
=== Start adding workers ===
=> Add worker SGDMWorker(index=0, momentum=0.9)
=> Add worker SGDMWorker(index=1, momentum=0.9)
=> Add worker SGDMWorker(index=2, momentum=0.9)
=> Add worker SGDMWorker(index=3, momentum=0.9)
=> Add worker SGDMWorker(index=4, momentum=0.9)
=> Add worker SGDMWorker(index=5, momentum=0.9)
=> Add worker SGDMWorker(index=6, momentum=0.9)
=> Add worker SGDMWorker(index=7, momentum=0.9)
=> Add worker SGDMWorker(index=8, momentum=0.9)
=> Add worker SGDMWorker(index=9, momentum=0.9)
=> Add worker ByzantineWorker(index=10)
=> Add worker ByzantineWorker(index=11)

=== Start adding graph ===
<codes.graph_utils.DumbbellVariant object at 0x7fb9fc8027c0>

Train epoch 1
[E 1B0  |    384/60000 (  1%) ] Loss: 2.3109 top1=  9.6875

=== Peeking data label distribution E1B0 ===
Worker 0 has targets: tensor([3, 0, 2, 2, 1], device='cuda:0')
Worker 1 has targets: tensor([2, 1, 4, 4, 0], device='cuda:0')
Worker 2 has targets: tensor([3, 1, 4, 1, 3], device='cuda:0')
Worker 3 has targets: tensor([2, 3, 0, 0, 1], device='cuda:0')
Worker 4 has targets: tensor([2, 1, 1, 4, 2], device='cuda:0')
Worker 5 has targets: tensor([6, 7, 6, 8, 6], device='cuda:0')
Worker 6 has targets: tensor([9, 9, 6, 7, 9], device='cuda:0')
Worker 7 has targets: tensor([7, 5, 7, 9, 5], device='cuda:0')
Worker 8 has targets: tensor([8, 9, 9, 5, 7], device='cuda:0')
Worker 9 has targets: tensor([8, 8, 7, 5, 9], device='cuda:0')
Worker 10 has targets: tensor([3, 0, 2, 2, 1], device='cuda:0')
Worker 11 has targets: tensor([6, 7, 6, 8, 6], device='cuda:0')


[E 1B10 |   4224/60000 (  7%) ] Loss: 1.0133 top1= 65.0000
[E 1B20 |   8064/60000 ( 13%) ] Loss: 0.2596 top1= 90.6250
[E 1B30 |  11904/60000 ( 20%) ] Loss: 0.4662 top1= 86.8750
[E 1B40 |  15744/60000 ( 26%) ] Loss: 0.2609 top1= 90.0000
[E 1B50 |  19584/60000 ( 33%) ] Loss: 0.1705 top1= 94.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4598 top1= 87.1194


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.4442 top1= 51.3121


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.0836 top1= 48.2873

Train epoch 2
[E 2B0  |    384/60000 (  1%) ] Loss: 0.1879 top1= 95.3125
[E 2B10 |   4224/60000 (  7%) ] Loss: 0.1645 top1= 94.6875
[E 2B20 |   8064/60000 ( 13%) ] Loss: 0.1324 top1= 95.9375
[E 2B30 |  11904/60000 ( 20%) ] Loss: 0.1722 top1= 95.3125
[E 2B40 |  15744/60000 ( 26%) ] Loss: 0.1419 top1= 95.0000
[E 2B50 |  19584/60000 ( 33%) ] Loss: 0.1017 top1= 96.5625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3341 top1= 89.7336


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.1555 top1= 56.0096


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5739 top1= 55.4387

Train epoch 3
[E 3B0  |    384/60000 (  1%) ] Loss: 0.1084 top1= 96.8750
[E 3B10 |   4224/60000 (  7%) ] Loss: 0.1154 top1= 96.2500
[E 3B20 |   8064/60000 ( 13%) ] Loss: 0.0861 top1= 96.5625
[E 3B30 |  11904/60000 ( 20%) ] Loss: 0.1190 top1= 97.1875
[E 3B40 |  15744/60000 ( 26%) ] Loss: 0.0970 top1= 96.8750
[E 3B50 |  19584/60000 ( 33%) ] Loss: 0.0533 top1= 98.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2790 top1= 90.8253


