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2020-01-31 19:36:35 Iteration 3500 Training Loss: 9.098e-02 Loss in Target Net: 2.417e-02
2020-01-31 19:36:56 Iteration 3550 Training Loss: 9.157e-02 Loss in Target Net: 2.267e-02
2020-01-31 19:37:17 Iteration 3600 Training Loss: 9.599e-02 Loss in Target Net: 2.646e-02
2020-01-31 19:37:38 Iteration 3650 Training Loss: 1.005e-01 Loss in Target Net: 2.453e-02
2020-01-31 19:37:59 Iteration 3700 Training Loss: 9.486e-02 Loss in Target Net: 2.290e-02
2020-01-31 19:38:20 Iteration 3750 Training Loss: 9.332e-02 Loss in Target Net: 3.233e-02
2020-01-31 19:38:41 Iteration 3800 Training Loss: 9.080e-02 Loss in Target Net: 3.138e-02
2020-01-31 19:39:01 Iteration 3850 Training Loss: 9.602e-02 Loss in Target Net: 2.827e-02
2020-01-31 19:39:22 Iteration 3900 Training Loss: 9.372e-02 Loss in Target Net: 3.206e-02
2020-01-31 19:39:43 Iteration 3950 Training Loss: 9.579e-02 Loss in Target Net: 3.601e-02
2020-01-31 19:40:04 Iteration 3999 Training Loss: 9.064e-02 Loss in Target Net: 2.270e-02
Evaluating against victims networks
DPN92
Using Adam for retraining
Files already downloaded and verified
2020-01-31 19:40:08, Epoch 0, Iteration 7, loss 1.244 (3.524), acc 90.385 (69.800)
2020-01-31 19:40:08, Epoch 30, Iteration 7, loss 0.099 (0.159), acc 98.077 (98.200)
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[12.436894, 7.2287965, -42.4501, 10.775398, -31.159285, 1.9764314, 15.962645, -53.38623, 37.291405, -51.042175], Poisons' Predictions:[8, 8, 8, 6, 8]
2020-01-31 19:40:12 Epoch 59, Val iteration 0, acc 91.200 (91.200)
2020-01-31 19:40:19 Epoch 59, Val iteration 19, acc 92.400 (91.770)
* Prec: 91.7700008392334
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SENet18
Using Adam for retraining
Files already downloaded and verified
2020-01-31 19:40:21, Epoch 0, Iteration 7, loss 0.917 (0.909), acc 94.231 (89.000)
2020-01-31 19:40:22, Epoch 30, Iteration 7, loss 0.529 (0.284), acc 92.308 (95.400)
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-6.879315, -11.000932, -13.0667305, -2.3164668, -0.14649263, -2.9846263, 13.326807, -19.058725, 7.428196, -11.635865], Poisons' Predictions:[8, 8, 5, 6, 6]
2020-01-31 19:40:22 Epoch 59, Val iteration 0, acc 92.000 (92.000)
2020-01-31 19:40:24 Epoch 59, Val iteration 19, acc 92.200 (91.330)
* Prec: 91.33000221252442
--------
ResNet50
Using Adam for retraining
Files already downloaded and verified
2020-01-31 19:40:27, Epoch 0, Iteration 7, loss 0.028 (1.222), acc 100.000 (86.200)
2020-01-31 19:40:27, 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:[-44.30065, -55.10957, -21.815966, -24.0662, -63.222546, -47.20474, 34.523823, -70.846436, 49.19145, -92.44491], Poisons' Predictions:[8, 8, 8, 8, 8]
2020-01-31 19:40:28 Epoch 59, Val iteration 0, acc 92.200 (92.200)
2020-01-31 19:40:32 Epoch 59, Val iteration 19, acc 93.600 (92.610)
* Prec: 92.61000175476075
--------
ResNeXt29_2x64d
Using Adam for retraining
Files already downloaded and verified
2020-01-31 19:40:34, Epoch 0, Iteration 7, loss 0.509 (1.946), acc 84.615 (73.600)
