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2020-01-31 20:56:29 Iteration 1700 Training Loss: 7.976e-02 Loss in Target Net: 1.284e-02 |
2020-01-31 20:56:52 Iteration 1750 Training Loss: 8.509e-02 Loss in Target Net: 1.377e-02 |
2020-01-31 20:57:14 Iteration 1800 Training Loss: 7.850e-02 Loss in Target Net: 1.155e-02 |
2020-01-31 20:57:36 Iteration 1850 Training Loss: 8.022e-02 Loss in Target Net: 1.066e-02 |
2020-01-31 20:58:00 Iteration 1900 Training Loss: 8.012e-02 Loss in Target Net: 9.029e-03 |
2020-01-31 20:58:22 Iteration 1950 Training Loss: 7.500e-02 Loss in Target Net: 1.296e-02 |
2020-01-31 20:58:45 Iteration 2000 Training Loss: 8.212e-02 Loss in Target Net: 7.317e-03 |
2020-01-31 20:59:08 Iteration 2050 Training Loss: 7.638e-02 Loss in Target Net: 7.438e-03 |
2020-01-31 20:59:29 Iteration 2100 Training Loss: 8.252e-02 Loss in Target Net: 1.028e-02 |
2020-01-31 20:59:52 Iteration 2150 Training Loss: 7.941e-02 Loss in Target Net: 1.264e-02 |
2020-01-31 21:00:14 Iteration 2200 Training Loss: 8.375e-02 Loss in Target Net: 1.269e-02 |
2020-01-31 21:00:35 Iteration 2250 Training Loss: 7.291e-02 Loss in Target Net: 1.318e-02 |
2020-01-31 21:00:57 Iteration 2300 Training Loss: 7.873e-02 Loss in Target Net: 1.132e-02 |
2020-01-31 21:01:19 Iteration 2350 Training Loss: 7.635e-02 Loss in Target Net: 7.691e-03 |
2020-01-31 21:01:40 Iteration 2400 Training Loss: 8.118e-02 Loss in Target Net: 9.754e-03 |
2020-01-31 21:02:01 Iteration 2450 Training Loss: 7.869e-02 Loss in Target Net: 1.245e-02 |
2020-01-31 21:02:24 Iteration 2500 Training Loss: 8.509e-02 Loss in Target Net: 8.978e-03 |
2020-01-31 21:02:47 Iteration 2550 Training Loss: 8.242e-02 Loss in Target Net: 9.147e-03 |
2020-01-31 21:03:10 Iteration 2600 Training Loss: 7.571e-02 Loss in Target Net: 6.735e-03 |
2020-01-31 21:03:32 Iteration 2650 Training Loss: 7.813e-02 Loss in Target Net: 7.642e-03 |
2020-01-31 21:03:55 Iteration 2700 Training Loss: 8.088e-02 Loss in Target Net: 9.130e-03 |
2020-01-31 21:04:18 Iteration 2750 Training Loss: 7.754e-02 Loss in Target Net: 9.455e-03 |
2020-01-31 21:04:41 Iteration 2800 Training Loss: 7.905e-02 Loss in Target Net: 1.230e-02 |
2020-01-31 21:05:04 Iteration 2850 Training Loss: 8.579e-02 Loss in Target Net: 1.367e-02 |
2020-01-31 21:05:26 Iteration 2900 Training Loss: 8.276e-02 Loss in Target Net: 9.420e-03 |
2020-01-31 21:05:49 Iteration 2950 Training Loss: 7.336e-02 Loss in Target Net: 1.040e-02 |
2020-01-31 21:06:12 Iteration 3000 Training Loss: 8.562e-02 Loss in Target Net: 1.146e-02 |
2020-01-31 21:06:35 Iteration 3050 Training Loss: 8.196e-02 Loss in Target Net: 8.336e-03 |
2020-01-31 21:06:59 Iteration 3100 Training Loss: 7.907e-02 Loss in Target Net: 8.597e-03 |
2020-01-31 21:07:22 Iteration 3150 Training Loss: 7.545e-02 Loss in Target Net: 9.345e-03 |
2020-01-31 21:07:45 Iteration 3200 Training Loss: 7.969e-02 Loss in Target Net: 9.595e-03 |
2020-01-31 21:08:08 Iteration 3250 Training Loss: 8.485e-02 Loss in Target Net: 1.410e-02 |
2020-01-31 21:08:30 Iteration 3300 Training Loss: 7.745e-02 Loss in Target Net: 9.273e-03 |
2020-01-31 21:08:52 Iteration 3350 Training Loss: 8.410e-02 Loss in Target Net: 8.166e-03 |
2020-01-31 21:09:14 Iteration 3400 Training Loss: 8.351e-02 Loss in Target Net: 1.375e-02 |
2020-01-31 21:09:36 Iteration 3450 Training Loss: 7.900e-02 Loss in Target Net: 4.665e-03 |
2020-01-31 21:09:57 Iteration 3500 Training Loss: 8.047e-02 Loss in Target Net: 7.474e-03 |
2020-01-31 21:10:20 Iteration 3550 Training Loss: 7.596e-02 Loss in Target Net: 6.670e-03 |
2020-01-31 21:10:43 Iteration 3600 Training Loss: 8.363e-02 Loss in Target Net: 8.350e-03 |
2020-01-31 21:11:07 Iteration 3650 Training Loss: 8.037e-02 Loss in Target Net: 1.087e-02 |