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.8623 top1= 58.9343


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5045 top1= 58.6038

Train epoch 4
[E 4B0  |    384/60000 (  1%) ] Loss: 0.0606 top1= 99.0625
[E 4B10 |   4224/60000 (  7%) ] Loss: 0.0794 top1= 96.5625
[E 4B20 |   8064/60000 ( 13%) ] Loss: 0.0527 top1= 99.0625
[E 4B30 |  11904/60000 ( 20%) ] Loss: 0.0807 top1= 97.5000
[E 4B40 |  15744/60000 ( 26%) ] Loss: 0.0724 top1= 97.8125
[E 4B50 |  19584/60000 ( 33%) ] Loss: 0.0333 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2472 top1= 91.6166


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.7128 top1= 61.4784


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.4835 top1= 62.1795

Train epoch 5
[E 5B0  |    384/60000 (  1%) ] Loss: 0.0484 top1= 98.7500
[E 5B10 |   4224/60000 (  7%) ] Loss: 0.0551 top1= 97.8125
[E 5B20 |   8064/60000 ( 13%) ] Loss: 0.0390 top1= 99.0625
[E 5B30 |  11904/60000 ( 20%) ] Loss: 0.0552 top1= 98.1250
[E 5B40 |  15744/60000 ( 26%) ] Loss: 0.0432 top1= 98.7500
[E 5B50 |  19584/60000 ( 33%) ] Loss: 0.0278 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2373 top1= 91.8069


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.6039 top1= 64.1226


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5922 top1= 62.9808

Train epoch 6
[E 6B0  |    384/60000 (  1%) ] Loss: 0.0378 top1= 99.0625
[E 6B10 |   4224/60000 (  7%) ] Loss: 0.0512 top1= 98.1250
[E 6B20 |   8064/60000 ( 13%) ] Loss: 0.0392 top1= 98.7500
[E 6B30 |  11904/60000 ( 20%) ] Loss: 0.0507 top1= 97.8125
[E 6B40 |  15744/60000 ( 26%) ] Loss: 0.0340 top1= 99.3750
[E 6B50 |  19584/60000 ( 33%) ] Loss: 0.0269 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2321 top1= 92.2476


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.4139 top1= 66.6967


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.3770 top1= 67.7484

Train epoch 7
[E 7B0  |    384/60000 (  1%) ] Loss: 0.0305 top1= 99.6875
[E 7B10 |   4224/60000 (  7%) ] Loss: 0.0325 top1= 99.0625
[E 7B20 |   8064/60000 ( 13%) ] Loss: 0.0131 top1=100.0000
[E 7B30 |  11904/60000 ( 20%) ] Loss: 0.0331 top1= 99.0625
[E 7B40 |  15744/60000 ( 26%) ] Loss: 0.0154 top1=100.0000
[E 7B50 |  19584/60000 ( 33%) ] Loss: 0.0122 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1987 top1= 93.7099


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0976 top1= 70.6230


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.0406 top1= 71.3542

Train epoch 8
[E 8B0  |    384/60000 (  1%) ] Loss: 0.0204 top1= 99.3750
[E 8B10 |   4224/60000 (  7%) ] Loss: 0.0189 top1= 99.6875
[E 8B20 |   8064/60000 ( 13%) ] Loss: 0.0288 top1= 98.7500
[E 8B30 |  11904/60000 ( 20%) ] Loss: 0.0310 top1= 98.4375
[E 8B40 |  15744/60000 ( 26%) ] Loss: 0.0112 top1=100.0000
[E 8B50 |  19584/60000 ( 33%) ] Loss: 0.0132 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1952 top1= 93.8001


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1380 top1= 71.3241


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.0699 top1= 71.8349

Train epoch 9
[E 9B0  |    384/60000 (  1%) ] Loss: 0.0111 top1= 99.6875
[E 9B10 |   4224/60000 (  7%) ] Loss: 0.0130 top1= 99.6875
[E 9B20 |   8064/60000 ( 13%) ] Loss: 0.0060 top1=100.0000
[E 9B30 |  11904/60000 ( 20%) ] Loss: 0.0101 top1= 99.6875
[E 9B40 |  15744/60000 ( 26%) ] Loss: 0.0139 top1=100.0000
[E 9B50 |  19584/60000 ( 33%) ] Loss: 0.0104 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1874 top1= 94.2107


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1663 top1= 71.7949


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.9358 top1= 75.2704

Train epoch 10
[E10B0  |    384/60000 (  1%) ] Loss: 0.0051 top1=100.0000
[E10B10 |   4224/60000 (  7%) ] Loss: 0.0073 top1=100.0000
[E10B20 |   8064/60000 ( 13%) ] Loss: 0.0040 top1=100.0000
[E10B30 |  11904/60000 ( 20%) ] Loss: 0.0067 top1=100.0000
[E10B40 |  15744/60000 ( 26%) ] Loss: 0.0045 top1=100.0000
[E10B50 |  19584/60000 ( 33%) ] Loss: 0.0041 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1891 top1= 94.3610


