Datasets:
SunayBhat1
/
PureGen_Poisons

Dataset card Data Studio Files
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2020-01-31 19:52:44 Iteration 900 Training Loss: 7.268e-02 Loss in Target Net: 7.203e-03
2020-01-31 19:53:05 Iteration 950 Training Loss: 7.824e-02 Loss in Target Net: 8.654e-03
2020-01-31 19:53:25 Iteration 1000 Training Loss: 7.731e-02 Loss in Target Net: 8.908e-03
2020-01-31 19:53:46 Iteration 1050 Training Loss: 7.763e-02 Loss in Target Net: 7.849e-03
2020-01-31 19:54:06 Iteration 1100 Training Loss: 7.453e-02 Loss in Target Net: 6.010e-03
2020-01-31 19:54:26 Iteration 1150 Training Loss: 7.164e-02 Loss in Target Net: 7.300e-03
2020-01-31 19:54:46 Iteration 1200 Training Loss: 7.366e-02 Loss in Target Net: 9.913e-03
2020-01-31 19:55:07 Iteration 1250 Training Loss: 7.605e-02 Loss in Target Net: 7.664e-03
2020-01-31 19:55:27 Iteration 1300 Training Loss: 7.824e-02 Loss in Target Net: 6.153e-03
2020-01-31 19:55:48 Iteration 1350 Training Loss: 8.125e-02 Loss in Target Net: 4.845e-03
2020-01-31 19:56:09 Iteration 1400 Training Loss: 7.837e-02 Loss in Target Net: 5.526e-03
2020-01-31 19:56:29 Iteration 1450 Training Loss: 7.143e-02 Loss in Target Net: 5.581e-03
2020-01-31 19:56:49 Iteration 1500 Training Loss: 8.262e-02 Loss in Target Net: 6.308e-03
2020-01-31 19:57:10 Iteration 1550 Training Loss: 7.832e-02 Loss in Target Net: 5.314e-03
2020-01-31 19:57:30 Iteration 1600 Training Loss: 7.259e-02 Loss in Target Net: 5.941e-03
2020-01-31 19:57:51 Iteration 1650 Training Loss: 7.697e-02 Loss in Target Net: 4.582e-03
2020-01-31 19:58:11 Iteration 1700 Training Loss: 7.208e-02 Loss in Target Net: 4.721e-03
2020-01-31 19:58:31 Iteration 1750 Training Loss: 8.171e-02 Loss in Target Net: 6.305e-03
2020-01-31 19:58:52 Iteration 1800 Training Loss: 7.476e-02 Loss in Target Net: 7.819e-03
2020-01-31 19:59:12 Iteration 1850 Training Loss: 7.539e-02 Loss in Target Net: 4.002e-03
2020-01-31 19:59:32 Iteration 1900 Training Loss: 7.441e-02 Loss in Target Net: 5.346e-03
2020-01-31 19:59:52 Iteration 1950 Training Loss: 7.771e-02 Loss in Target Net: 8.598e-03
2020-01-31 20:00:13 Iteration 2000 Training Loss: 7.410e-02 Loss in Target Net: 6.455e-03
2020-01-31 20:00:33 Iteration 2050 Training Loss: 7.406e-02 Loss in Target Net: 4.638e-03
2020-01-31 20:00:53 Iteration 2100 Training Loss: 7.637e-02 Loss in Target Net: 8.262e-03
2020-01-31 20:01:13 Iteration 2150 Training Loss: 7.537e-02 Loss in Target Net: 9.244e-03
2020-01-31 20:01:33 Iteration 2200 Training Loss: 7.674e-02 Loss in Target Net: 8.483e-03
2020-01-31 20:01:54 Iteration 2250 Training Loss: 8.524e-02 Loss in Target Net: 3.394e-03
2020-01-31 20:02:15 Iteration 2300 Training Loss: 7.460e-02 Loss in Target Net: 6.434e-03
2020-01-31 20:02:36 Iteration 2350 Training Loss: 7.476e-02 Loss in Target Net: 7.273e-03
2020-01-31 20:02:56 Iteration 2400 Training Loss: 7.467e-02 Loss in Target Net: 3.522e-03
2020-01-31 20:03:17 Iteration 2450 Training Loss: 7.431e-02 Loss in Target Net: 5.553e-03
2020-01-31 20:03:37 Iteration 2500 Training Loss: 7.706e-02 Loss in Target Net: 4.695e-03
2020-01-31 20:03:57 Iteration 2550 Training Loss: 7.509e-02 Loss in Target Net: 3.265e-03
2020-01-31 20:04:17 Iteration 2600 Training Loss: 7.019e-02 Loss in Target Net: 5.346e-03
2020-01-31 20:04:37 Iteration 2650 Training Loss: 7.358e-02 Loss in Target Net: 5.824e-03
2020-01-31 20:04:58 Iteration 2700 Training Loss: 8.073e-02 Loss in Target Net: 6.576e-03
2020-01-31 20:05:19 Iteration 2750 Training Loss: 7.620e-02 Loss in Target Net: 4.551e-03
2020-01-31 20:05:39 Iteration 2800 Training Loss: 7.901e-02 Loss in Target Net: 5.968e-03
2020-01-31 20:05:59 Iteration 2850 Training Loss: 7.592e-02 Loss in Target Net: 3.791e-03
2020-01-31 20:06:20 Iteration 2900 Training Loss: 7.612e-02 Loss in Target Net: 3.416e-03
2020-01-31 20:06:40 Iteration 2950 Training Loss: 7.133e-02 Loss in Target Net: 4.847e-03
2020-01-31 20:07:00 Iteration 3000 Training Loss: 6.939e-02 Loss in Target Net: 5.948e-03
