
=== 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 BitFlippingWorker
=> Add worker BitFlippingWorker

=== Start adding graph ===
<codes.graph_utils.DumbbellVariant object at 0x7fc5fc7aeb80>

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: 1.0075 top1= 63.7500
[E 1B20 |   8064/60000 ( 13%) ] Loss: 0.2661 top1= 91.5625
[E 1B30 |  11904/60000 ( 20%) ] Loss: 0.4770 top1= 85.3125
[E 1B40 |  15744/60000 ( 26%) ] Loss: 0.2780 top1= 90.6250
[E 1B50 |  19584/60000 ( 33%) ] Loss: 0.1891 top1= 93.1250

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.7391 top1= 83.4635


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.3016 top1= 49.8197


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.7494 top1= 45.5529

Train epoch 2
[E 2B0  |    384/60000 (  1%) ] Loss: 0.1742 top1= 94.3750
[E 2B10 |   4224/60000 (  7%) ] Loss: 0.1674 top1= 95.0000
[E 2B20 |   8064/60000 ( 13%) ] Loss: 0.1271 top1= 95.6250
[E 2B30 |  11904/60000 ( 20%) ] Loss: 0.1508 top1= 95.6250
[E 2B40 |  15744/60000 ( 26%) ] Loss: 0.1323 top1= 95.0000
[E 2B50 |  19584/60000 ( 33%) ] Loss: 0.0797 top1= 97.8125

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6243 top1= 85.8874


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.1663 top1= 50.2804


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.7299 top1= 46.2240

Train epoch 3
[E 3B0  |    384/60000 (  1%) ] Loss: 0.0985 top1= 96.8750
[E 3B10 |   4224/60000 (  7%) ] Loss: 0.0884 top1= 96.2500
[E 3B20 |   8064/60000 ( 13%) ] Loss: 0.0702 top1= 98.4375
[E 3B30 |  11904/60000 ( 20%) ] Loss: 0.1094 top1= 95.9375
[E 3B40 |  15744/60000 ( 26%) ] Loss: 0.0722 top1= 97.5000
[E 3B50 |  19584/60000 ( 33%) ] Loss: 0.0435 top1= 98.7500

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5321 top1= 87.0192


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.3154 top1= 50.5409


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.8986 top1= 46.2841

Train epoch 4
[E 4B0  |    384/60000 (  1%) ] Loss: 0.0624 top1= 98.4375
[E 4B10 |   4224/60000 (  7%) ] Loss: 0.0501 top1= 98.4375
[E 4B20 |   8064/60000 ( 13%) ] Loss: 0.0313 top1= 99.3750
[E 4B30 |  11904/60000 ( 20%) ] Loss: 0.0586 top1= 98.4375
[E 4B40 |  15744/60000 ( 26%) ] Loss: 0.0489 top1= 98.7500
[E 4B50 |  19584/60000 ( 33%) ] Loss: 0.0226 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4480 top1= 88.5617


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.5310 top1= 50.5609


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.1396 top1= 46.6346

Train epoch 5
[E 5B0  |    384/60000 (  1%) ] Loss: 0.0327 top1= 99.0625
[E 5B10 |   4224/60000 (  7%) ] Loss: 0.0409 top1= 98.7500
[E 5B20 |   8064/60000 ( 13%) ] Loss: 0.0240 top1= 99.3750
[E 5B30 |  11904/60000 ( 20%) ] Loss: 0.0285 top1= 99.3750
[E 5B40 |  15744/60000 ( 26%) ] Loss: 0.0252 top1= 99.6875
[E 5B50 |  19584/60000 ( 33%) ] Loss: 0.0258 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3817 top1= 90.1342


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.7185 top1= 50.6110


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.1679 top1= 47.1655

Train epoch 6
[E 6B0  |    384/60000 (  1%) ] Loss: 0.0205 top1= 99.3750
[E 6B10 |   4224/60000 (  7%) ] Loss: 0.0279 top1= 98.7500
[E 6B20 |   8064/60000 ( 13%) ] Loss: 0.0096 top1=100.0000
[E 6B30 |  11904/60000 ( 20%) ] Loss: 0.0146 top1=100.0000
[E 6B40 |  15744/60000 ( 26%) ] Loss: 0.0211 top1= 99.6875
[E 6B50 |  19584/60000 ( 33%) ] Loss: 0.0162 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3568 top1= 90.1743


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.7349 top1= 50.5208


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.2603 top1= 47.1655

Train epoch 7
[E 7B0  |    384/60000 (  1%) ] Loss: 0.0123 top1= 99.6875
[E 7B10 |   4224/60000 (  7%) ] Loss: 0.0144 top1= 99.3750
[E 7B20 |   8064/60000 ( 13%) ] Loss: 0.0070 top1=100.0000
[E 7B30 |  11904/60000 ( 20%) ] Loss: 0.0142 top1= 99.6875
[E 7B40 |  15744/60000 ( 26%) ] Loss: 0.0176 top1= 99.6875
[E 7B50 |  19584/60000 ( 33%) ] Loss: 0.0180 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3500 top1= 90.0741