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.8937 top1= 76.6927


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.8708 top1= 77.7143

Train epoch 11
[E11B0  |    384/60000 (  1%) ] Loss: 0.0040 top1=100.0000
[E11B10 |   4224/60000 (  7%) ] Loss: 0.0048 top1=100.0000
[E11B20 |   8064/60000 ( 13%) ] Loss: 0.0029 top1=100.0000
[E11B30 |  11904/60000 ( 20%) ] Loss: 0.0050 top1=100.0000
[E11B40 |  15744/60000 ( 26%) ] Loss: 0.0041 top1=100.0000
[E11B50 |  19584/60000 ( 33%) ] Loss: 0.0022 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1880 top1= 94.5012


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.7335 top1= 80.3185


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.7348 top1= 80.6591

Train epoch 12
[E12B0  |    384/60000 (  1%) ] Loss: 0.0034 top1=100.0000
[E12B10 |   4224/60000 (  7%) ] Loss: 0.0023 top1=100.0000
[E12B20 |   8064/60000 ( 13%) ] Loss: 0.0023 top1=100.0000
[E12B30 |  11904/60000 ( 20%) ] Loss: 0.0027 top1=100.0000
[E12B40 |  15744/60000 ( 26%) ] Loss: 0.0031 top1=100.0000
[E12B50 |  19584/60000 ( 33%) ] Loss: 0.0026 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1871 top1= 94.8217


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.6760 top1= 82.0413


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.6823 top1= 82.3618

Train epoch 13
[E13B0  |    384/60000 (  1%) ] Loss: 0.0021 top1=100.0000
[E13B10 |   4224/60000 (  7%) ] Loss: 0.0021 top1=100.0000
[E13B20 |   8064/60000 ( 13%) ] Loss: 0.0015 top1=100.0000
[E13B30 |  11904/60000 ( 20%) ] Loss: 0.0033 top1=100.0000
[E13B40 |  15744/60000 ( 26%) ] Loss: 0.0026 top1=100.0000
[E13B50 |  19584/60000 ( 33%) ] Loss: 0.0015 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1850 top1= 94.8718


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.6425 top1= 82.9026


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.6400 top1= 83.4335

Train epoch 14
[E14B0  |    384/60000 (  1%) ] Loss: 0.0017 top1=100.0000
[E14B10 |   4224/60000 (  7%) ] Loss: 0.0014 top1=100.0000
[E14B20 |   8064/60000 ( 13%) ] Loss: 0.0012 top1=100.0000
[E14B30 |  11904/60000 ( 20%) ] Loss: 0.0028 top1=100.0000
[E14B40 |  15744/60000 ( 26%) ] Loss: 0.0029 top1=100.0000
[E14B50 |  19584/60000 ( 33%) ] Loss: 0.0014 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1854 top1= 95.0120


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.6127 top1= 84.0244


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.5774 top1= 84.9760

Train epoch 15
[E15B0  |    384/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E15B10 |   4224/60000 (  7%) ] Loss: 0.0011 top1=100.0000
[E15B20 |   8064/60000 ( 13%) ] Loss: 0.0011 top1=100.0000
[E15B30 |  11904/60000 ( 20%) ] Loss: 0.0020 top1=100.0000
[E15B40 |  15744/60000 ( 26%) ] Loss: 0.0013 top1=100.0000
[E15B50 |  19584/60000 ( 33%) ] Loss: 0.0012 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1868 top1= 95.0721


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.5801 top1= 84.9058


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.5547 top1= 85.9175

Train epoch 16
[E16B0  |    384/60000 (  1%) ] Loss: 0.0013 top1=100.0000
[E16B10 |   4224/60000 (  7%) ] Loss: 0.0009 top1=100.0000
[E16B20 |   8064/60000 ( 13%) ] Loss: 0.0009 top1=100.0000
[E16B30 |  11904/60000 ( 20%) ] Loss: 0.0015 top1=100.0000
[E16B40 |  15744/60000 ( 26%) ] Loss: 0.0012 top1=100.0000
[E16B50 |  19584/60000 ( 33%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1878 top1= 95.0721


