SunayBhat1/PureGen_Poisons · Datasets at Hugging Face

text stringlengths 5 1.13k
Path: chk-black-ourmean/mean/4000/39
Selected base image indices: [213, 225, 227, 247, 249]
2020-01-31 21:43:05 Iteration 0 Training Loss: 1.170e+00 Loss in Target Net: 4.578e-01
2020-01-31 21:43:29 Iteration 50 Training Loss: 1.033e-01 Loss in Target Net: 1.275e-02
2020-01-31 21:43:50 Iteration 100 Training Loss: 8.667e-02 Loss in Target Net: 7.806e-03
2020-01-31 21:44:12 Iteration 150 Training Loss: 8.837e-02 Loss in Target Net: 1.020e-02
2020-01-31 21:44:34 Iteration 200 Training Loss: 8.466e-02 Loss in Target Net: 8.396e-03
2020-01-31 21:44:55 Iteration 250 Training Loss: 8.767e-02 Loss in Target Net: 6.008e-03
2020-01-31 21:45:16 Iteration 300 Training Loss: 8.680e-02 Loss in Target Net: 9.107e-03
2020-01-31 21:45:40 Iteration 350 Training Loss: 8.566e-02 Loss in Target Net: 7.743e-03
2020-01-31 21:46:02 Iteration 400 Training Loss: 8.055e-02 Loss in Target Net: 5.163e-03
2020-01-31 21:46:23 Iteration 450 Training Loss: 8.008e-02 Loss in Target Net: 7.339e-03
2020-01-31 21:46:44 Iteration 500 Training Loss: 8.171e-02 Loss in Target Net: 3.725e-03
2020-01-31 21:47:06 Iteration 550 Training Loss: 8.028e-02 Loss in Target Net: 4.166e-03
2020-01-31 21:47:27 Iteration 600 Training Loss: 8.432e-02 Loss in Target Net: 4.950e-03
2020-01-31 21:47:48 Iteration 650 Training Loss: 8.533e-02 Loss in Target Net: 6.296e-03
2020-01-31 21:48:09 Iteration 700 Training Loss: 8.008e-02 Loss in Target Net: 5.651e-03
2020-01-31 21:48:30 Iteration 750 Training Loss: 7.758e-02 Loss in Target Net: 5.479e-03
2020-01-31 21:48:52 Iteration 800 Training Loss: 7.889e-02 Loss in Target Net: 4.803e-03
2020-01-31 21:49:13 Iteration 850 Training Loss: 8.136e-02 Loss in Target Net: 6.137e-03
2020-01-31 21:49:35 Iteration 900 Training Loss: 8.320e-02 Loss in Target Net: 6.686e-03
2020-01-31 21:49:57 Iteration 950 Training Loss: 8.539e-02 Loss in Target Net: 6.793e-03
2020-01-31 21:50:20 Iteration 1000 Training Loss: 8.670e-02 Loss in Target Net: 5.469e-03
2020-01-31 21:50:41 Iteration 1050 Training Loss: 7.548e-02 Loss in Target Net: 8.038e-03
2020-01-31 21:51:03 Iteration 1100 Training Loss: 7.915e-02 Loss in Target Net: 4.796e-03
2020-01-31 21:51:24 Iteration 1150 Training Loss: 8.491e-02 Loss in Target Net: 5.777e-03
2020-01-31 21:51:44 Iteration 1200 Training Loss: 7.338e-02 Loss in Target Net: 7.359e-03
2020-01-31 21:52:04 Iteration 1250 Training Loss: 7.643e-02 Loss in Target Net: 5.233e-03
2020-01-31 21:52:25 Iteration 1300 Training Loss: 8.589e-02 Loss in Target Net: 7.629e-03
2020-01-31 21:52:47 Iteration 1350 Training Loss: 7.822e-02 Loss in Target Net: 3.713e-03
2020-01-31 21:53:07 Iteration 1400 Training Loss: 7.976e-02 Loss in Target Net: 7.521e-03
2020-01-31 21:53:28 Iteration 1450 Training Loss: 7.777e-02 Loss in Target Net: 6.472e-03
