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2020-02-04 22:11:38 Iteration 1900 Training Loss: 9.648e-02 Loss in Target Net: 1.985e-02 |
2020-02-04 22:13:00 Iteration 1950 Training Loss: 1.027e-01 Loss in Target Net: 1.234e-02 |
2020-02-04 22:14:20 Iteration 2000 Training Loss: 9.651e-02 Loss in Target Net: 1.550e-02 |
2020-02-04 22:15:44 Iteration 2050 Training Loss: 1.046e-01 Loss in Target Net: 1.312e-02 |
2020-02-04 22:17:09 Iteration 2100 Training Loss: 9.908e-02 Loss in Target Net: 1.521e-02 |
2020-02-04 22:18:36 Iteration 2150 Training Loss: 1.017e-01 Loss in Target Net: 1.407e-02 |
2020-02-04 22:20:05 Iteration 2200 Training Loss: 9.533e-02 Loss in Target Net: 1.548e-02 |
2020-02-04 22:21:33 Iteration 2250 Training Loss: 1.062e-01 Loss in Target Net: 1.327e-02 |
2020-02-04 22:23:02 Iteration 2300 Training Loss: 9.624e-02 Loss in Target Net: 1.693e-02 |
2020-02-04 22:24:30 Iteration 2350 Training Loss: 9.679e-02 Loss in Target Net: 1.915e-02 |
2020-02-04 22:25:57 Iteration 2400 Training Loss: 1.030e-01 Loss in Target Net: 2.128e-02 |
2020-02-04 22:27:23 Iteration 2450 Training Loss: 1.078e-01 Loss in Target Net: 1.497e-02 |
2020-02-04 22:28:49 Iteration 2500 Training Loss: 1.028e-01 Loss in Target Net: 2.905e-02 |
2020-02-04 22:30:14 Iteration 2550 Training Loss: 1.064e-01 Loss in Target Net: 1.949e-02 |
2020-02-04 22:31:38 Iteration 2600 Training Loss: 1.044e-01 Loss in Target Net: 1.563e-02 |
2020-02-04 22:33:03 Iteration 2650 Training Loss: 9.525e-02 Loss in Target Net: 1.159e-02 |
2020-02-04 22:34:30 Iteration 2700 Training Loss: 1.041e-01 Loss in Target Net: 1.650e-02 |
2020-02-04 22:35:57 Iteration 2750 Training Loss: 9.965e-02 Loss in Target Net: 1.166e-02 |
2020-02-04 22:37:23 Iteration 2800 Training Loss: 1.045e-01 Loss in Target Net: 1.664e-02 |
2020-02-04 22:38:50 Iteration 2850 Training Loss: 1.054e-01 Loss in Target Net: 1.770e-02 |
2020-02-04 22:40:17 Iteration 2900 Training Loss: 1.012e-01 Loss in Target Net: 1.365e-02 |
2020-02-04 22:41:41 Iteration 2950 Training Loss: 1.012e-01 Loss in Target Net: 1.355e-02 |
2020-02-04 22:43:06 Iteration 3000 Training Loss: 9.872e-02 Loss in Target Net: 1.209e-02 |
2020-02-04 22:44:30 Iteration 3050 Training Loss: 1.037e-01 Loss in Target Net: 1.059e-02 |
2020-02-04 22:45:52 Iteration 3100 Training Loss: 1.017e-01 Loss in Target Net: 1.236e-02 |
2020-02-04 22:47:11 Iteration 3150 Training Loss: 1.033e-01 Loss in Target Net: 1.230e-02 |
2020-02-04 22:48:34 Iteration 3200 Training Loss: 1.066e-01 Loss in Target Net: 1.954e-02 |
2020-02-04 22:49:59 Iteration 3250 Training Loss: 9.205e-02 Loss in Target Net: 1.207e-02 |
2020-02-04 22:51:25 Iteration 3300 Training Loss: 1.019e-01 Loss in Target Net: 1.120e-02 |
2020-02-04 22:52:50 Iteration 3350 Training Loss: 9.631e-02 Loss in Target Net: 1.367e-02 |
2020-02-04 22:54:15 Iteration 3400 Training Loss: 9.990e-02 Loss in Target Net: 1.302e-02 |
2020-02-04 22:55:43 Iteration 3450 Training Loss: 1.075e-01 Loss in Target Net: 1.246e-02 |
2020-02-04 22:57:11 Iteration 3500 Training Loss: 9.682e-02 Loss in Target Net: 1.921e-02 |
2020-02-04 22:58:39 Iteration 3550 Training Loss: 1.000e-01 Loss in Target Net: 1.735e-02 |
2020-02-04 23:00:05 Iteration 3600 Training Loss: 9.398e-02 Loss in Target Net: 1.459e-02 |
2020-02-04 23:01:32 Iteration 3650 Training Loss: 9.998e-02 Loss in Target Net: 1.627e-02 |
2020-02-04 23:02:57 Iteration 3700 Training Loss: 9.638e-02 Loss in Target Net: 9.804e-03 |
2020-02-04 23:04:23 Iteration 3750 Training Loss: 9.822e-02 Loss in Target Net: 2.146e-02 |
2020-02-04 23:05:47 Iteration 3800 Training Loss: 9.787e-02 Loss in Target Net: 8.463e-03 |
2020-02-04 23:07:11 Iteration 3850 Training Loss: 1.007e-01 Loss in Target Net: 1.531e-02 |