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.5521 top1= 85.7572


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.5368 top1= 86.4583

Train epoch 17
[E17B0  |    384/60000 (  1%) ] Loss: 0.0012 top1=100.0000
[E17B10 |   4224/60000 (  7%) ] Loss: 0.0009 top1=100.0000
[E17B20 |   8064/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E17B30 |  11904/60000 ( 20%) ] Loss: 0.0014 top1=100.0000
[E17B40 |  15744/60000 ( 26%) ] Loss: 0.0011 top1=100.0000
[E17B50 |  19584/60000 ( 33%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1885 top1= 95.1222


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.5324 top1= 86.3181


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.5250 top1= 86.8790

Train epoch 18
[E18B0  |    384/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E18B10 |   4224/60000 (  7%) ] Loss: 0.0008 top1=100.0000
[E18B20 |   8064/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E18B30 |  11904/60000 ( 20%) ] Loss: 0.0012 top1=100.0000
[E18B40 |  15744/60000 ( 26%) ] Loss: 0.0010 top1=100.0000
[E18B50 |  19584/60000 ( 33%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1892 top1= 95.1923


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.5163 top1= 86.9191


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.5130 top1= 87.3097

Train epoch 19
[E19B0  |    384/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E19B10 |   4224/60000 (  7%) ] Loss: 0.0007 top1=100.0000
[E19B20 |   8064/60000 ( 13%) ] Loss: 0.0007 top1=100.0000
[E19B30 |  11904/60000 ( 20%) ] Loss: 0.0011 top1=100.0000
[E19B40 |  15744/60000 ( 26%) ] Loss: 0.0010 top1=100.0000
[E19B50 |  19584/60000 ( 33%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1898 top1= 95.2023


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.5006 top1= 87.3698


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.5023 top1= 87.7204

Train epoch 20
[E20B0  |    384/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E20B10 |   4224/60000 (  7%) ] Loss: 0.0007 top1=100.0000
[E20B20 |   8064/60000 ( 13%) ] Loss: 0.0007 top1=100.0000
[E20B30 |  11904/60000 ( 20%) ] Loss: 0.0010 top1=100.0000
[E20B40 |  15744/60000 ( 26%) ] Loss: 0.0009 top1=100.0000
[E20B50 |  19584/60000 ( 33%) ] Loss: 0.0008 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1905 top1= 95.2724


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4882 top1= 87.8706


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4924 top1= 88.0308

Train epoch 21
[E21B0  |    384/60000 (  1%) ] Loss: 0.0008 top1=100.0000
[E21B10 |   4224/60000 (  7%) ] Loss: 0.0007 top1=100.0000
[E21B20 |   8064/60000 ( 13%) ] Loss: 0.0006 top1=100.0000
[E21B30 |  11904/60000 ( 20%) ] Loss: 0.0009 top1=100.0000
[E21B40 |  15744/60000 ( 26%) ] Loss: 0.0008 top1=100.0000
[E21B50 |  19584/60000 ( 33%) ] Loss: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1911 top1= 95.3325


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4757 top1= 88.3213


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4839 top1= 88.2913

Train epoch 22
[E22B0  |    384/60000 (  1%) ] Loss: 0.0008 top1=100.0000
[E22B10 |   4224/60000 (  7%) ] Loss: 0.0006 top1=100.0000
[E22B20 |   8064/60000 ( 13%) ] Loss: 0.0006 top1=100.0000
[E22B30 |  11904/60000 ( 20%) ] Loss: 0.0009 top1=100.0000
[E22B40 |  15744/60000 ( 26%) ] Loss: 0.0008 top1=100.0000
[E22B50 |  19584/60000 ( 33%) ] Loss: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1918 top1= 95.3526


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4648 top1= 88.6819


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4760 top1= 88.6018

Train epoch 23
[E23B0  |    384/60000 (  1%) ] Loss: 0.0007 top1=100.0000
[E23B10 |   4224/60000 (  7%) ] Loss: 0.0006 top1=100.0000
[E23B20 |   8064/60000 ( 13%) ] Loss: 0.0006 top1=100.0000
[E23B30 |  11904/60000 ( 20%) ] Loss: 0.0008 top1=100.0000
[E23B40 |  15744/60000 ( 26%) ] Loss: 0.0008 top1=100.0000
[E23B50 |  19584/60000 ( 33%) ] Loss: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1923 top1= 95.3926


