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2020-01-31 17:52:40 Iteration 1700 Training Loss: 1.025e-01 Loss in Target Net: 1.167e-02 |
2020-01-31 17:53:01 Iteration 1750 Training Loss: 9.055e-02 Loss in Target Net: 1.726e-02 |
2020-01-31 17:53:23 Iteration 1800 Training Loss: 9.711e-02 Loss in Target Net: 8.004e-03 |
2020-01-31 17:53:45 Iteration 1850 Training Loss: 9.263e-02 Loss in Target Net: 2.465e-02 |
2020-01-31 17:54:07 Iteration 1900 Training Loss: 9.728e-02 Loss in Target Net: 2.226e-02 |
2020-01-31 17:54:28 Iteration 1950 Training Loss: 8.964e-02 Loss in Target Net: 1.254e-02 |
2020-01-31 17:54:50 Iteration 2000 Training Loss: 9.094e-02 Loss in Target Net: 3.086e-02 |
2020-01-31 17:55:11 Iteration 2050 Training Loss: 8.908e-02 Loss in Target Net: 2.628e-02 |
2020-01-31 17:55:33 Iteration 2100 Training Loss: 9.545e-02 Loss in Target Net: 1.727e-02 |
2020-01-31 17:55:55 Iteration 2150 Training Loss: 1.020e-01 Loss in Target Net: 1.941e-02 |
2020-01-31 17:56:17 Iteration 2200 Training Loss: 9.390e-02 Loss in Target Net: 1.881e-02 |
2020-01-31 17:56:39 Iteration 2250 Training Loss: 9.819e-02 Loss in Target Net: 2.322e-02 |
2020-01-31 17:57:01 Iteration 2300 Training Loss: 9.232e-02 Loss in Target Net: 1.731e-02 |
2020-01-31 17:57:23 Iteration 2350 Training Loss: 8.974e-02 Loss in Target Net: 1.505e-02 |
2020-01-31 17:57:44 Iteration 2400 Training Loss: 9.416e-02 Loss in Target Net: 1.101e-02 |
2020-01-31 17:58:06 Iteration 2450 Training Loss: 9.272e-02 Loss in Target Net: 1.149e-02 |
2020-01-31 17:58:28 Iteration 2500 Training Loss: 9.731e-02 Loss in Target Net: 3.010e-02 |
2020-01-31 17:58:50 Iteration 2550 Training Loss: 9.530e-02 Loss in Target Net: 1.106e-02 |
2020-01-31 17:59:12 Iteration 2600 Training Loss: 9.133e-02 Loss in Target Net: 1.396e-02 |
2020-01-31 17:59:34 Iteration 2650 Training Loss: 9.173e-02 Loss in Target Net: 1.107e-02 |
2020-01-31 17:59:55 Iteration 2700 Training Loss: 9.993e-02 Loss in Target Net: 1.245e-02 |
2020-01-31 18:00:17 Iteration 2750 Training Loss: 9.032e-02 Loss in Target Net: 1.601e-02 |
2020-01-31 18:00:39 Iteration 2800 Training Loss: 9.428e-02 Loss in Target Net: 2.637e-02 |
2020-01-31 18:01:00 Iteration 2850 Training Loss: 1.025e-01 Loss in Target Net: 2.991e-02 |
2020-01-31 18:01:22 Iteration 2900 Training Loss: 9.017e-02 Loss in Target Net: 1.586e-02 |
2020-01-31 18:01:44 Iteration 2950 Training Loss: 9.230e-02 Loss in Target Net: 1.585e-02 |
2020-01-31 18:02:06 Iteration 3000 Training Loss: 8.772e-02 Loss in Target Net: 2.251e-02 |
2020-01-31 18:02:27 Iteration 3050 Training Loss: 9.347e-02 Loss in Target Net: 2.305e-02 |
2020-01-31 18:02:49 Iteration 3100 Training Loss: 9.583e-02 Loss in Target Net: 1.355e-02 |
2020-01-31 18:03:10 Iteration 3150 Training Loss: 8.452e-02 Loss in Target Net: 1.194e-02 |
2020-01-31 18:03:32 Iteration 3200 Training Loss: 9.930e-02 Loss in Target Net: 9.603e-03 |
2020-01-31 18:03:53 Iteration 3250 Training Loss: 1.064e-01 Loss in Target Net: 9.982e-03 |
2020-01-31 18:04:15 Iteration 3300 Training Loss: 9.469e-02 Loss in Target Net: 1.171e-02 |
2020-01-31 18:04:36 Iteration 3350 Training Loss: 9.424e-02 Loss in Target Net: 1.478e-02 |
2020-01-31 18:04:58 Iteration 3400 Training Loss: 9.246e-02 Loss in Target Net: 1.220e-02 |
2020-01-31 18:05:19 Iteration 3450 Training Loss: 9.596e-02 Loss in Target Net: 1.889e-02 |
2020-01-31 18:05:41 Iteration 3500 Training Loss: 8.630e-02 Loss in Target Net: 2.341e-02 |
2020-01-31 18:06:03 Iteration 3550 Training Loss: 8.578e-02 Loss in Target Net: 1.901e-02 |
2020-01-31 18:06:25 Iteration 3600 Training Loss: 1.008e-01 Loss in Target Net: 2.139e-02 |
2020-01-31 18:06:47 Iteration 3650 Training Loss: 9.728e-02 Loss in Target Net: 2.058e-02 |