2020-01-31 21:53:50 Iteration 1500 Training Loss: 8.109e-02 Loss in Target Net: 7.068e-03
2020-01-31 21:54:10 Iteration 1550 Training Loss: 8.491e-02 Loss in Target Net: 5.844e-03
2020-01-31 21:54:32 Iteration 1600 Training Loss: 8.273e-02 Loss in Target Net: 8.158e-03
2020-01-31 21:54:53 Iteration 1650 Training Loss: 7.933e-02 Loss in Target Net: 8.409e-03
2020-01-31 21:55:14 Iteration 1700 Training Loss: 7.659e-02 Loss in Target Net: 8.537e-03
2020-01-31 21:55:36 Iteration 1750 Training Loss: 8.122e-02 Loss in Target Net: 1.037e-02
2020-01-31 21:55:58 Iteration 1800 Training Loss: 7.953e-02 Loss in Target Net: 7.509e-03
2020-01-31 21:56:21 Iteration 1850 Training Loss: 7.310e-02 Loss in Target Net: 5.551e-03
2020-01-31 21:56:42 Iteration 1900 Training Loss: 8.098e-02 Loss in Target Net: 4.286e-03
2020-01-31 21:57:03 Iteration 1950 Training Loss: 7.635e-02 Loss in Target Net: 6.900e-03
2020-01-31 21:57:26 Iteration 2000 Training Loss: 8.094e-02 Loss in Target Net: 3.608e-03
2020-01-31 21:57:48 Iteration 2050 Training Loss: 7.801e-02 Loss in Target Net: 4.437e-03
2020-01-31 21:58:11 Iteration 2100 Training Loss: 7.625e-02 Loss in Target Net: 4.889e-03
2020-01-31 21:58:33 Iteration 2150 Training Loss: 8.090e-02 Loss in Target Net: 5.656e-03
2020-01-31 21:58:56 Iteration 2200 Training Loss: 8.005e-02 Loss in Target Net: 5.339e-03
2020-01-31 21:59:16 Iteration 2250 Training Loss: 7.638e-02 Loss in Target Net: 5.319e-03
2020-01-31 21:59:37 Iteration 2300 Training Loss: 7.295e-02 Loss in Target Net: 5.943e-03
2020-01-31 21:59:58 Iteration 2350 Training Loss: 7.371e-02 Loss in Target Net: 4.141e-03
2020-01-31 22:00:19 Iteration 2400 Training Loss: 8.197e-02 Loss in Target Net: 5.099e-03
2020-01-31 22:00:41 Iteration 2450 Training Loss: 7.614e-02 Loss in Target Net: 4.291e-03
2020-01-31 22:01:03 Iteration 2500 Training Loss: 8.154e-02 Loss in Target Net: 4.830e-03
2020-01-31 22:01:24 Iteration 2550 Training Loss: 7.514e-02 Loss in Target Net: 7.318e-03
2020-01-31 22:01:45 Iteration 2600 Training Loss: 8.569e-02 Loss in Target Net: 7.094e-03
2020-01-31 22:02:05 Iteration 2650 Training Loss: 7.407e-02 Loss in Target Net: 7.255e-03
2020-01-31 22:02:27 Iteration 2700 Training Loss: 8.180e-02 Loss in Target Net: 5.594e-03
2020-01-31 22:02:50 Iteration 2750 Training Loss: 8.609e-02 Loss in Target Net: 6.336e-03
2020-01-31 22:03:12 Iteration 2800 Training Loss: 7.619e-02 Loss in Target Net: 4.455e-03
2020-01-31 22:03:32 Iteration 2850 Training Loss: 7.819e-02 Loss in Target Net: 4.952e-03
2020-01-31 22:03:53 Iteration 2900 Training Loss: 7.649e-02 Loss in Target Net: 4.041e-03
2020-01-31 22:04:16 Iteration 2950 Training Loss: 7.450e-02 Loss in Target Net: 7.150e-03
2020-01-31 22:04:38 Iteration 3000 Training Loss: 7.262e-02 Loss in Target Net: 6.888e-03
2020-01-31 22:05:01 Iteration 3050 Training Loss: 7.917e-02 Loss in Target Net: 5.096e-03