2020-01-31 21:11:29 Iteration 3700 Training Loss: 7.873e-02 Loss in Target Net: 7.501e-03 |
2020-01-31 21:11:50 Iteration 3750 Training Loss: 8.049e-02 Loss in Target Net: 9.828e-03 |
2020-01-31 21:12:10 Iteration 3800 Training Loss: 8.111e-02 Loss in Target Net: 9.293e-03 |
2020-01-31 21:12:33 Iteration 3850 Training Loss: 7.853e-02 Loss in Target Net: 1.044e-02 |
2020-01-31 21:12:54 Iteration 3900 Training Loss: 7.825e-02 Loss in Target Net: 8.712e-03 |
2020-01-31 21:13:15 Iteration 3950 Training Loss: 8.202e-02 Loss in Target Net: 9.335e-03 |
2020-01-31 21:13:38 Iteration 3999 Training Loss: 7.875e-02 Loss in Target Net: 1.326e-02 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 21:13:42, Epoch 0, Iteration 7, loss 2.257 (4.357), acc 88.462 (65.200) |
2020-01-31 21:13:43, Epoch 30, Iteration 7, loss 0.235 (0.079), acc 98.077 (98.600) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[12.963672, -18.604692, -43.89042, 2.4888191, -34.04108, -1.869318, 23.102808, -58.285797, 27.792248, -123.56953], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 21:13:47 Epoch 59, Val iteration 0, acc 89.800 (89.800) |
2020-01-31 21:13:54 Epoch 59, Val iteration 19, acc 92.200 (91.940) |
* Prec: 91.94000205993652 |
-------- |
SENet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 21:13:56, Epoch 0, Iteration 7, loss 0.526 (0.661), acc 92.308 (87.800) |
2020-01-31 21:13:56, Epoch 30, Iteration 7, loss 0.237 (0.177), acc 96.154 (96.200) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[8.25033, -9.332134, -5.262137, -5.628705, 11.592764, -10.571176, 26.307648, -20.815939, 19.863237, -17.798716], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 21:13:57 Epoch 59, Val iteration 0, acc 93.200 (93.200) |
2020-01-31 21:13:59 Epoch 59, Val iteration 19, acc 92.800 (92.090) |
* Prec: 92.09000091552734 |
-------- |
ResNet50 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 21:14:01, Epoch 0, Iteration 7, loss 0.532 (0.701), acc 98.077 (90.200) |
2020-01-31 21:14:02, Epoch 30, Iteration 7, loss 0.000 (0.000), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-54.972862, -0.69950145, -59.022175, -41.259434, -51.2604, -34.680298, 35.44034, -63.65976, 34.258366, -43.447643], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 21:14:03 Epoch 59, Val iteration 0, acc 92.600 (92.600) |
2020-01-31 21:14:07 Epoch 59, Val iteration 19, acc 94.400 (93.610) |
* Prec: 93.61000022888183 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 21:14:09, Epoch 0, Iteration 7, loss 0.711 (1.988), acc 82.692 (70.800) |
2020-01-31 21:14:09, Epoch 30, Iteration 7, loss 0.216 (0.118), acc 94.231 (97.600) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-20.420418, 8.5195055, 1.3967488, 10.9938135, -67.48748, -30.393913, 24.86405, -8.888146, 22.619719, -21.276615], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 21:14:11 Epoch 59, Val iteration 0, acc 92.400 (92.400) |
2020-01-31 21:14:15 Epoch 59, Val iteration 19, acc 93.600 (93.210) |
* Prec: 93.21000099182129 |
-------- |
GoogLeNet |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 21:14:17, Epoch 0, Iteration 7, loss 0.467 (0.428), acc 94.231 (91.400) |
2020-01-31 21:14:17, Epoch 30, Iteration 7, loss 0.043 (0.032), acc 98.077 (99.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-13.782405, -1.3362986, -3.8242083, -1.1457531, -16.575518, -5.7651653, 6.2740226, -5.956909, 12.776533, -21.548203], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 21:14:20 Epoch 59, Val iteration 0, acc 91.200 (91.200) |
2020-01-31 21:14:24 Epoch 59, Val iteration 19, acc 92.200 (91.990) |
* Prec: 91.99000205993653 |
-------- |
MobileNetV2 |
Using Adam for retraining |
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