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2020-01-31 19:20:35 Iteration 1100 Training Loss: 7.073e-02 Loss in Target Net: 2.192e-03 |
2020-01-31 19:20:57 Iteration 1150 Training Loss: 7.299e-02 Loss in Target Net: 1.873e-03 |
2020-01-31 19:21:18 Iteration 1200 Training Loss: 6.669e-02 Loss in Target Net: 1.820e-03 |
2020-01-31 19:21:40 Iteration 1250 Training Loss: 6.658e-02 Loss in Target Net: 1.197e-03 |
2020-01-31 19:22:02 Iteration 1300 Training Loss: 6.493e-02 Loss in Target Net: 1.243e-03 |
2020-01-31 19:22:23 Iteration 1350 Training Loss: 7.160e-02 Loss in Target Net: 2.363e-03 |
2020-01-31 19:22:45 Iteration 1400 Training Loss: 6.632e-02 Loss in Target Net: 2.285e-03 |
2020-01-31 19:23:06 Iteration 1450 Training Loss: 6.798e-02 Loss in Target Net: 1.539e-03 |
2020-01-31 19:23:27 Iteration 1500 Training Loss: 6.871e-02 Loss in Target Net: 1.491e-03 |
2020-01-31 19:23:48 Iteration 1550 Training Loss: 6.398e-02 Loss in Target Net: 1.807e-03 |
2020-01-31 19:24:09 Iteration 1600 Training Loss: 6.608e-02 Loss in Target Net: 1.925e-03 |
2020-01-31 19:24:31 Iteration 1650 Training Loss: 6.605e-02 Loss in Target Net: 1.509e-03 |
2020-01-31 19:24:52 Iteration 1700 Training Loss: 6.824e-02 Loss in Target Net: 1.868e-03 |
2020-01-31 19:25:13 Iteration 1750 Training Loss: 6.854e-02 Loss in Target Net: 2.202e-03 |
2020-01-31 19:25:35 Iteration 1800 Training Loss: 6.741e-02 Loss in Target Net: 2.461e-03 |
2020-01-31 19:25:56 Iteration 1850 Training Loss: 7.003e-02 Loss in Target Net: 1.379e-03 |
2020-01-31 19:26:17 Iteration 1900 Training Loss: 7.277e-02 Loss in Target Net: 2.033e-03 |
2020-01-31 19:26:39 Iteration 1950 Training Loss: 6.689e-02 Loss in Target Net: 1.346e-03 |
2020-01-31 19:27:00 Iteration 2000 Training Loss: 6.980e-02 Loss in Target Net: 2.681e-03 |
2020-01-31 19:27:22 Iteration 2050 Training Loss: 6.302e-02 Loss in Target Net: 1.875e-03 |
2020-01-31 19:27:44 Iteration 2100 Training Loss: 5.918e-02 Loss in Target Net: 1.986e-03 |
2020-01-31 19:28:05 Iteration 2150 Training Loss: 6.446e-02 Loss in Target Net: 3.496e-03 |
2020-01-31 19:28:27 Iteration 2200 Training Loss: 6.586e-02 Loss in Target Net: 3.283e-03 |
2020-01-31 19:28:48 Iteration 2250 Training Loss: 7.120e-02 Loss in Target Net: 2.110e-03 |
2020-01-31 19:29:10 Iteration 2300 Training Loss: 7.282e-02 Loss in Target Net: 1.864e-03 |
2020-01-31 19:29:31 Iteration 2350 Training Loss: 6.265e-02 Loss in Target Net: 1.697e-03 |
2020-01-31 19:29:52 Iteration 2400 Training Loss: 7.099e-02 Loss in Target Net: 1.688e-03 |
2020-01-31 19:30:14 Iteration 2450 Training Loss: 6.905e-02 Loss in Target Net: 3.805e-03 |
2020-01-31 19:30:36 Iteration 2500 Training Loss: 6.547e-02 Loss in Target Net: 3.288e-03 |
2020-01-31 19:30:57 Iteration 2550 Training Loss: 6.310e-02 Loss in Target Net: 4.250e-03 |
2020-01-31 19:31:18 Iteration 2600 Training Loss: 6.962e-02 Loss in Target Net: 2.578e-03 |
2020-01-31 19:31:40 Iteration 2650 Training Loss: 6.962e-02 Loss in Target Net: 3.054e-03 |
2020-01-31 19:32:02 Iteration 2700 Training Loss: 6.462e-02 Loss in Target Net: 2.908e-03 |
2020-01-31 19:32:23 Iteration 2750 Training Loss: 6.576e-02 Loss in Target Net: 2.023e-03 |
2020-01-31 19:32:46 Iteration 2800 Training Loss: 6.600e-02 Loss in Target Net: 2.267e-03 |
2020-01-31 19:33:07 Iteration 2850 Training Loss: 6.473e-02 Loss in Target Net: 3.348e-03 |
2020-01-31 19:33:29 Iteration 2900 Training Loss: 6.359e-02 Loss in Target Net: 3.267e-03 |
2020-01-31 19:33:51 Iteration 2950 Training Loss: 6.402e-02 Loss in Target Net: 3.926e-03 |
2020-01-31 19:34:12 Iteration 3000 Training Loss: 6.783e-02 Loss in Target Net: 3.318e-03 |
2020-01-31 19:34:34 Iteration 3050 Training Loss: 6.688e-02 Loss in Target Net: 1.945e-03 |
2020-01-31 19:34:56 Iteration 3100 Training Loss: 6.680e-02 Loss in Target Net: 2.479e-03 |
2020-01-31 19:35:18 Iteration 3150 Training Loss: 6.417e-02 Loss in Target Net: 1.428e-03 |
