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2020-01-31 17:52:01 Iteration 1100 Training Loss: 6.569e-02 Loss in Target Net: 1.405e-02 |
2020-01-31 17:52:24 Iteration 1150 Training Loss: 6.886e-02 Loss in Target Net: 1.181e-02 |
2020-01-31 17:52:47 Iteration 1200 Training Loss: 6.973e-02 Loss in Target Net: 9.550e-03 |
2020-01-31 17:53:09 Iteration 1250 Training Loss: 6.717e-02 Loss in Target Net: 1.427e-02 |
2020-01-31 17:53:36 Iteration 1300 Training Loss: 6.362e-02 Loss in Target Net: 1.381e-02 |
2020-01-31 17:53:59 Iteration 1350 Training Loss: 7.188e-02 Loss in Target Net: 1.341e-02 |
2020-01-31 17:54:22 Iteration 1400 Training Loss: 6.409e-02 Loss in Target Net: 1.211e-02 |
2020-01-31 17:54:47 Iteration 1450 Training Loss: 6.406e-02 Loss in Target Net: 1.170e-02 |
2020-01-31 17:55:11 Iteration 1500 Training Loss: 6.019e-02 Loss in Target Net: 1.019e-02 |
2020-01-31 17:55:34 Iteration 1550 Training Loss: 6.208e-02 Loss in Target Net: 1.001e-02 |
2020-01-31 17:55:58 Iteration 1600 Training Loss: 7.050e-02 Loss in Target Net: 1.001e-02 |
2020-01-31 17:56:23 Iteration 1650 Training Loss: 6.396e-02 Loss in Target Net: 1.038e-02 |
2020-01-31 17:56:46 Iteration 1700 Training Loss: 6.978e-02 Loss in Target Net: 1.004e-02 |
2020-01-31 17:57:11 Iteration 1750 Training Loss: 6.730e-02 Loss in Target Net: 1.141e-02 |
2020-01-31 17:57:35 Iteration 1800 Training Loss: 6.486e-02 Loss in Target Net: 1.017e-02 |
2020-01-31 17:57:58 Iteration 1850 Training Loss: 6.971e-02 Loss in Target Net: 7.003e-03 |
2020-01-31 17:58:20 Iteration 1900 Training Loss: 6.716e-02 Loss in Target Net: 7.960e-03 |
2020-01-31 17:58:42 Iteration 1950 Training Loss: 6.894e-02 Loss in Target Net: 9.591e-03 |
2020-01-31 17:59:03 Iteration 2000 Training Loss: 6.622e-02 Loss in Target Net: 1.159e-02 |
2020-01-31 17:59:24 Iteration 2050 Training Loss: 6.442e-02 Loss in Target Net: 1.437e-02 |
2020-01-31 17:59:45 Iteration 2100 Training Loss: 6.814e-02 Loss in Target Net: 9.465e-03 |
2020-01-31 18:00:05 Iteration 2150 Training Loss: 6.557e-02 Loss in Target Net: 5.792e-03 |
2020-01-31 18:00:29 Iteration 2200 Training Loss: 6.322e-02 Loss in Target Net: 1.084e-02 |
2020-01-31 18:00:51 Iteration 2250 Training Loss: 6.782e-02 Loss in Target Net: 9.305e-03 |
2020-01-31 18:01:15 Iteration 2300 Training Loss: 6.903e-02 Loss in Target Net: 1.115e-02 |
2020-01-31 18:01:37 Iteration 2350 Training Loss: 6.994e-02 Loss in Target Net: 8.083e-03 |
2020-01-31 18:02:00 Iteration 2400 Training Loss: 6.010e-02 Loss in Target Net: 1.254e-02 |
2020-01-31 18:02:22 Iteration 2450 Training Loss: 7.139e-02 Loss in Target Net: 1.038e-02 |
2020-01-31 18:02:44 Iteration 2500 Training Loss: 6.802e-02 Loss in Target Net: 9.827e-03 |
2020-01-31 18:03:07 Iteration 2550 Training Loss: 6.811e-02 Loss in Target Net: 6.297e-03 |
2020-01-31 18:03:29 Iteration 2600 Training Loss: 6.248e-02 Loss in Target Net: 1.020e-02 |
2020-01-31 18:03:52 Iteration 2650 Training Loss: 6.265e-02 Loss in Target Net: 1.158e-02 |
2020-01-31 18:04:15 Iteration 2700 Training Loss: 6.732e-02 Loss in Target Net: 7.942e-03 |
2020-01-31 18:04:38 Iteration 2750 Training Loss: 6.199e-02 Loss in Target Net: 9.149e-03 |
2020-01-31 18:05:01 Iteration 2800 Training Loss: 6.409e-02 Loss in Target Net: 1.031e-02 |
2020-01-31 18:05:23 Iteration 2850 Training Loss: 6.374e-02 Loss in Target Net: 1.311e-02 |
2020-01-31 18:05:48 Iteration 2900 Training Loss: 6.059e-02 Loss in Target Net: 8.806e-03 |
2020-01-31 18:06:11 Iteration 2950 Training Loss: 6.474e-02 Loss in Target Net: 6.656e-03 |
2020-01-31 18:06:34 Iteration 3000 Training Loss: 6.282e-02 Loss in Target Net: 8.714e-03 |
2020-01-31 18:06:58 Iteration 3050 Training Loss: 6.711e-02 Loss in Target Net: 8.955e-03 |
2020-01-31 18:07:21 Iteration 3100 Training Loss: 6.594e-02 Loss in Target Net: 8.997e-03 |
2020-01-31 18:07:47 Iteration 3150 Training Loss: 6.647e-02 Loss in Target Net: 1.162e-02 |
