Datasets:
SunayBhat1
/
PureGen_Poisons

Dataset card Data Studio Files
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2020-01-31 18:47:29 Iteration 100 Training Loss: 1.160e-01 Loss in Target Net: 6.247e-03
2020-01-31 18:47:51 Iteration 150 Training Loss: 1.048e-01 Loss in Target Net: 6.401e-03
2020-01-31 18:48:13 Iteration 200 Training Loss: 1.013e-01 Loss in Target Net: 5.977e-03
2020-01-31 18:48:36 Iteration 250 Training Loss: 1.030e-01 Loss in Target Net: 4.821e-03
2020-01-31 18:48:58 Iteration 300 Training Loss: 9.297e-02 Loss in Target Net: 2.832e-03
2020-01-31 18:49:21 Iteration 350 Training Loss: 1.012e-01 Loss in Target Net: 6.602e-03
2020-01-31 18:49:42 Iteration 400 Training Loss: 9.858e-02 Loss in Target Net: 7.304e-03
2020-01-31 18:50:06 Iteration 450 Training Loss: 9.308e-02 Loss in Target Net: 9.763e-03
2020-01-31 18:50:29 Iteration 500 Training Loss: 9.777e-02 Loss in Target Net: 7.165e-03
2020-01-31 18:50:52 Iteration 550 Training Loss: 8.640e-02 Loss in Target Net: 6.408e-03
2020-01-31 18:51:16 Iteration 600 Training Loss: 8.670e-02 Loss in Target Net: 7.656e-03
2020-01-31 18:51:39 Iteration 650 Training Loss: 8.940e-02 Loss in Target Net: 6.684e-03
2020-01-31 18:52:03 Iteration 700 Training Loss: 9.479e-02 Loss in Target Net: 9.932e-03
2020-01-31 18:52:25 Iteration 750 Training Loss: 9.580e-02 Loss in Target Net: 5.912e-03
2020-01-31 18:52:47 Iteration 800 Training Loss: 9.556e-02 Loss in Target Net: 8.766e-03
2020-01-31 18:53:09 Iteration 850 Training Loss: 8.660e-02 Loss in Target Net: 7.024e-03
2020-01-31 18:53:30 Iteration 900 Training Loss: 8.821e-02 Loss in Target Net: 4.964e-03
2020-01-31 18:53:51 Iteration 950 Training Loss: 8.881e-02 Loss in Target Net: 6.337e-03
2020-01-31 18:54:12 Iteration 1000 Training Loss: 9.159e-02 Loss in Target Net: 4.230e-03
2020-01-31 18:54:35 Iteration 1050 Training Loss: 8.997e-02 Loss in Target Net: 8.199e-03
2020-01-31 18:54:58 Iteration 1100 Training Loss: 9.246e-02 Loss in Target Net: 5.190e-03
2020-01-31 18:55:19 Iteration 1150 Training Loss: 9.246e-02 Loss in Target Net: 8.229e-03
2020-01-31 18:55:40 Iteration 1200 Training Loss: 8.460e-02 Loss in Target Net: 1.017e-02
2020-01-31 18:56:01 Iteration 1250 Training Loss: 9.817e-02 Loss in Target Net: 6.684e-03
2020-01-31 18:56:23 Iteration 1300 Training Loss: 9.117e-02 Loss in Target Net: 7.510e-03
2020-01-31 18:56:45 Iteration 1350 Training Loss: 8.817e-02 Loss in Target Net: 8.188e-03
2020-01-31 18:57:06 Iteration 1400 Training Loss: 9.626e-02 Loss in Target Net: 7.557e-03
2020-01-31 18:57:28 Iteration 1450 Training Loss: 8.883e-02 Loss in Target Net: 1.245e-02
2020-01-31 18:57:49 Iteration 1500 Training Loss: 9.266e-02 Loss in Target Net: 1.334e-02
2020-01-31 18:58:11 Iteration 1550 Training Loss: 8.695e-02 Loss in Target Net: 1.304e-02
2020-01-31 18:58:32 Iteration 1600 Training Loss: 9.059e-02 Loss in Target Net: 4.192e-03
