Datasets:
SunayBhat1
/
PureGen_Poisons

Dataset card Data Studio Files
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2020-01-31 21:12:22 Iteration 100 Training Loss: 7.351e-02 Loss in Target Net: 9.192e-03
2020-01-31 21:12:45 Iteration 150 Training Loss: 7.178e-02 Loss in Target Net: 7.532e-03
2020-01-31 21:13:08 Iteration 200 Training Loss: 6.945e-02 Loss in Target Net: 1.006e-02
2020-01-31 21:13:30 Iteration 250 Training Loss: 6.814e-02 Loss in Target Net: 8.019e-03
2020-01-31 21:13:53 Iteration 300 Training Loss: 6.504e-02 Loss in Target Net: 9.060e-03
2020-01-31 21:14:17 Iteration 350 Training Loss: 7.380e-02 Loss in Target Net: 1.269e-02
2020-01-31 21:14:41 Iteration 400 Training Loss: 6.945e-02 Loss in Target Net: 1.131e-02
2020-01-31 21:15:04 Iteration 450 Training Loss: 7.342e-02 Loss in Target Net: 1.533e-02
2020-01-31 21:15:27 Iteration 500 Training Loss: 6.028e-02 Loss in Target Net: 1.125e-02
2020-01-31 21:15:50 Iteration 550 Training Loss: 6.548e-02 Loss in Target Net: 1.188e-02
2020-01-31 21:16:13 Iteration 600 Training Loss: 6.226e-02 Loss in Target Net: 9.132e-03
2020-01-31 21:16:35 Iteration 650 Training Loss: 6.307e-02 Loss in Target Net: 9.230e-03
2020-01-31 21:16:57 Iteration 700 Training Loss: 5.837e-02 Loss in Target Net: 7.879e-03
2020-01-31 21:17:21 Iteration 750 Training Loss: 6.580e-02 Loss in Target Net: 8.421e-03
2020-01-31 21:17:43 Iteration 800 Training Loss: 6.607e-02 Loss in Target Net: 8.108e-03
2020-01-31 21:18:06 Iteration 850 Training Loss: 5.874e-02 Loss in Target Net: 1.121e-02
2020-01-31 21:18:29 Iteration 900 Training Loss: 6.623e-02 Loss in Target Net: 1.088e-02
2020-01-31 21:18:53 Iteration 950 Training Loss: 6.636e-02 Loss in Target Net: 1.151e-02
2020-01-31 21:19:15 Iteration 1000 Training Loss: 5.954e-02 Loss in Target Net: 9.850e-03
2020-01-31 21:19:38 Iteration 1050 Training Loss: 7.015e-02 Loss in Target Net: 9.562e-03
2020-01-31 21:20:00 Iteration 1100 Training Loss: 6.375e-02 Loss in Target Net: 1.080e-02
2020-01-31 21:20:22 Iteration 1150 Training Loss: 6.873e-02 Loss in Target Net: 8.764e-03
2020-01-31 21:20:45 Iteration 1200 Training Loss: 6.106e-02 Loss in Target Net: 1.113e-02
2020-01-31 21:21:07 Iteration 1250 Training Loss: 6.438e-02 Loss in Target Net: 9.377e-03
2020-01-31 21:21:29 Iteration 1300 Training Loss: 6.974e-02 Loss in Target Net: 8.167e-03
2020-01-31 21:21:52 Iteration 1350 Training Loss: 6.552e-02 Loss in Target Net: 1.219e-02
2020-01-31 21:22:15 Iteration 1400 Training Loss: 6.335e-02 Loss in Target Net: 8.706e-03
2020-01-31 21:22:37 Iteration 1450 Training Loss: 6.821e-02 Loss in Target Net: 1.293e-02
2020-01-31 21:23:01 Iteration 1500 Training Loss: 6.875e-02 Loss in Target Net: 1.123e-02
2020-01-31 21:23:23 Iteration 1550 Training Loss: 6.274e-02 Loss in Target Net: 1.347e-02
2020-01-31 21:23:45 Iteration 1600 Training Loss: 6.935e-02 Loss in Target Net: 9.706e-03