2020-01-31 18:07:08 Iteration 3700 Training Loss: 9.160e-02 Loss in Target Net: 2.071e-02 |
2020-01-31 18:07:30 Iteration 3750 Training Loss: 9.466e-02 Loss in Target Net: 1.504e-02 |
2020-01-31 18:07:51 Iteration 3800 Training Loss: 9.346e-02 Loss in Target Net: 2.511e-02 |
2020-01-31 18:08:14 Iteration 3850 Training Loss: 1.041e-01 Loss in Target Net: 2.243e-02 |
2020-01-31 18:08:35 Iteration 3900 Training Loss: 9.016e-02 Loss in Target Net: 1.928e-02 |
2020-01-31 18:08:57 Iteration 3950 Training Loss: 9.300e-02 Loss in Target Net: 1.967e-02 |
2020-01-31 18:09:18 Iteration 3999 Training Loss: 8.935e-02 Loss in Target Net: 1.138e-02 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:09:23, Epoch 0, Iteration 7, loss 0.783 (2.942), acc 92.308 (73.200) |
2020-01-31 18:09:23, Epoch 30, Iteration 7, loss 0.163 (0.076), acc 96.154 (98.400) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-10.6655245, -49.20906, -31.942823, 10.600345, -34.362576, 2.0330677, 10.22486, -89.79911, 17.427053, -86.40514], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 18:09:27 Epoch 59, Val iteration 0, acc 91.800 (91.800) |
2020-01-31 18:09:34 Epoch 59, Val iteration 19, acc 93.000 (92.210) |
* Prec: 92.21000175476074 |
-------- |
SENet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:09:37, Epoch 0, Iteration 7, loss 1.451 (0.851), acc 86.538 (88.400) |
2020-01-31 18:09:37, Epoch 30, Iteration 7, loss 0.017 (0.281), acc 100.000 (95.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-6.7919745, -12.9570875, -1.9478996, 7.37636, 4.78888, 0.5970772, 12.86375, -14.889353, 14.360962, -12.76411], Poisons' Predictions:[8, 8, 3, 3, 8] |
2020-01-31 18:09:38 Epoch 59, Val iteration 0, acc 92.000 (92.000) |
2020-01-31 18:09:40 Epoch 59, Val iteration 19, acc 92.200 (91.390) |
* Prec: 91.3900016784668 |
-------- |
ResNet50 |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:09:43, Epoch 0, Iteration 7, loss 0.123 (2.038), acc 96.154 (85.400) |
2020-01-31 18:09:43, 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:[-116.35385, -59.879684, -70.136826, -60.007935, -40.00468, -46.54527, 6.0893087, -64.96648, 5.0990167, -50.94051], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 18:09:44 Epoch 59, Val iteration 0, acc 92.400 (92.400) |
2020-01-31 18:09:49 Epoch 59, Val iteration 19, acc 94.200 (92.870) |
* Prec: 92.87000198364258 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:09:51, Epoch 0, Iteration 7, loss 0.190 (1.809), acc 90.385 (72.400) |
2020-01-31 18:09:52, Epoch 30, Iteration 7, loss 0.077 (0.099), acc 96.154 (97.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-26.521938, -18.005566, -7.9468555, 13.420517, -23.967266, -12.203451, 13.204728, -16.200743, 17.70629, -25.855728], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 18:09:53 Epoch 59, Val iteration 0, acc 92.600 (92.600) |
2020-01-31 18:09:57 Epoch 59, Val iteration 19, acc 93.800 (93.080) |
* Prec: 93.08000221252442 |
-------- |
GoogLeNet |
Using Adam for retraining |
Files already downloaded and verified |
2020-01-31 18:10:00, Epoch 0, Iteration 7, loss 0.956 (0.474), acc 80.769 (89.200) |
2020-01-31 18:10:01, Epoch 30, Iteration 7, loss 0.019 (0.036), acc 98.077 (98.800) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-23.914017, -7.9687805, -0.8479713, 4.7993484, -12.5139885, 1.691057, 3.055676, -16.133146, 5.820558, -19.880638], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-01-31 18:10:03 Epoch 59, Val iteration 0, acc 91.400 (91.400) |
2020-01-31 18:10:08 Epoch 59, Val iteration 19, acc 90.800 (91.720) |
* Prec: 91.72000083923339 |
-------- |
MobileNetV2 |
Using Adam for retraining |
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