Datasets:
SunayBhat1
/
PureGen_Poisons

Dataset card Data Studio Files
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2020-01-31 17:13:09 Iteration 300 Training Loss: 8.770e-02 Loss in Target Net: 1.522e-02
2020-01-31 17:13:33 Iteration 350 Training Loss: 8.754e-02 Loss in Target Net: 1.095e-02
2020-01-31 17:13:56 Iteration 400 Training Loss: 8.722e-02 Loss in Target Net: 1.644e-02
2020-01-31 17:14:19 Iteration 450 Training Loss: 8.208e-02 Loss in Target Net: 1.255e-02
2020-01-31 17:14:42 Iteration 500 Training Loss: 8.254e-02 Loss in Target Net: 1.396e-02
2020-01-31 17:15:06 Iteration 550 Training Loss: 8.111e-02 Loss in Target Net: 1.338e-02
2020-01-31 17:15:29 Iteration 600 Training Loss: 8.381e-02 Loss in Target Net: 1.298e-02
2020-01-31 17:15:53 Iteration 650 Training Loss: 8.283e-02 Loss in Target Net: 1.015e-02
2020-01-31 17:16:16 Iteration 700 Training Loss: 8.165e-02 Loss in Target Net: 9.060e-03
2020-01-31 17:16:39 Iteration 750 Training Loss: 7.642e-02 Loss in Target Net: 1.168e-02
2020-01-31 17:17:02 Iteration 800 Training Loss: 8.735e-02 Loss in Target Net: 1.313e-02
2020-01-31 17:17:26 Iteration 850 Training Loss: 7.737e-02 Loss in Target Net: 1.363e-02
2020-01-31 17:17:50 Iteration 900 Training Loss: 7.749e-02 Loss in Target Net: 1.129e-02
2020-01-31 17:18:13 Iteration 950 Training Loss: 8.974e-02 Loss in Target Net: 8.650e-03
2020-01-31 17:18:37 Iteration 1000 Training Loss: 8.037e-02 Loss in Target Net: 9.855e-03
2020-01-31 17:19:00 Iteration 1050 Training Loss: 7.905e-02 Loss in Target Net: 9.531e-03
2020-01-31 17:19:25 Iteration 1100 Training Loss: 8.309e-02 Loss in Target Net: 1.039e-02
2020-01-31 17:19:49 Iteration 1150 Training Loss: 8.571e-02 Loss in Target Net: 1.101e-02
2020-01-31 17:20:12 Iteration 1200 Training Loss: 7.976e-02 Loss in Target Net: 8.280e-03
2020-01-31 17:20:35 Iteration 1250 Training Loss: 8.347e-02 Loss in Target Net: 1.047e-02
2020-01-31 17:20:59 Iteration 1300 Training Loss: 8.245e-02 Loss in Target Net: 1.150e-02
2020-01-31 17:21:23 Iteration 1350 Training Loss: 8.678e-02 Loss in Target Net: 1.136e-02
2020-01-31 17:21:47 Iteration 1400 Training Loss: 8.661e-02 Loss in Target Net: 1.093e-02
2020-01-31 17:22:11 Iteration 1450 Training Loss: 8.562e-02 Loss in Target Net: 1.215e-02
2020-01-31 17:22:36 Iteration 1500 Training Loss: 8.301e-02 Loss in Target Net: 1.611e-02
2020-01-31 17:23:00 Iteration 1550 Training Loss: 8.693e-02 Loss in Target Net: 1.347e-02
2020-01-31 17:23:25 Iteration 1600 Training Loss: 8.247e-02 Loss in Target Net: 1.844e-02
2020-01-31 17:23:49 Iteration 1650 Training Loss: 8.627e-02 Loss in Target Net: 1.865e-02
2020-01-31 17:24:13 Iteration 1700 Training Loss: 8.165e-02 Loss in Target Net: 1.481e-02