2020-01-31 21:24:08 Iteration 1650 Training Loss: 6.868e-02 Loss in Target Net: 1.063e-02
2020-01-31 21:24:30 Iteration 1700 Training Loss: 6.026e-02 Loss in Target Net: 7.502e-03
2020-01-31 21:24:52 Iteration 1750 Training Loss: 6.494e-02 Loss in Target Net: 1.106e-02
2020-01-31 21:25:15 Iteration 1800 Training Loss: 6.836e-02 Loss in Target Net: 1.476e-02
2020-01-31 21:25:38 Iteration 1850 Training Loss: 6.638e-02 Loss in Target Net: 1.059e-02
2020-01-31 21:26:01 Iteration 1900 Training Loss: 6.278e-02 Loss in Target Net: 1.252e-02
2020-01-31 21:26:23 Iteration 1950 Training Loss: 5.961e-02 Loss in Target Net: 8.828e-03
2020-01-31 21:26:47 Iteration 2000 Training Loss: 6.182e-02 Loss in Target Net: 1.190e-02
2020-01-31 21:27:09 Iteration 2050 Training Loss: 6.183e-02 Loss in Target Net: 1.231e-02
2020-01-31 21:27:31 Iteration 2100 Training Loss: 6.619e-02 Loss in Target Net: 8.696e-03
2020-01-31 21:27:54 Iteration 2150 Training Loss: 6.463e-02 Loss in Target Net: 1.340e-02
2020-01-31 21:28:16 Iteration 2200 Training Loss: 6.156e-02 Loss in Target Net: 9.217e-03
2020-01-31 21:28:39 Iteration 2250 Training Loss: 6.442e-02 Loss in Target Net: 1.091e-02
2020-01-31 21:29:01 Iteration 2300 Training Loss: 6.693e-02 Loss in Target Net: 8.128e-03
2020-01-31 21:29:23 Iteration 2350 Training Loss: 6.328e-02 Loss in Target Net: 8.900e-03
2020-01-31 21:29:45 Iteration 2400 Training Loss: 6.661e-02 Loss in Target Net: 8.252e-03
2020-01-31 21:30:08 Iteration 2450 Training Loss: 6.309e-02 Loss in Target Net: 1.053e-02
2020-01-31 21:30:30 Iteration 2500 Training Loss: 6.406e-02 Loss in Target Net: 1.079e-02
2020-01-31 21:30:52 Iteration 2550 Training Loss: 6.144e-02 Loss in Target Net: 1.156e-02
2020-01-31 21:31:15 Iteration 2600 Training Loss: 6.156e-02 Loss in Target Net: 1.036e-02
2020-01-31 21:31:37 Iteration 2650 Training Loss: 7.105e-02 Loss in Target Net: 1.130e-02
2020-01-31 21:32:00 Iteration 2700 Training Loss: 6.820e-02 Loss in Target Net: 1.100e-02
2020-01-31 21:32:22 Iteration 2750 Training Loss: 6.387e-02 Loss in Target Net: 8.939e-03
2020-01-31 21:32:43 Iteration 2800 Training Loss: 5.798e-02 Loss in Target Net: 1.050e-02
2020-01-31 21:33:05 Iteration 2850 Training Loss: 6.859e-02 Loss in Target Net: 6.889e-03
2020-01-31 21:33:28 Iteration 2900 Training Loss: 6.962e-02 Loss in Target Net: 1.255e-02
2020-01-31 21:33:51 Iteration 2950 Training Loss: 6.355e-02 Loss in Target Net: 1.143e-02
2020-01-31 21:34:12 Iteration 3000 Training Loss: 6.244e-02 Loss in Target Net: 8.806e-03
2020-01-31 21:34:36 Iteration 3050 Training Loss: 6.264e-02 Loss in Target Net: 1.037e-02
2020-01-31 21:34:57 Iteration 3100 Training Loss: 6.352e-02 Loss in Target Net: 8.709e-03
2020-01-31 21:35:19 Iteration 3150 Training Loss: 6.495e-02 Loss in Target Net: 9.814e-03