2020-01-31 19:35:39 Iteration 3200 Training Loss: 7.030e-02 Loss in Target Net: 2.704e-03 |
2020-01-31 19:36:01 Iteration 3250 Training Loss: 7.002e-02 Loss in Target Net: 4.194e-03 |
2020-01-31 19:36:23 Iteration 3300 Training Loss: 7.042e-02 Loss in Target Net: 2.510e-03 |
2020-01-31 19:36:45 Iteration 3350 Training Loss: 7.163e-02 Loss in Target Net: 1.514e-03 |
2020-01-31 19:37:07 Iteration 3400 Training Loss: 6.528e-02 Loss in Target Net: 2.473e-03 |
2020-01-31 19:37:29 Iteration 3450 Training Loss: 6.312e-02 Loss in Target Net: 1.520e-03 |
2020-01-31 19:37:50 Iteration 3500 Training Loss: 6.665e-02 Loss in Target Net: 2.075e-03 |
2020-01-31 19:38:12 Iteration 3550 Training Loss: 7.309e-02 Loss in Target Net: 3.360e-03 |
2020-01-31 19:38:34 Iteration 3600 Training Loss: 6.835e-02 Loss in Target Net: 4.575e-03 |
2020-01-31 19:38:55 Iteration 3650 Training Loss: 6.688e-02 Loss in Target Net: 4.173e-03 |
2020-01-31 19:39:17 Iteration 3700 Training Loss: 7.127e-02 Loss in Target Net: 2.958e-03 |
2020-01-31 19:39:38 Iteration 3750 Training Loss: 7.239e-02 Loss in Target Net: 2.267e-03 |
2020-01-31 19:40:00 Iteration 3800 Training Loss: 6.923e-02 Loss in Target Net: 1.508e-03 |
2020-01-31 19:40:22 Iteration 3850 Training Loss: 6.402e-02 Loss in Target Net: 2.720e-03 |
2020-01-31 19:40:44 Iteration 3900 Training Loss: 6.902e-02 Loss in Target Net: 5.218e-03 |
2020-01-31 19:41:07 Iteration 3950 Training Loss: 6.355e-02 Loss in Target Net: 2.580e-03 |
2020-01-31 19:41:29 Iteration 3999 Training Loss: 6.958e-02 Loss in Target Net: 3.158e-03 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:41:33, Epoch 0, Iteration 7, loss 1.958 (4.546), acc 84.615 (61.800) |
2020-01-31 19:41:33, Epoch 30, Iteration 7, loss 0.060 (0.052), acc 96.154 (97.800) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[16.266794, -25.043219, -40.3602, 12.213663, -16.989603, 5.5647864, 48.773693, -69.13261, 40.53643, -67.94683], Poisons' Predictions:[8, 8, 8, 8, 6] |
2020-01-31 19:41:37 Epoch 59, Val iteration 0, acc 90.400 (90.400) |
2020-01-31 19:41:44 Epoch 59, Val iteration 19, acc 92.800 (91.870) |
* Prec: 91.87000122070313 |
-------- |
SENet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:41:46, Epoch 0, Iteration 7, loss 0.898 (0.887), acc 94.231 (84.000) |
2020-01-31 19:41:47, Epoch 30, Iteration 7, loss 0.139 (0.273), acc 94.231 (95.000) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[0.7641646, -1.5907264, -6.131378, -0.4686064, 9.488911, -6.787756, 25.205393, -0.6458482, 20.096857, -11.757098], Poisons' Predictions:[6, 6, 6, 8, 8] |
2020-01-31 19:41:47 Epoch 59, Val iteration 0, acc 91.600 (91.600) |
2020-01-31 19:41:50 Epoch 59, Val iteration 19, acc 92.800 (91.520) |
* Prec: 91.52000045776367 |
-------- |
ResNet50 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:41:52, Epoch 0, Iteration 7, loss 0.000 (0.831), acc 100.000 (87.800) |
2020-01-31 19:41:52, Epoch 30, Iteration 7, loss 0.017 (0.003), acc 98.077 (99.800) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-62.869694, -19.004114, -87.70876, -9.671084, -49.884735, -71.16001, 20.684166, -28.707817, 16.138489, -21.672539], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:41:53 Epoch 59, Val iteration 0, acc 90.800 (90.800) |
2020-01-31 19:41:58 Epoch 59, Val iteration 19, acc 92.800 (91.850) |
* Prec: 91.85000190734863 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 19:42:00, Epoch 0, Iteration 7, loss 0.554 (1.738), acc 96.154 (74.400) |
2020-01-31 19:42:00, Epoch 30, Iteration 7, loss 0.104 (0.121), acc 98.077 (98.000) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-34.928352, 11.976488, -2.4080224, 2.8417864, -51.467525, -32.735332, 30.284172, -24.097425, 28.098022, -22.389055], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 19:42:01 Epoch 59, Val iteration 0, acc 93.400 (93.400) |
2020-01-31 19:42:05 Epoch 59, Val iteration 19, acc 92.400 (92.480) |
* Prec: 92.48000144958496 |
-------- |
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