2020-01-31 17:24:38 Iteration 1750 Training Loss: 8.521e-02 Loss in Target Net: 1.618e-02
2020-01-31 17:25:03 Iteration 1800 Training Loss: 8.327e-02 Loss in Target Net: 1.830e-02
2020-01-31 17:25:27 Iteration 1850 Training Loss: 8.455e-02 Loss in Target Net: 1.968e-02
2020-01-31 17:25:51 Iteration 1900 Training Loss: 8.030e-02 Loss in Target Net: 1.108e-02
2020-01-31 17:26:16 Iteration 1950 Training Loss: 7.459e-02 Loss in Target Net: 1.032e-02
2020-01-31 17:26:40 Iteration 2000 Training Loss: 8.187e-02 Loss in Target Net: 1.511e-02
2020-01-31 17:27:05 Iteration 2050 Training Loss: 8.000e-02 Loss in Target Net: 1.690e-02
2020-01-31 17:27:29 Iteration 2100 Training Loss: 7.995e-02 Loss in Target Net: 1.056e-02
2020-01-31 17:27:53 Iteration 2150 Training Loss: 8.545e-02 Loss in Target Net: 1.590e-02
2020-01-31 17:28:17 Iteration 2200 Training Loss: 8.630e-02 Loss in Target Net: 1.455e-02
2020-01-31 17:28:41 Iteration 2250 Training Loss: 8.019e-02 Loss in Target Net: 1.250e-02
2020-01-31 17:29:06 Iteration 2300 Training Loss: 7.853e-02 Loss in Target Net: 1.223e-02
2020-01-31 17:29:31 Iteration 2350 Training Loss: 8.340e-02 Loss in Target Net: 1.325e-02
2020-01-31 17:29:56 Iteration 2400 Training Loss: 7.971e-02 Loss in Target Net: 1.513e-02
2020-01-31 17:30:21 Iteration 2450 Training Loss: 7.822e-02 Loss in Target Net: 1.908e-02
2020-01-31 17:30:45 Iteration 2500 Training Loss: 9.101e-02 Loss in Target Net: 1.322e-02
2020-01-31 17:31:09 Iteration 2550 Training Loss: 8.271e-02 Loss in Target Net: 9.709e-03
2020-01-31 17:31:34 Iteration 2600 Training Loss: 7.936e-02 Loss in Target Net: 1.430e-02
2020-01-31 17:31:58 Iteration 2650 Training Loss: 7.794e-02 Loss in Target Net: 1.618e-02
2020-01-31 17:32:22 Iteration 2700 Training Loss: 7.792e-02 Loss in Target Net: 1.355e-02
2020-01-31 17:32:46 Iteration 2750 Training Loss: 8.231e-02 Loss in Target Net: 1.308e-02
2020-01-31 17:33:10 Iteration 2800 Training Loss: 8.750e-02 Loss in Target Net: 1.595e-02
2020-01-31 17:33:32 Iteration 2850 Training Loss: 8.399e-02 Loss in Target Net: 1.371e-02
2020-01-31 17:33:54 Iteration 2900 Training Loss: 7.109e-02 Loss in Target Net: 2.015e-02
2020-01-31 17:34:19 Iteration 2950 Training Loss: 7.916e-02 Loss in Target Net: 1.437e-02
2020-01-31 17:34:43 Iteration 3000 Training Loss: 7.915e-02 Loss in Target Net: 1.912e-02
2020-01-31 17:35:08 Iteration 3050 Training Loss: 8.162e-02 Loss in Target Net: 1.784e-02
2020-01-31 17:35:31 Iteration 3100 Training Loss: 7.665e-02 Loss in Target Net: 1.565e-02
2020-01-31 17:35:55 Iteration 3150 Training Loss: 8.372e-02 Loss in Target Net: 1.675e-02
2020-01-31 17:36:19 Iteration 3200 Training Loss: 8.044e-02 Loss in Target Net: 1.335e-02
2020-01-31 17:36:44 Iteration 3250 Training Loss: 8.839e-02 Loss in Target Net: 1.247e-02