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4542 top1= 89.0925


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4688 top1= 88.8121

Train epoch 24
[E24B0  |    384/60000 (  1%) ] Loss: 0.0007 top1=100.0000
[E24B10 |   4224/60000 (  7%) ] Loss: 0.0005 top1=100.0000
[E24B20 |   8064/60000 ( 13%) ] Loss: 0.0005 top1=100.0000
[E24B30 |  11904/60000 ( 20%) ] Loss: 0.0007 top1=100.0000
[E24B40 |  15744/60000 ( 26%) ] Loss: 0.0007 top1=100.0000
[E24B50 |  19584/60000 ( 33%) ] Loss: 0.0006 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1930 top1= 95.3726


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4451 top1= 89.4531


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4620 top1= 89.0024

Train epoch 25
[E25B0  |    384/60000 (  1%) ] Loss: 0.0006 top1=100.0000
[E25B10 |   4224/60000 (  7%) ] Loss: 0.0005 top1=100.0000
[E25B20 |   8064/60000 ( 13%) ] Loss: 0.0005 top1=100.0000
[E25B30 |  11904/60000 ( 20%) ] Loss: 0.0007 top1=100.0000
[E25B40 |  15744/60000 ( 26%) ] Loss: 0.0007 top1=100.0000
[E25B50 |  19584/60000 ( 33%) ] Loss: 0.0006 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1935 top1= 95.3826


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4364 top1= 89.6434


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4556 top1= 89.2228

Train epoch 26
[E26B0  |    384/60000 (  1%) ] Loss: 0.0006 top1=100.0000
[E26B10 |   4224/60000 (  7%) ] Loss: 0.0005 top1=100.0000
[E26B20 |   8064/60000 ( 13%) ] Loss: 0.0005 top1=100.0000
[E26B30 |  11904/60000 ( 20%) ] Loss: 0.0006 top1=100.0000
[E26B40 |  15744/60000 ( 26%) ] Loss: 0.0006 top1=100.0000
[E26B50 |  19584/60000 ( 33%) ] Loss: 0.0005 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1940 top1= 95.3826


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4283 top1= 89.8137


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4497 top1= 89.4331

Train epoch 27
[E27B0  |    384/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E27B10 |   4224/60000 (  7%) ] Loss: 0.0005 top1=100.0000
[E27B20 |   8064/60000 ( 13%) ] Loss: 0.0005 top1=100.0000
[E27B30 |  11904/60000 ( 20%) ] Loss: 0.0006 top1=100.0000
[E27B40 |  15744/60000 ( 26%) ] Loss: 0.0006 top1=100.0000
[E27B50 |  19584/60000 ( 33%) ] Loss: 0.0005 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1946 top1= 95.3926


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4209 top1= 90.0942


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4441 top1= 89.5633

Train epoch 28
[E28B0  |    384/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E28B10 |   4224/60000 (  7%) ] Loss: 0.0004 top1=100.0000
[E28B20 |   8064/60000 ( 13%) ] Loss: 0.0005 top1=100.0000
[E28B30 |  11904/60000 ( 20%) ] Loss: 0.0006 top1=100.0000
[E28B40 |  15744/60000 ( 26%) ] Loss: 0.0006 top1=100.0000
[E28B50 |  19584/60000 ( 33%) ] Loss: 0.0005 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1951 top1= 95.3826


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4140 top1= 90.3546


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4389 top1= 89.7236

Train epoch 29
[E29B0  |    384/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E29B10 |   4224/60000 (  7%) ] Loss: 0.0004 top1=100.0000
[E29B20 |   8064/60000 ( 13%) ] Loss: 0.0004 top1=100.0000
[E29B30 |  11904/60000 ( 20%) ] Loss: 0.0005 top1=100.0000
[E29B40 |  15744/60000 ( 26%) ] Loss: 0.0006 top1=100.0000
[E29B50 |  19584/60000 ( 33%) ] Loss: 0.0005 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1956 top1= 95.4026


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4076 top1= 90.5148


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4339 top1= 89.8838

Train epoch 30
[E30B0  |    384/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E30B10 |   4224/60000 (  7%) ] Loss: 0.0004 top1=100.0000
[E30B20 |   8064/60000 ( 13%) ] Loss: 0.0004 top1=100.0000
[E30B30 |  11904/60000 ( 20%) ] Loss: 0.0005 top1=100.0000
[E30B40 |  15744/60000 ( 26%) ] Loss: 0.0005 top1=100.0000
[E30B50 |  19584/60000 ( 33%) ] Loss: 0.0004 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1961 top1= 95.4227


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4010 top1= 90.6951


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4291 top1= 90.0741