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.4543 top1= 50.4107


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.4777 top1= 46.9050

Train epoch 8
[E 8B0  |    384/60000 (  1%) ] Loss: 0.0104 top1=100.0000
[E 8B10 |   4224/60000 (  7%) ] Loss: 0.0076 top1=100.0000
[E 8B20 |   8064/60000 ( 13%) ] Loss: 0.0045 top1=100.0000
[E 8B30 |  11904/60000 ( 20%) ] Loss: 0.0128 top1= 99.6875
[E 8B40 |  15744/60000 ( 26%) ] Loss: 0.0114 top1=100.0000
[E 8B50 |  19584/60000 ( 33%) ] Loss: 0.0066 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3318 top1= 90.7151


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.3024 top1= 50.7011


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.5907 top1= 47.1354

Train epoch 9
[E 9B0  |    384/60000 (  1%) ] Loss: 0.0064 top1=100.0000
[E 9B10 |   4224/60000 (  7%) ] Loss: 0.0119 top1= 99.3750
[E 9B20 |   8064/60000 ( 13%) ] Loss: 0.0143 top1= 99.6875
[E 9B30 |  11904/60000 ( 20%) ] Loss: 0.0131 top1= 99.6875
[E 9B40 |  15744/60000 ( 26%) ] Loss: 0.0049 top1=100.0000
[E 9B50 |  19584/60000 ( 33%) ] Loss: 0.0039 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3048 top1= 91.3361


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.3870 top1= 50.7512


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.5964 top1= 47.1154

Train epoch 10
[E10B0  |    384/60000 (  1%) ] Loss: 0.0057 top1=100.0000
[E10B10 |   4224/60000 (  7%) ] Loss: 0.0120 top1=100.0000
[E10B20 |   8064/60000 ( 13%) ] Loss: 0.0050 top1=100.0000
[E10B30 |  11904/60000 ( 20%) ] Loss: 0.0066 top1=100.0000
[E10B40 |  15744/60000 ( 26%) ] Loss: 0.0042 top1=100.0000
[E10B50 |  19584/60000 ( 33%) ] Loss: 0.0040 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3113 top1= 90.8554


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.6666 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.3164 top1= 47.2256

Train epoch 11
[E11B0  |    384/60000 (  1%) ] Loss: 0.0022 top1=100.0000
[E11B10 |   4224/60000 (  7%) ] Loss: 0.0054 top1=100.0000
[E11B20 |   8064/60000 ( 13%) ] Loss: 0.0025 top1=100.0000
[E11B30 |  11904/60000 ( 20%) ] Loss: 0.0089 top1= 99.3750
[E11B40 |  15744/60000 ( 26%) ] Loss: 0.0061 top1= 99.6875
[E11B50 |  19584/60000 ( 33%) ] Loss: 0.0035 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3170 top1= 90.6951


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.9296 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.1874 top1= 47.2356

Train epoch 12
[E12B0  |    384/60000 (  1%) ] Loss: 0.0018 top1=100.0000
[E12B10 |   4224/60000 (  7%) ] Loss: 0.0038 top1=100.0000
[E12B20 |   8064/60000 ( 13%) ] Loss: 0.0021 top1=100.0000
[E12B30 |  11904/60000 ( 20%) ] Loss: 0.0066 top1= 99.6875
[E12B40 |  15744/60000 ( 26%) ] Loss: 0.0029 top1=100.0000
[E12B50 |  19584/60000 ( 33%) ] Loss: 0.0023 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3166 top1= 90.4046


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.1516 top1= 50.7011


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.3573 top1= 47.2155

Train epoch 13
[E13B0  |    384/60000 (  1%) ] Loss: 0.0019 top1=100.0000
[E13B10 |   4224/60000 (  7%) ] Loss: 0.0019 top1=100.0000
[E13B20 |   8064/60000 ( 13%) ] Loss: 0.0022 top1=100.0000
[E13B30 |  11904/60000 ( 20%) ] Loss: 0.0026 top1=100.0000
[E13B40 |  15744/60000 ( 26%) ] Loss: 0.0021 top1=100.0000
[E13B50 |  19584/60000 ( 33%) ] Loss: 0.0016 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3396 top1= 89.1226


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.3395 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.2665 top1= 47.1554

Train epoch 14
[E14B0  |    384/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E14B10 |   4224/60000 (  7%) ] Loss: 0.0019 top1=100.0000
[E14B20 |   8064/60000 ( 13%) ] Loss: 0.0014 top1=100.0000
[E14B30 |  11904/60000 ( 20%) ] Loss: 0.0035 top1=100.0000
[E14B40 |  15744/60000 ( 26%) ] Loss: 0.0012 top1=100.0000
[E14B50 |  19584/60000 ( 33%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3289 top1= 89.3730


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.4872 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.2878 top1= 47.3057

