 1200 Training Loss: 6.658e-02 Loss in Target Net: 1.951e-02 |
2020-01-31 18:51:35 Iteration 1250 Training Loss: 6.810e-02 Loss in Target Net: 1.558e-02 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.