2020-01-31 18:08:09 Iteration 3200 Training Loss: 6.632e-02 Loss in Target Net: 1.111e-02 |
2020-01-31 18:08:34 Iteration 3250 Training Loss: 6.062e-02 Loss in Target Net: 1.146e-02 |
2020-01-31 18:08:57 Iteration 3300 Training Loss: 6.604e-02 Loss in Target Net: 1.368e-02 |
2020-01-31 18:09:22 Iteration 3350 Training Loss: 6.267e-02 Loss in Target Net: 1.318e-02 |
2020-01-31 18:09:46 Iteration 3400 Training Loss: 6.302e-02 Loss in Target Net: 1.030e-02 |
2020-01-31 18:10:08 Iteration 3450 Training Loss: 6.232e-02 Loss in Target Net: 8.329e-03 |
2020-01-31 18:10:31 Iteration 3500 Training Loss: 6.671e-02 Loss in Target Net: 9.676e-03 |
2020-01-31 18:10:54 Iteration 3550 Training Loss: 6.779e-02 Loss in Target Net: 9.379e-03 |
2020-01-31 18:11:16 Iteration 3600 Training Loss: 6.539e-02 Loss in Target Net: 7.834e-03 |
2020-01-31 18:11:38 Iteration 3650 Training Loss: 7.064e-02 Loss in Target Net: 1.025e-02 |
2020-01-31 18:12:00 Iteration 3700 Training Loss: 7.045e-02 Loss in Target Net: 1.016e-02 |
2020-01-31 18:12:21 Iteration 3750 Training Loss: 5.913e-02 Loss in Target Net: 7.645e-03 |
2020-01-31 18:12:43 Iteration 3800 Training Loss: 6.283e-02 Loss in Target Net: 6.552e-03 |
2020-01-31 18:13:05 Iteration 3850 Training Loss: 6.862e-02 Loss in Target Net: 8.699e-03 |
2020-01-31 18:13:26 Iteration 3900 Training Loss: 6.944e-02 Loss in Target Net: 7.490e-03 |
2020-01-31 18:13:48 Iteration 3950 Training Loss: 6.554e-02 Loss in Target Net: 7.691e-03 |
2020-01-31 18:14:08 Iteration 3999 Training Loss: 6.670e-02 Loss in Target Net: 8.495e-03 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:14:12, Epoch 0, Iteration 7, loss 1.163 (3.307), acc 92.308 (74.600) |
2020-01-31 18:14:13, Epoch 30, Iteration 7, loss 1.492 (0.483), acc 86.538 (94.400) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[5.290997, 13.132723, -67.29669, -5.1313543, -49.238003, -41.690674, 29.56293, -58.750378, 33.64157, -91.2554], Poisons' Predictions:[8, 8, 8, 6, 8] |
2020-01-31 18:14:17 Epoch 59, Val iteration 0, acc 90.800 (90.800) |
2020-01-31 18:14:24 Epoch 59, Val iteration 19, acc 92.600 (91.860) |
* Prec: 91.86000175476075 |
-------- |
SENet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:14:26, Epoch 0, Iteration 7, loss 0.229 (0.762), acc 98.077 (85.000) |
2020-01-31 18:14:27, Epoch 30, Iteration 7, loss 0.004 (0.159), acc 100.000 (96.600) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[6.3075523, -5.083956, -9.03815, -1.649816, 10.854952, -9.075654, 21.2124, -10.522763, 17.094538, -13.192638], Poisons' Predictions:[8, 6, 8, 6, 6] |
2020-01-31 18:14:28 Epoch 59, Val iteration 0, acc 92.400 (92.400) |
2020-01-31 18:14:30 Epoch 59, Val iteration 19, acc 93.600 (91.820) |
* Prec: 91.8200008392334 |
-------- |
ResNet50 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:14:32, Epoch 0, Iteration 7, loss 0.268 (1.369), acc 98.077 (86.000) |
2020-01-31 18:14:33, Epoch 30, Iteration 7, loss 0.007 (0.005), acc 100.000 (99.800) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-47.616264, -1.9882373, -57.47622, -56.68726, -79.51396, -20.217894, 31.333939, -38.785774, 37.259007, -16.573393], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 18:14:34 Epoch 59, Val iteration 0, acc 92.400 (92.400) |
2020-01-31 18:14:38 Epoch 59, Val iteration 19, acc 93.600 (92.830) |
* Prec: 92.83000106811524 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:14:41, Epoch 0, Iteration 7, loss 0.731 (3.034), acc 90.385 (64.000) |
2020-01-31 18:14:41, Epoch 30, Iteration 7, loss 0.013 (0.046), acc 100.000 (99.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-23.209604, -7.5067506, -5.7689404, 8.478656, -70.36696, -26.554876, 16.08121, -25.24647, 25.239092, -25.218927], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 18:14:42 Epoch 59, Val iteration 0, acc 92.800 (92.800) |
2020-01-31 18:14:46 Epoch 59, Val iteration 19, acc 92.600 (92.760) |
* Prec: 92.76000099182129 |
-------- |
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