2020-01-31 22:05:24 Iteration 3100 Training Loss: 7.509e-02 Loss in Target Net: 4.827e-03
2020-01-31 22:05:46 Iteration 3150 Training Loss: 7.555e-02 Loss in Target Net: 4.346e-03
2020-01-31 22:06:08 Iteration 3200 Training Loss: 8.267e-02 Loss in Target Net: 7.009e-03
2020-01-31 22:06:30 Iteration 3250 Training Loss: 7.531e-02 Loss in Target Net: 6.197e-03
2020-01-31 22:06:51 Iteration 3300 Training Loss: 7.550e-02 Loss in Target Net: 4.478e-03
2020-01-31 22:07:14 Iteration 3350 Training Loss: 7.242e-02 Loss in Target Net: 4.101e-03
2020-01-31 22:07:38 Iteration 3400 Training Loss: 8.375e-02 Loss in Target Net: 6.624e-03
2020-01-31 22:08:00 Iteration 3450 Training Loss: 7.290e-02 Loss in Target Net: 5.119e-03
2020-01-31 22:08:24 Iteration 3500 Training Loss: 7.375e-02 Loss in Target Net: 7.129e-03
2020-01-31 22:08:48 Iteration 3550 Training Loss: 8.166e-02 Loss in Target Net: 6.633e-03
2020-01-31 22:09:10 Iteration 3600 Training Loss: 7.360e-02 Loss in Target Net: 3.450e-03
2020-01-31 22:09:33 Iteration 3650 Training Loss: 7.465e-02 Loss in Target Net: 3.824e-03
2020-01-31 22:09:56 Iteration 3700 Training Loss: 8.132e-02 Loss in Target Net: 4.644e-03
2020-01-31 22:10:19 Iteration 3750 Training Loss: 7.235e-02 Loss in Target Net: 4.040e-03
2020-01-31 22:10:41 Iteration 3800 Training Loss: 7.884e-02 Loss in Target Net: 4.320e-03
2020-01-31 22:11:04 Iteration 3850 Training Loss: 8.040e-02 Loss in Target Net: 3.785e-03
2020-01-31 22:11:27 Iteration 3900 Training Loss: 7.850e-02 Loss in Target Net: 4.602e-03
2020-01-31 22:11:50 Iteration 3950 Training Loss: 7.668e-02 Loss in Target Net: 4.513e-03
2020-01-31 22:12:13 Iteration 3999 Training Loss: 8.215e-02 Loss in Target Net: 5.632e-03
Evaluating against victims networks
DPN92
Using Adam for retraining
Files already downloaded and verified
2020-01-31 22:12:17, Epoch 0, Iteration 7, loss 0.718 (3.729), acc 92.308 (69.600)
2020-01-31 22:12:18, Epoch 30, Iteration 7, loss 0.080 (0.202), acc 98.077 (97.600)
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[5.0158105, -16.462767, -26.103668, 4.9550614, -34.299107, -1.2050501, 25.931528, -34.638737, 27.749273, -82.46319], Poisons' Predictions:[8, 8, 8, 6, 6]
2020-01-31 22:12:22 Epoch 59, Val iteration 0, acc 90.200 (90.200)
2020-01-31 22:12:29 Epoch 59, Val iteration 19, acc 92.600 (91.890)
* Prec: 91.8900016784668
--------
SENet18
Using Adam for retraining
Files already downloaded and verified
2020-01-31 22:12:31, Epoch 0, Iteration 7, loss 1.808 (0.880), acc 82.692 (89.400)
2020-01-31 22:12:31, Epoch 30, Iteration 7, loss 0.243 (0.150), acc 96.154 (96.600)
Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-0.028677404, -26.044214, -6.1731215, -0.8430221, 0.17917347, -5.7760224, 17.823586, -23.672806, 14.606859, -6.304456], Poisons' Predictions:[8, 8, 8, 8, 6]