2020-01-31 21:35:41 Iteration 3200 Training Loss: 6.228e-02 Loss in Target Net: 1.080e-02
2020-01-31 21:36:04 Iteration 3250 Training Loss: 6.182e-02 Loss in Target Net: 1.072e-02
2020-01-31 21:36:26 Iteration 3300 Training Loss: 6.901e-02 Loss in Target Net: 7.217e-03
2020-01-31 21:36:49 Iteration 3350 Training Loss: 5.968e-02 Loss in Target Net: 1.090e-02
2020-01-31 21:37:12 Iteration 3400 Training Loss: 6.059e-02 Loss in Target Net: 1.070e-02
2020-01-31 21:37:34 Iteration 3450 Training Loss: 6.603e-02 Loss in Target Net: 1.264e-02
2020-01-31 21:37:56 Iteration 3500 Training Loss: 6.457e-02 Loss in Target Net: 1.057e-02
2020-01-31 21:38:18 Iteration 3550 Training Loss: 5.888e-02 Loss in Target Net: 1.303e-02
2020-01-31 21:38:40 Iteration 3600 Training Loss: 6.349e-02 Loss in Target Net: 1.058e-02
2020-01-31 21:39:03 Iteration 3650 Training Loss: 5.920e-02 Loss in Target Net: 1.396e-02
2020-01-31 21:39:25 Iteration 3700 Training Loss: 6.080e-02 Loss in Target Net: 1.294e-02
2020-01-31 21:39:48 Iteration 3750 Training Loss: 6.187e-02 Loss in Target Net: 1.056e-02
2020-01-31 21:40:10 Iteration 3800 Training Loss: 6.459e-02 Loss in Target Net: 9.768e-03
2020-01-31 21:40:34 Iteration 3850 Training Loss: 6.149e-02 Loss in Target Net: 1.355e-02
2020-01-31 21:40:56 Iteration 3900 Training Loss: 5.545e-02 Loss in Target Net: 1.202e-02
2020-01-31 21:41:19 Iteration 3950 Training Loss: 6.541e-02 Loss in Target Net: 1.374e-02
2020-01-31 21:41:41 Iteration 3999 Training Loss: 5.916e-02 Loss in Target Net: 9.554e-03
Evaluating against victims networks
DPN92
Using Adam for retraining
Files already downloaded and verified
2020-01-31 21:41:45, Epoch 0, Iteration 7, loss 0.414 (3.849), acc 92.308 (66.600)
2020-01-31 21:41:46, Epoch 30, Iteration 7, loss 0.449 (0.232), acc 96.154 (96.400)
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[7.191953, -22.885098, -42.959896, -5.11252, -36.047123, -9.17223, 34.40605, -38.0104, 34.98662, -129.54895], Poisons' Predictions:[6, 8, 6, 6, 8]
2020-01-31 21:41:50 Epoch 59, Val iteration 0, acc 91.200 (91.200)
2020-01-31 21:41:57 Epoch 59, Val iteration 19, acc 92.800 (92.630)
* Prec: 92.63000144958497
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SENet18
Using Adam for retraining
Files already downloaded and verified
2020-01-31 21:41:59, Epoch 0, Iteration 7, loss 0.155 (0.909), acc 94.231 (87.600)
2020-01-31 21:42:00, Epoch 30, Iteration 7, loss 0.014 (0.264), acc 100.000 (95.200)
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[3.0628972, -12.729276, -14.46293, -6.251491, 1.2838513, -16.202133, 20.928043, -19.205524, 18.871468, -36.848442], Poisons' Predictions:[8, 6, 6, 8, 6]
2020-01-31 21:42:01 Epoch 59, Val iteration 0, acc 91.600 (91.600)
2020-01-31 21:42:02 Epoch 59, Val iteration 19, acc 93.000 (91.040)
* Prec: 91.04000129699708
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