2020-01-31 18:58:54 Iteration 1650 Training Loss: 8.654e-02 Loss in Target Net: 7.028e-03
2020-01-31 18:59:15 Iteration 1700 Training Loss: 9.556e-02 Loss in Target Net: 4.035e-03
2020-01-31 18:59:36 Iteration 1750 Training Loss: 8.784e-02 Loss in Target Net: 1.042e-02
2020-01-31 18:59:57 Iteration 1800 Training Loss: 9.759e-02 Loss in Target Net: 5.062e-03
2020-01-31 19:00:18 Iteration 1850 Training Loss: 9.225e-02 Loss in Target Net: 5.569e-03
2020-01-31 19:00:40 Iteration 1900 Training Loss: 8.638e-02 Loss in Target Net: 8.936e-03
2020-01-31 19:01:03 Iteration 1950 Training Loss: 8.845e-02 Loss in Target Net: 5.154e-03
2020-01-31 19:01:24 Iteration 2000 Training Loss: 8.805e-02 Loss in Target Net: 5.093e-03
2020-01-31 19:01:45 Iteration 2050 Training Loss: 9.411e-02 Loss in Target Net: 5.397e-03
2020-01-31 19:02:07 Iteration 2100 Training Loss: 8.799e-02 Loss in Target Net: 5.490e-03
2020-01-31 19:02:28 Iteration 2150 Training Loss: 9.003e-02 Loss in Target Net: 6.728e-03
2020-01-31 19:02:50 Iteration 2200 Training Loss: 8.425e-02 Loss in Target Net: 5.693e-03
2020-01-31 19:03:11 Iteration 2250 Training Loss: 9.205e-02 Loss in Target Net: 1.063e-02
2020-01-31 19:03:33 Iteration 2300 Training Loss: 8.707e-02 Loss in Target Net: 6.412e-03
2020-01-31 19:03:55 Iteration 2350 Training Loss: 9.009e-02 Loss in Target Net: 1.550e-02
2020-01-31 19:04:16 Iteration 2400 Training Loss: 9.239e-02 Loss in Target Net: 8.505e-03
2020-01-31 19:04:37 Iteration 2450 Training Loss: 8.495e-02 Loss in Target Net: 7.807e-03
2020-01-31 19:04:58 Iteration 2500 Training Loss: 9.092e-02 Loss in Target Net: 3.742e-03
2020-01-31 19:05:19 Iteration 2550 Training Loss: 9.428e-02 Loss in Target Net: 7.859e-03
2020-01-31 19:05:41 Iteration 2600 Training Loss: 9.030e-02 Loss in Target Net: 4.225e-03
2020-01-31 19:06:02 Iteration 2650 Training Loss: 8.385e-02 Loss in Target Net: 6.425e-03
2020-01-31 19:06:23 Iteration 2700 Training Loss: 1.012e-01 Loss in Target Net: 1.052e-02
2020-01-31 19:06:46 Iteration 2750 Training Loss: 9.023e-02 Loss in Target Net: 6.853e-03
2020-01-31 19:07:08 Iteration 2800 Training Loss: 9.481e-02 Loss in Target Net: 6.561e-03
2020-01-31 19:07:29 Iteration 2850 Training Loss: 8.448e-02 Loss in Target Net: 1.106e-02
2020-01-31 19:07:50 Iteration 2900 Training Loss: 8.966e-02 Loss in Target Net: 8.770e-03
2020-01-31 19:08:13 Iteration 2950 Training Loss: 9.762e-02 Loss in Target Net: 4.751e-03
2020-01-31 19:08:35 Iteration 3000 Training Loss: 9.209e-02 Loss in Target Net: 9.451e-03
2020-01-31 19:08:55 Iteration 3050 Training Loss: 8.454e-02 Loss in Target Net: 5.699e-03
2020-01-31 19:09:17 Iteration 3100 Training Loss: 9.114e-02 Loss in Target Net: 4.949e-03
2020-01-31 19:09:38 Iteration 3150 Training Loss: 9.889e-02 Loss in Target Net: 9.109e-03