2020-02-04 23:08:34 Iteration 3900 Training Loss: 9.767e-02 Loss in Target Net: 2.074e-02 |
2020-02-04 23:09:58 Iteration 3950 Training Loss: 1.024e-01 Loss in Target Net: 1.155e-02 |
2020-02-04 23:11:20 Iteration 3999 Training Loss: 1.047e-01 Loss in Target Net: 1.700e-02 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:11:38, Epoch 0, Iteration 7, loss 1.358 (3.811), acc 90.385 (71.800) |
2020-02-04 23:11:39, Epoch 30, Iteration 7, loss 0.124 (0.267), acc 98.077 (94.600) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[15.042622, -16.456814, -45.56871, -0.053410903, -31.247957, 2.7136447, 21.05273, -90.75293, 18.614138, -60.540775], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 23:12:10 Epoch 59, Val iteration 0, acc 92.000 (92.000) |
2020-02-04 23:13:00 Epoch 59, Val iteration 19, acc 92.400 (92.640) |
* Prec: 92.64000205993652 |
-------- |
SENet18 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:13:05, Epoch 0, Iteration 7, loss 0.601 (0.628), acc 90.385 (89.000) |
2020-02-04 23:13:05, Epoch 30, Iteration 7, loss 0.113 (0.179), acc 96.154 (97.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[4.5084085, -4.887779, -2.5853052, 2.6596375, 5.457788, -11.346654, 14.4179735, -9.655211, 20.262566, -20.758871], Poisons' Predictions:[8, 8, 3, 8, 8] |
2020-02-04 23:13:09 Epoch 59, Val iteration 0, acc 92.000 (92.000) |
2020-02-04 23:13:16 Epoch 59, Val iteration 19, acc 93.000 (91.480) |
* Prec: 91.48000106811523 |
-------- |
ResNet50 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:13:23, Epoch 0, Iteration 7, loss 0.001 (1.283), acc 100.000 (85.000) |
2020-02-04 23:13:24, Epoch 30, Iteration 7, loss 0.000 (0.000), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-31.406258, -53.738583, -43.638123, -58.22298, -58.154194, -18.487759, 37.80173, -35.844917, 42.04418, -6.8334975], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 23:13:31 Epoch 59, Val iteration 0, acc 93.200 (93.200) |
2020-02-04 23:13:52 Epoch 59, Val iteration 19, acc 94.600 (93.840) |
* Prec: 93.84000244140626 |
-------- |
ResNeXt29_2x64d |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:13:58, Epoch 0, Iteration 7, loss 0.135 (2.659), acc 94.231 (72.600) |
2020-02-04 23:13:59, Epoch 30, Iteration 7, loss 0.008 (0.021), acc 100.000 (99.000) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-21.955566, -0.5580027, -6.2683625, 6.711982, -49.779907, -20.565607, 12.997987, -26.363707, 6.5817246, -30.70418], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 23:14:06 Epoch 59, Val iteration 0, acc 92.600 (92.600) |
2020-02-04 23:14:27 Epoch 59, Val iteration 19, acc 94.000 (92.860) |
* Prec: 92.86000175476075 |
-------- |
GoogLeNet |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:14:36, Epoch 0, Iteration 7, loss 0.428 (0.490), acc 90.385 (88.400) |
2020-02-04 23:14:36, Epoch 30, Iteration 7, loss 0.133 (0.052), acc 94.231 (98.200) |
Target Label: 6, Poison label: 8, Prediction:3, Target's Score:[-10.533151, -13.399958, 0.7167899, 2.0528145, -5.9442234, -0.8374464, 1.7296811, -8.372919, 0.33048916, -19.074652], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 23:14:52 Epoch 59, Val iteration 0, acc 92.200 (92.200) |
2020-02-04 23:15:37 Epoch 59, Val iteration 19, acc 92.000 (92.110) |
* Prec: 92.1100009918213 |
-------- |
MobileNetV2 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 23:15:42, Epoch 0, Iteration 7, loss 1.642 (2.979), acc 80.769 (67.600) |
2020-02-04 23:15:42, Epoch 30, Iteration 7, loss 0.432 (0.494), acc 90.385 (91.400) |
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[6.7088847, -20.10209, -0.31778315, 18.303165, -49.499878, 3.1892703, 24.473024, -23.33811, 17.475224, -0.38239127], Poisons' Predictions:[8, 6, 8, 6, 6] |
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