text stringlengths 5 1.13k |
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Files already downloaded and verified |
2020-02-04 23:22:31, Epoch 0, Iteration 7, loss 1.294 (0.804), acc 88.462 (85.200) |
2020-02-04 23:22:32, Epoch 30, Iteration 7, loss 0.021 (0.199), acc 98.077 (94.800) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[1.3134378, 3.5888453, -7.111573, -7.4007096, -5.4352355, -12.896159, 24.67191, -10.496454, 22.193798, -16.295156], Poisons' Predictions:[6, 6, 6, 8, 6] |
2020-02-04 23:22:36 Epoch 59, Val iteration 0, acc 91.400 (91.400) |
2020-02-04 23:22:45 Epoch 59, Val iteration 19, acc 92.600 (91.100) |
* Prec: 91.10000076293946 |
-------- |
ResNet50 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:22:52, Epoch 0, Iteration 7, loss 0.000 (1.221), acc 100.000 (83.200) |
2020-02-04 23:22:52, Epoch 30, Iteration 7, loss 0.000 (0.120), acc 100.000 (99.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-31.481293, -39.490772, -36.75363, -48.18938, -19.111897, -53.73562, 19.696453, -36.158245, 24.796457, -33.15817], Poisons' Predictions:[8, 8, 8, 8, 6] |
2020-02-04 23:23:00 Epoch 59, Val iteration 0, acc 91.600 (91.600) |
2020-02-04 23:23:22 Epoch 59, Val iteration 19, acc 92.400 (92.300) |
* Prec: 92.30000190734863 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:23:29, Epoch 0, Iteration 7, loss 0.484 (2.590), acc 94.231 (69.600) |
2020-02-04 23:23:30, Epoch 30, Iteration 7, loss 0.022 (0.068), acc 98.077 (97.800) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-37.92073, -17.60394, -13.258503, 11.053249, -61.529194, -22.760818, 27.397123, -33.47982, 26.397018, -29.05255], Poisons' Predictions:[8, 8, 6, 8, 8] |
2020-02-04 23:23:37 Epoch 59, Val iteration 0, acc 92.600 (92.600) |
2020-02-04 23:23:58 Epoch 59, Val iteration 19, acc 92.800 (92.500) |
* Prec: 92.50000190734863 |
-------- |
GoogLeNet |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:24:07, Epoch 0, Iteration 7, loss 0.495 (0.496), acc 90.385 (89.600) |
2020-02-04 23:24:08, Epoch 30, Iteration 7, loss 0.178 (0.097), acc 94.231 (96.600) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-25.819323, -6.417992, -19.053488, -0.42072248, -8.322805, -5.121664, 10.838119, -14.003453, 7.337009, -18.113684], Poisons' Predictions:[8, 8, 6, 8, 8] |
2020-02-04 23:24:24 Epoch 59, Val iteration 0, acc 91.400 (91.400) |
2020-02-04 23:24:56 Epoch 59, Val iteration 19, acc 91.400 (91.750) |
* Prec: 91.75000228881837 |
-------- |
MobileNetV2 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:25:01, Epoch 0, Iteration 7, loss 0.951 (2.693), acc 84.615 (68.000) |
2020-02-04 23:25:01, Epoch 30, Iteration 7, loss 0.005 (0.142), acc 100.000 (96.000) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-3.8427014, -18.500776, -4.184408, 15.187323, -16.903759, -2.1252933, 26.397943, -30.282602, 20.549255, -6.4471054], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 23:25:05 Epoch 59, Val iteration 0, acc 88.000 (88.000) |
2020-02-04 23:25:13 Epoch 59, Val iteration 19, acc 89.000 (86.890) |
* Prec: 86.89000091552734 |
-------- |
ResNet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:25:16, Epoch 0, Iteration 7, loss 0.441 (0.790), acc 94.231 (85.400) |
2020-02-04 23:25:16, Epoch 30, Iteration 7, loss 0.041 (0.030), acc 96.154 (98.600) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-25.486286, -13.320967, -17.987967, 1.2957379, -41.142246, -10.426809, 10.442381, -14.809189, 8.767753, -35.960743], Poisons' Predictions:[8, 6, 8, 8, 8] |
2020-02-04 23:25:17 Epoch 59, Val iteration 0, acc 93.600 (93.600) |
2020-02-04 23:25:24 Epoch 59, Val iteration 19, acc 93.400 (92.910) |
* Prec: 92.91000137329101 |
-------- |
DenseNet121 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:25:32, Epoch 0, Iteration 7, loss 0.154 (0.416), acc 96.154 (91.000) |
2020-02-04 23:25:33, Epoch 30, Iteration 7, loss 0.009 (0.009), acc 100.000 (99.800) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-11.018138, -20.414469, -15.569078, -5.321678, -9.721191, -4.6456246, 5.4578524, -31.852264, 4.3198905, -12.82981], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 23:25:44 Epoch 59, Val iteration 0, acc 93.400 (93.400) |
2020-02-04 23:26:08 Epoch 59, Val iteration 19, acc 92.600 (93.070) |
* Prec: 93.07000198364258 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 119 |
TARGET INDEX: 42 |
DPN92 0 |
SENet18 0 |
ResNet50 1 |
ResNeXt29_2x64d 0 |
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='11', 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=43, 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/4000/43 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-02-04 21:22:01 Iteration 0 Training Loss: 1.085e+00 Loss in Target Net: 3.316e-01 |
2020-02-04 21:23:17 Iteration 50 Training Loss: 7.720e-02 Loss in Target Net: 2.134e-03 |
2020-02-04 21:24:34 Iteration 100 Training Loss: 6.813e-02 Loss in Target Net: 1.876e-03 |
2020-02-04 21:25:51 Iteration 150 Training Loss: 6.391e-02 Loss in Target Net: 1.800e-03 |
2020-02-04 21:27:09 Iteration 200 Training Loss: 5.984e-02 Loss in Target Net: 1.689e-03 |
2020-02-04 21:28:28 Iteration 250 Training Loss: 6.223e-02 Loss in Target Net: 2.559e-03 |
2020-02-04 21:29:47 Iteration 300 Training Loss: 6.129e-02 Loss in Target Net: 1.564e-03 |
2020-02-04 21:31:06 Iteration 350 Training Loss: 5.518e-02 Loss in Target Net: 1.698e-03 |
2020-02-04 21:32:24 Iteration 400 Training Loss: 5.738e-02 Loss in Target Net: 1.703e-03 |
2020-02-04 21:33:42 Iteration 450 Training Loss: 6.309e-02 Loss in Target Net: 1.841e-03 |
2020-02-04 21:35:01 Iteration 500 Training Loss: 6.821e-02 Loss in Target Net: 1.794e-03 |
2020-02-04 21:36:21 Iteration 550 Training Loss: 6.079e-02 Loss in Target Net: 1.999e-03 |
2020-02-04 21:37:41 Iteration 600 Training Loss: 6.023e-02 Loss in Target Net: 1.719e-03 |
2020-02-04 21:38:59 Iteration 650 Training Loss: 6.019e-02 Loss in Target Net: 1.648e-03 |
2020-02-04 21:40:26 Iteration 700 Training Loss: 5.913e-02 Loss in Target Net: 1.963e-03 |
2020-02-04 21:42:06 Iteration 750 Training Loss: 5.711e-02 Loss in Target Net: 1.605e-03 |
2020-02-04 21:43:50 Iteration 800 Training Loss: 5.997e-02 Loss in Target Net: 1.853e-03 |
2020-02-04 21:45:34 Iteration 850 Training Loss: 5.573e-02 Loss in Target Net: 2.032e-03 |
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