Path: chk-black-ourmean/mean/4000/39

Selected base image indices: [213, 225, 227, 247, 249]

2020-01-31 21:43:05 Iteration 0 Training Loss: 1.170e+00 Loss in Target Net: 4.578e-01

2020-01-31 21:43:29 Iteration 50 Training Loss: 1.033e-01 Loss in Target Net: 1.275e-02

2020-01-31 21:43:50 Iteration 100 Training Loss: 8.667e-02 Loss in Target Net: 7.806e-03

2020-01-31 21:44:12 Iteration 150 Training Loss: 8.837e-02 Loss in Target Net: 1.020e-02

2020-01-31 21:44:34 Iteration 200 Training Loss: 8.466e-02 Loss in Target Net: 8.396e-03

2020-01-31 21:44:55 Iteration 250 Training Loss: 8.767e-02 Loss in Target Net: 6.008e-03

2020-01-31 21:45:16 Iteration 300 Training Loss: 8.680e-02 Loss in Target Net: 9.107e-03

2020-01-31 21:45:40 Iteration 350 Training Loss: 8.566e-02 Loss in Target Net: 7.743e-03

2020-01-31 21:46:02 Iteration 400 Training Loss: 8.055e-02 Loss in Target Net: 5.163e-03

2020-01-31 21:46:23 Iteration 450 Training Loss: 8.008e-02 Loss in Target Net: 7.339e-03

2020-01-31 21:46:44 Iteration 500 Training Loss: 8.171e-02 Loss in Target Net: 3.725e-03

2020-01-31 21:47:06 Iteration 550 Training Loss: 8.028e-02 Loss in Target Net: 4.166e-03

2020-01-31 21:47:27 Iteration 600 Training Loss: 8.432e-02 Loss in Target Net: 4.950e-03

2020-01-31 21:47:48 Iteration 650 Training Loss: 8.533e-02 Loss in Target Net: 6.296e-03

2020-01-31 21:48:09 Iteration 700 Training Loss: 8.008e-02 Loss in Target Net: 5.651e-03

2020-01-31 21:48:30 Iteration 750 Training Loss: 7.758e-02 Loss in Target Net: 5.479e-03

2020-01-31 21:48:52 Iteration 800 Training Loss: 7.889e-02 Loss in Target Net: 4.803e-03

2020-01-31 21:49:13 Iteration 850 Training Loss: 8.136e-02 Loss in Target Net: 6.137e-03

2020-01-31 21:49:35 Iteration 900 Training Loss: 8.320e-02 Loss in Target Net: 6.686e-03

2020-01-31 21:49:57 Iteration 950 Training Loss: 8.539e-02 Loss in Target Net: 6.793e-03

2020-01-31 21:50:20 Iteration 1000 Training Loss: 8.670e-02 Loss in Target Net: 5.469e-03

2020-01-31 21:50:41 Iteration 1050 Training Loss: 7.548e-02 Loss in Target Net: 8.038e-03

2020-01-31 21:51:03 Iteration 1100 Training Loss: 7.915e-02 Loss in Target Net: 4.796e-03

2020-01-31 21:51:24 Iteration 1150 Training Loss: 8.491e-02 Loss in Target Net: 5.777e-03

2020-01-31 21:51:44 Iteration 1200 Training Loss: 7.338e-02 Loss in Target Net: 7.359e-03

2020-01-31 21:52:04 Iteration 1250 Training Loss: 7.643e-02 Loss in Target Net: 5.233e-03

2020-01-31 21:52:25 Iteration 1300 Training Loss: 8.589e-02 Loss in Target Net: 7.629e-03

2020-01-31 21:52:47 Iteration 1350 Training Loss: 7.822e-02 Loss in Target Net: 3.713e-03

2020-01-31 21:53:07 Iteration 1400 Training Loss: 7.976e-02 Loss in Target Net: 7.521e-03

2020-01-31 21:53:28 Iteration 1450 Training Loss: 7.777e-02 Loss in Target Net: 6.472e-03