2020-01-31 19:10:00 Iteration 3200 Training Loss: 8.408e-02 Loss in Target Net: 1.137e-02
2020-01-31 19:10:22 Iteration 3250 Training Loss: 9.347e-02 Loss in Target Net: 1.537e-02
2020-01-31 19:10:43 Iteration 3300 Training Loss: 9.432e-02 Loss in Target Net: 9.807e-03
2020-01-31 19:11:05 Iteration 3350 Training Loss: 9.235e-02 Loss in Target Net: 7.127e-03
2020-01-31 19:11:27 Iteration 3400 Training Loss: 9.022e-02 Loss in Target Net: 6.617e-03
2020-01-31 19:11:49 Iteration 3450 Training Loss: 9.078e-02 Loss in Target Net: 6.687e-03
2020-01-31 19:12:10 Iteration 3500 Training Loss: 8.659e-02 Loss in Target Net: 6.207e-03
2020-01-31 19:12:31 Iteration 3550 Training Loss: 1.026e-01 Loss in Target Net: 5.285e-03
2020-01-31 19:12:52 Iteration 3600 Training Loss: 8.166e-02 Loss in Target Net: 7.035e-03
2020-01-31 19:13:13 Iteration 3650 Training Loss: 8.729e-02 Loss in Target Net: 9.903e-03
2020-01-31 19:13:33 Iteration 3700 Training Loss: 9.078e-02 Loss in Target Net: 8.565e-03
2020-01-31 19:13:54 Iteration 3750 Training Loss: 8.887e-02 Loss in Target Net: 1.131e-02
2020-01-31 19:14:14 Iteration 3800 Training Loss: 9.217e-02 Loss in Target Net: 7.037e-03
2020-01-31 19:14:35 Iteration 3850 Training Loss: 8.094e-02 Loss in Target Net: 6.340e-03
2020-01-31 19:14:55 Iteration 3900 Training Loss: 8.352e-02 Loss in Target Net: 6.535e-03
2020-01-31 19:15:16 Iteration 3950 Training Loss: 9.019e-02 Loss in Target Net: 6.244e-03
2020-01-31 19:15:36 Iteration 3999 Training Loss: 8.561e-02 Loss in Target Net: 7.712e-03
Evaluating against victims networks
DPN92
Using Adam for retraining
Files already downloaded and verified
2020-01-31 19:15:41, Epoch 0, Iteration 7, loss 3.207 (4.246), acc 76.923 (65.800)
2020-01-31 19:15:41, Epoch 30, Iteration 7, loss 0.409 (0.158), acc 96.154 (96.600)
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-0.5299261, -33.441063, -41.465668, 2.9452267, -31.68492, -0.90755093, 32.192158, -41.85452, 36.604748, -81.76974], Poisons' Predictions:[8, 8, 8, 8, 8]
2020-01-31 19:15:45 Epoch 59, Val iteration 0, acc 93.200 (93.200)
2020-01-31 19:15:52 Epoch 59, Val iteration 19, acc 92.600 (92.720)
* Prec: 92.72000083923339
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SENet18
Using Adam for retraining
Files already downloaded and verified
2020-01-31 19:15:54, Epoch 0, Iteration 7, loss 0.568 (0.815), acc 94.231 (86.600)
2020-01-31 19:15:55, Epoch 30, Iteration 7, loss 0.282 (0.143), acc 90.385 (96.800)
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-1.053484, -15.603708, 1.9377314, 0.5167544, 9.66451, 1.1304168, 33.29328, -38.514164, 23.278143, -16.111914], Poisons' Predictions:[8, 8, 8, 8, 8]
2020-01-31 19:15:56 Epoch 59, Val iteration 0, acc 91.600 (91.600)
2020-01-31 19:15:58 Epoch 59, Val iteration 19, acc 92.800 (91.320)
* Prec: 91.32000160217285
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