2020-01-31 19:40:35, Epoch 30, Iteration 7, loss 0.041 (0.043), acc 98.077 (98.600)
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-29.151667, -5.29909, -3.6546903, 12.380903, -34.411846, -23.830236, 19.257002, -25.079414, 16.494724, -10.7349615], Poisons' Predictions:[8, 8, 8, 8, 8]
2020-01-31 19:40:36 Epoch 59, Val iteration 0, acc 91.600 (91.600)
2020-01-31 19:40:40 Epoch 59, Val iteration 19, acc 93.200 (92.030)
* Prec: 92.03000106811524
--------
GoogLeNet
Using Adam for retraining
Files already downloaded and verified
2020-01-31 19:40:43, Epoch 0, Iteration 7, loss 0.118 (0.534), acc 96.154 (88.200)
2020-01-31 19:40:43, Epoch 30, Iteration 7, loss 0.067 (0.049), acc 96.154 (98.200)
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-13.264638, -16.470797, -1.4893844, -3.573565, -8.757932, 3.7852368, -2.8963928, -18.292562, 4.3426304, -12.228493], Poisons' Predictions:[8, 8, 8, 8, 8]
2020-01-31 19:40:45 Epoch 59, Val iteration 0, acc 91.600 (91.600)
2020-01-31 19:40:50 Epoch 59, Val iteration 19, acc 92.800 (92.120)
* Prec: 92.12000160217285
--------
MobileNetV2
Using Adam for retraining
Files already downloaded and verified
2020-01-31 19:40:52, Epoch 0, Iteration 7, loss 1.849 (4.456), acc 73.077 (56.400)
2020-01-31 19:40:52, Epoch 30, Iteration 7, loss 0.274 (0.263), acc 92.308 (94.600)
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[4.668431, -46.193413, 13.002288, 19.445452, -11.586762, 5.6602826, 28.92502, -14.768405, 26.344982, -14.549994], Poisons' Predictions:[8, 8, 8, 6, 8]
2020-01-31 19:40:53 Epoch 59, Val iteration 0, acc 88.200 (88.200)
2020-01-31 19:40:55 Epoch 59, Val iteration 19, acc 88.800 (87.500)
* Prec: 87.50000190734863
--------
ResNet18
Using Adam for retraining
Files already downloaded and verified
2020-01-31 19:40:57, Epoch 0, Iteration 7, loss 0.995 (0.873), acc 94.231 (86.400)
2020-01-31 19:40:57, Epoch 30, Iteration 7, loss 0.001 (0.029), acc 100.000 (99.600)
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-30.651646, -7.272678, -14.273579, 1.8450384, -48.222115, -9.021306, 4.529991, -26.526978, 5.9396534, -29.66919], Poisons' Predictions:[8, 8, 8, 6, 8]
2020-01-31 19:40:57 Epoch 59, Val iteration 0, acc 93.200 (93.200)
2020-01-31 19:40:59 Epoch 59, Val iteration 19, acc 93.400 (92.460)
* Prec: 92.46000137329102
--------
DenseNet121
Using Adam for retraining
Files already downloaded and verified
2020-01-31 19:41:02, Epoch 0, Iteration 7, loss 0.360 (0.486), acc 94.231 (90.200)
2020-01-31 19:41:02, Epoch 30, Iteration 7, loss 0.002 (0.004), acc 100.000 (100.000)
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-6.7020707, -28.563553, -12.235293, -6.382827, -13.825761, -12.138611, 4.001978, -20.202276, 4.1341777, -25.34355], Poisons' Predictions:[8, 8, 8, 8, 8]
2020-01-31 19:41:04 Epoch 59, Val iteration 0, acc 93.800 (93.800)
2020-01-31 19:41:09 Epoch 59, Val iteration 19, acc 93.200 (93.070)
* Prec: 93.0700023651123
--------
------SUMMARY------
TIME ELAPSED (mins): 28
TARGET INDEX: 19
DPN92 1
SENet18 0
ResNet50 1
ResNeXt29_2x64d 0
GoogLeNet 1