2020-01-31 21:53:50 Iteration 1500 Training Loss: 8.109e-02 Loss in Target Net: 7.068e-03

2020-01-31 21:54:10 Iteration 1550 Training Loss: 8.491e-02 Loss in Target Net: 5.844e-03

2020-01-31 21:54:32 Iteration 1600 Training Loss: 8.273e-02 Loss in Target Net: 8.158e-03

2020-01-31 21:54:53 Iteration 1650 Training Loss: 7.933e-02 Loss in Target Net: 8.409e-03

2020-01-31 21:55:14 Iteration 1700 Training Loss: 7.659e-02 Loss in Target Net: 8.537e-03

2020-01-31 21:55:36 Iteration 1750 Training Loss: 8.122e-02 Loss in Target Net: 1.037e-02

2020-01-31 21:55:58 Iteration 1800 Training Loss: 7.953e-02 Loss in Target Net: 7.509e-03

2020-01-31 21:56:21 Iteration 1850 Training Loss: 7.310e-02 Loss in Target Net: 5.551e-03

2020-01-31 21:56:42 Iteration 1900 Training Loss: 8.098e-02 Loss in Target Net: 4.286e-03

2020-01-31 21:57:03 Iteration 1950 Training Loss: 7.635e-02 Loss in Target Net: 6.900e-03

2020-01-31 21:57:26 Iteration 2000 Training Loss: 8.094e-02 Loss in Target Net: 3.608e-03

2020-01-31 21:57:48 Iteration 2050 Training Loss: 7.801e-02 Loss in Target Net: 4.437e-03

2020-01-31 21:58:11 Iteration 2100 Training Loss: 7.625e-02 Loss in Target Net: 4.889e-03

2020-01-31 21:58:33 Iteration 2150 Training Loss: 8.090e-02 Loss in Target Net: 5.656e-03

2020-01-31 21:58:56 Iteration 2200 Training Loss: 8.005e-02 Loss in Target Net: 5.339e-03

2020-01-31 21:59:16 Iteration 2250 Training Loss: 7.638e-02 Loss in Target Net: 5.319e-03

2020-01-31 21:59:37 Iteration 2300 Training Loss: 7.295e-02 Loss in Target Net: 5.943e-03

2020-01-31 21:59:58 Iteration 2350 Training Loss: 7.371e-02 Loss in Target Net: 4.141e-03

2020-01-31 22:00:19 Iteration 2400 Training Loss: 8.197e-02 Loss in Target Net: 5.099e-03

2020-01-31 22:00:41 Iteration 2450 Training Loss: 7.614e-02 Loss in Target Net: 4.291e-03

2020-01-31 22:01:03 Iteration 2500 Training Loss: 8.154e-02 Loss in Target Net: 4.830e-03

2020-01-31 22:01:24 Iteration 2550 Training Loss: 7.514e-02 Loss in Target Net: 7.318e-03

2020-01-31 22:01:45 Iteration 2600 Training Loss: 8.569e-02 Loss in Target Net: 7.094e-03

2020-01-31 22:02:05 Iteration 2650 Training Loss: 7.407e-02 Loss in Target Net: 7.255e-03

2020-01-31 22:02:27 Iteration 2700 Training Loss: 8.180e-02 Loss in Target Net: 5.594e-03

2020-01-31 22:02:50 Iteration 2750 Training Loss: 8.609e-02 Loss in Target Net: 6.336e-03

2020-01-31 22:03:12 Iteration 2800 Training Loss: 7.619e-02 Loss in Target Net: 4.455e-03

2020-01-31 22:03:32 Iteration 2850 Training Loss: 7.819e-02 Loss in Target Net: 4.952e-03

2020-01-31 22:03:53 Iteration 2900 Training Loss: 7.649e-02 Loss in Target Net: 4.041e-03

2020-01-31 22:04:16 Iteration 2950 Training Loss: 7.450e-02 Loss in Target Net: 7.150e-03

2020-01-31 22:04:38 Iteration 3000 Training Loss: 7.262e-02 Loss in Target Net: 6.888e-03