2020-01-31 17:37:08 Iteration 3300 Training Loss: 8.620e-02 Loss in Target Net: 1.716e-02
2020-01-31 17:37:32 Iteration 3350 Training Loss: 7.870e-02 Loss in Target Net: 1.205e-02
2020-01-31 17:37:57 Iteration 3400 Training Loss: 8.325e-02 Loss in Target Net: 1.654e-02
2020-01-31 17:38:21 Iteration 3450 Training Loss: 7.713e-02 Loss in Target Net: 1.100e-02
2020-01-31 17:38:45 Iteration 3500 Training Loss: 8.154e-02 Loss in Target Net: 1.310e-02
2020-01-31 17:39:08 Iteration 3550 Training Loss: 7.555e-02 Loss in Target Net: 1.538e-02
2020-01-31 17:39:30 Iteration 3600 Training Loss: 8.035e-02 Loss in Target Net: 1.960e-02
2020-01-31 17:39:52 Iteration 3650 Training Loss: 7.215e-02 Loss in Target Net: 1.863e-02
2020-01-31 17:40:13 Iteration 3700 Training Loss: 8.632e-02 Loss in Target Net: 1.223e-02
2020-01-31 17:40:35 Iteration 3750 Training Loss: 7.897e-02 Loss in Target Net: 1.849e-02
2020-01-31 17:40:57 Iteration 3800 Training Loss: 8.712e-02 Loss in Target Net: 2.285e-02
2020-01-31 17:41:19 Iteration 3850 Training Loss: 8.032e-02 Loss in Target Net: 1.873e-02
2020-01-31 17:41:40 Iteration 3900 Training Loss: 8.362e-02 Loss in Target Net: 1.071e-02
2020-01-31 17:42:02 Iteration 3950 Training Loss: 8.137e-02 Loss in Target Net: 1.247e-02
2020-01-31 17:42:24 Iteration 3999 Training Loss: 8.384e-02 Loss in Target Net: 1.455e-02
Evaluating against victims networks
DPN92
Using Adam for retraining
Files already downloaded and verified
2020-01-31 17:42:28, Epoch 0, Iteration 7, loss 1.541 (4.313), acc 86.538 (64.800)
2020-01-31 17:42:28, Epoch 30, Iteration 7, loss 0.049 (0.172), acc 98.077 (94.800)
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[6.100868, -7.2527866, -39.012737, 5.560783, -13.620274, -0.88825256, 29.660364, -48.84945, 28.311497, -87.727455], Poisons' Predictions:[8, 8, 8, 8, 6]
2020-01-31 17:42:32 Epoch 59, Val iteration 0, acc 91.000 (91.000)
2020-01-31 17:42:40 Epoch 59, Val iteration 19, acc 92.000 (91.740)
* Prec: 91.74000129699706
--------
SENet18
Using Adam for retraining
Files already downloaded and verified
2020-01-31 17:42:42, Epoch 0, Iteration 7, loss 0.738 (0.674), acc 92.308 (90.800)
2020-01-31 17:42:42, Epoch 30, Iteration 7, loss 0.344 (0.168), acc 92.308 (96.000)
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-6.305817, -14.198962, -12.157731, 9.390903, 13.919559, -5.474612, 11.1886425, -20.79822, 24.71988, -12.438627], Poisons' Predictions:[8, 8, 8, 8, 6]
2020-01-31 17:42:44 Epoch 59, Val iteration 0, acc 91.600 (91.600)
2020-01-31 17:42:46 Epoch 59, Val iteration 19, acc 92.800 (91.520)
* Prec: 91.52000122070312
--------
ResNet50
Using Adam for retraining
Files already downloaded and verified
2020-01-31 17:42:49, Epoch 0, Iteration 7, loss 0.874 (0.790), acc 98.077 (89.800)