2020-01-31 20:07:21 Iteration 3050 Training Loss: 7.091e-02 Loss in Target Net: 4.126e-03
2020-01-31 20:07:41 Iteration 3100 Training Loss: 8.181e-02 Loss in Target Net: 4.328e-03
2020-01-31 20:08:01 Iteration 3150 Training Loss: 7.836e-02 Loss in Target Net: 3.960e-03
2020-01-31 20:08:22 Iteration 3200 Training Loss: 7.786e-02 Loss in Target Net: 4.843e-03
2020-01-31 20:08:43 Iteration 3250 Training Loss: 8.081e-02 Loss in Target Net: 4.154e-03
2020-01-31 20:09:03 Iteration 3300 Training Loss: 7.932e-02 Loss in Target Net: 3.954e-03
2020-01-31 20:09:23 Iteration 3350 Training Loss: 7.269e-02 Loss in Target Net: 6.343e-03
2020-01-31 20:09:44 Iteration 3400 Training Loss: 7.778e-02 Loss in Target Net: 4.774e-03
2020-01-31 20:10:05 Iteration 3450 Training Loss: 7.641e-02 Loss in Target Net: 4.598e-03
2020-01-31 20:10:25 Iteration 3500 Training Loss: 7.252e-02 Loss in Target Net: 4.767e-03
2020-01-31 20:10:46 Iteration 3550 Training Loss: 7.116e-02 Loss in Target Net: 5.591e-03
2020-01-31 20:11:07 Iteration 3600 Training Loss: 7.790e-02 Loss in Target Net: 5.927e-03
2020-01-31 20:11:28 Iteration 3650 Training Loss: 7.653e-02 Loss in Target Net: 5.418e-03
2020-01-31 20:11:50 Iteration 3700 Training Loss: 7.065e-02 Loss in Target Net: 5.767e-03
2020-01-31 20:12:11 Iteration 3750 Training Loss: 7.966e-02 Loss in Target Net: 7.334e-03
2020-01-31 20:12:33 Iteration 3800 Training Loss: 7.259e-02 Loss in Target Net: 7.419e-03
2020-01-31 20:12:54 Iteration 3850 Training Loss: 7.643e-02 Loss in Target Net: 6.957e-03
2020-01-31 20:13:16 Iteration 3900 Training Loss: 6.938e-02 Loss in Target Net: 5.815e-03
2020-01-31 20:13:37 Iteration 3950 Training Loss: 7.188e-02 Loss in Target Net: 7.505e-03
2020-01-31 20:13:59 Iteration 3999 Training Loss: 7.914e-02 Loss in Target Net: 5.057e-03
Evaluating against victims networks
DPN92
Using Adam for retraining
Files already downloaded and verified
2020-01-31 20:14:03, Epoch 0, Iteration 7, loss 0.436 (3.040), acc 96.154 (75.400)
2020-01-31 20:14:03, Epoch 30, Iteration 7, loss 0.031 (0.010), acc 98.077 (99.600)
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[2.1252058, -49.80975, -61.54015, -14.115532, -53.777893, -29.072592, 9.641319, -41.958527, 21.873137, -118.31002], Poisons' Predictions:[8, 8, 8, 8, 8]
2020-01-31 20:14:07 Epoch 59, Val iteration 0, acc 92.000 (92.000)
2020-01-31 20:14:15 Epoch 59, Val iteration 19, acc 92.400 (92.370)
* Prec: 92.3700008392334
--------
SENet18
Using Adam for retraining
Files already downloaded and verified
2020-01-31 20:14:17, Epoch 0, Iteration 7, loss 1.094 (0.801), acc 84.615 (87.200)
2020-01-31 20:14:17, Epoch 30, Iteration 7, loss 0.099 (0.167), acc 96.154 (96.000)
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[5.329774, -9.9309635, -5.72799, -6.133371, 4.7590723, -12.718464, 23.55786, -1.2975645, 18.740242, -17.26503], Poisons' Predictions:[8, 8, 6, 6, 8]
2020-01-31 20:14:18 Epoch 59, Val iteration 0, acc 92.000 (92.000)
2020-01-31 20:14:20 Epoch 59, Val iteration 19, acc 92.200 (91.710)
* Prec: 91.71000137329102
--------
ResNet50
Using Adam for retraining
Files already downloaded and verified
2020-01-31 20:14:22, Epoch 0, Iteration 7, loss 0.747 (0.831), acc 92.308 (89.600)
2020-01-31 20:14:23, 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:[-92.26217, -39.841568, -35.642414, -62.00811, -83.539345, -63.75047, 14.186321, -41.801018, 17.900503, -48.531727], Poisons' Predictions:[8, 8, 8, 8, 8]
2020-01-31 20:14:24 Epoch 59, Val iteration 0, acc 93.000 (93.000)
2020-01-31 20:14:28 Epoch 59, Val iteration 19, acc 93.600 (93.480)
* Prec: 93.48000106811523
--------
ResNeXt29_2x64d
Using Adam for retraining
Files already downloaded and verified
2020-01-31 20:14:30, Epoch 0, Iteration 7, loss 2.005 (2.093), acc 80.769 (69.000)
2020-01-31 20:14:31, Epoch 30, Iteration 7, loss 0.013 (0.022), acc 100.000 (99.000)
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-22.100113, 10.495238, -3.0659919, 15.1143265, -75.76852, -24.647003, 29.060263, -15.63297, 24.73471, -25.641651], Poisons' Predictions:[8, 8, 8, 8, 8]