2020-01-31 22:05:01 Iteration 3050 Training Loss: 7.917e-02 Loss in Target Net: 5.096e-03

2020-01-31 22:05:24 Iteration 3100 Training Loss: 7.509e-02 Loss in Target Net: 4.827e-03

2020-01-31 22:05:46 Iteration 3150 Training Loss: 7.555e-02 Loss in Target Net: 4.346e-03

2020-01-31 22:06:08 Iteration 3200 Training Loss: 8.267e-02 Loss in Target Net: 7.009e-03

2020-01-31 22:06:30 Iteration 3250 Training Loss: 7.531e-02 Loss in Target Net: 6.197e-03

2020-01-31 22:06:51 Iteration 3300 Training Loss: 7.550e-02 Loss in Target Net: 4.478e-03

2020-01-31 22:07:14 Iteration 3350 Training Loss: 7.242e-02 Loss in Target Net: 4.101e-03

2020-01-31 22:07:38 Iteration 3400 Training Loss: 8.375e-02 Loss in Target Net: 6.624e-03

2020-01-31 22:08:00 Iteration 3450 Training Loss: 7.290e-02 Loss in Target Net: 5.119e-03

2020-01-31 22:08:24 Iteration 3500 Training Loss: 7.375e-02 Loss in Target Net: 7.129e-03

2020-01-31 22:08:48 Iteration 3550 Training Loss: 8.166e-02 Loss in Target Net: 6.633e-03

2020-01-31 22:09:10 Iteration 3600 Training Loss: 7.360e-02 Loss in Target Net: 3.450e-03

2020-01-31 22:09:33 Iteration 3650 Training Loss: 7.465e-02 Loss in Target Net: 3.824e-03

2020-01-31 22:09:56 Iteration 3700 Training Loss: 8.132e-02 Loss in Target Net: 4.644e-03

2020-01-31 22:10:19 Iteration 3750 Training Loss: 7.235e-02 Loss in Target Net: 4.040e-03

2020-01-31 22:10:41 Iteration 3800 Training Loss: 7.884e-02 Loss in Target Net: 4.320e-03

2020-01-31 22:11:04 Iteration 3850 Training Loss: 8.040e-02 Loss in Target Net: 3.785e-03

2020-01-31 22:11:27 Iteration 3900 Training Loss: 7.850e-02 Loss in Target Net: 4.602e-03

2020-01-31 22:11:50 Iteration 3950 Training Loss: 7.668e-02 Loss in Target Net: 4.513e-03

2020-01-31 22:12:13 Iteration 3999 Training Loss: 8.215e-02 Loss in Target Net: 5.632e-03

Evaluating against victims networks

DPN92

Using Adam for retraining

Files already downloaded and verified

2020-01-31 22:12:17, Epoch 0, Iteration 7, loss 0.718 (3.729), acc 92.308 (69.600)

2020-01-31 22:12:18, Epoch 30, Iteration 7, loss 0.080 (0.202), acc 98.077 (97.600)

Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[5.0158105, -16.462767, -26.103668, 4.9550614, -34.299107, -1.2050501, 25.931528, -34.638737, 27.749273, -82.46319], Poisons' Predictions:[8, 8, 8, 6, 6]

2020-01-31 22:12:22 Epoch 59, Val iteration 0, acc 90.200 (90.200)

2020-01-31 22:12:29 Epoch 59, Val iteration 19, acc 92.600 (91.890)

* Prec: 91.8900016784668

--------

SENet18

Using Adam for retraining

Files already downloaded and verified

2020-01-31 22:12:31, Epoch 0, Iteration 7, loss 1.808 (0.880), acc 82.692 (89.400)

2020-01-31 22:12:31, Epoch 30, Iteration 7, loss 0.243 (0.150), acc 96.154 (96.600)

Target Label: 6, Poison label: 8, Prediction:6, Target's Score:[-0.028677404, -26.044214, -6.1731215, -0.8430221, 0.17917347, -5.7760224, 17.823586, -23.672806, 14.606859, -6.304456], Poisons' Predictions:[8, 8, 8, 8, 6]