Train epoch 15
[E15B0  |    384/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E15B10 |   4224/60000 (  7%) ] Loss: 0.0015 top1=100.0000
[E15B20 |   8064/60000 ( 13%) ] Loss: 0.0028 top1=100.0000
[E15B30 |  11904/60000 ( 20%) ] Loss: 0.0020 top1=100.0000
[E15B40 |  15744/60000 ( 26%) ] Loss: 0.0011 top1=100.0000
[E15B50 |  19584/60000 ( 33%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3241 top1= 89.1126


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.6060 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.3751 top1= 47.3658

Train epoch 16
[E16B0  |    384/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E16B10 |   4224/60000 (  7%) ] Loss: 0.0012 top1=100.0000
[E16B20 |   8064/60000 ( 13%) ] Loss: 0.0009 top1=100.0000
[E16B30 |  11904/60000 ( 20%) ] Loss: 0.0011 top1=100.0000
[E16B40 |  15744/60000 ( 26%) ] Loss: 0.0009 top1=100.0000
[E16B50 |  19584/60000 ( 33%) ] Loss: 0.0008 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3083 top1= 89.7536


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.7069 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.5847 top1= 47.5060

Train epoch 17
[E17B0  |    384/60000 (  1%) ] Loss: 0.0007 top1=100.0000
[E17B10 |   4224/60000 (  7%) ] Loss: 0.0006 top1=100.0000
[E17B20 |   8064/60000 ( 13%) ] Loss: 0.0007 top1=100.0000
[E17B30 |  11904/60000 ( 20%) ] Loss: 0.0009 top1=100.0000
[E17B40 |  15744/60000 ( 26%) ] Loss: 0.0007 top1=100.0000
[E17B50 |  19584/60000 ( 33%) ] Loss: 0.0006 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3055 top1= 89.7336


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.7945 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.7164 top1= 47.4760

Train epoch 18
[E18B0  |    384/60000 (  1%) ] Loss: 0.0006 top1=100.0000
[E18B10 |   4224/60000 (  7%) ] Loss: 0.0005 top1=100.0000
[E18B20 |   8064/60000 ( 13%) ] Loss: 0.0006 top1=100.0000
[E18B30 |  11904/60000 ( 20%) ] Loss: 0.0008 top1=100.0000
[E18B40 |  15744/60000 ( 26%) ] Loss: 0.0007 top1=100.0000
[E18B50 |  19584/60000 ( 33%) ] Loss: 0.0005 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3041 top1= 89.8037


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.8717 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.8340 top1= 47.4659

Train epoch 19
[E19B0  |    384/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E19B10 |   4224/60000 (  7%) ] Loss: 0.0005 top1=100.0000
[E19B20 |   8064/60000 ( 13%) ] Loss: 0.0005 top1=100.0000
[E19B30 |  11904/60000 ( 20%) ] Loss: 0.0007 top1=100.0000
[E19B40 |  15744/60000 ( 26%) ] Loss: 0.0006 top1=100.0000
[E19B50 |  19584/60000 ( 33%) ] Loss: 0.0005 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3033 top1= 89.8337


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9386 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.9301 top1= 47.4559

Train epoch 20
[E20B0  |    384/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E20B10 |   4224/60000 (  7%) ] Loss: 0.0004 top1=100.0000
[E20B20 |   8064/60000 ( 13%) ] Loss: 0.0004 top1=100.0000
[E20B30 |  11904/60000 ( 20%) ] Loss: 0.0007 top1=100.0000
[E20B40 |  15744/60000 ( 26%) ] Loss: 0.0006 top1=100.0000
[E20B50 |  19584/60000 ( 33%) ] Loss: 0.0004 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3033 top1= 89.7636


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.0028 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.0093 top1= 47.4359

Train epoch 21
[E21B0  |    384/60000 (  1%) ] Loss: 0.0004 top1=100.0000
[E21B10 |   4224/60000 (  7%) ] Loss: 0.0004 top1=100.0000
[E21B20 |   8064/60000 ( 13%) ] Loss: 0.0004 top1=100.0000
[E21B30 |  11904/60000 ( 20%) ] Loss: 0.0006 top1=100.0000
[E21B40 |  15744/60000 ( 26%) ] Loss: 0.0005 top1=100.0000
[E21B50 |  19584/60000 ( 33%) ] Loss: 0.0004 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3038 top1= 89.7837


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.0618 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.0793 top1= 47.4359

Train epoch 22
[E22B0  |    384/60000 (  1%) ] Loss: 0.0004 top1=100.0000
[E22B10 |   4224/60000 (  7%) ] Loss: 0.0003 top1=100.0000
[E22B20 |   8064/60000 ( 13%) ] Loss: 0.0003 top1=100.0000
[E22B30 |  11904/60000 ( 20%) ] Loss: 0.0005 top1=100.0000
[E22B40 |  15744/60000 ( 26%) ] Loss: 0.0005 top1=100.0000
[E22B50 |  19584/60000 ( 33%) ] Loss: 0.0004 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3046 top1= 89.7336


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.1169 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.1405 top1= 47.4359

Train epoch 23
[E23B0  |    384/60000 (  1%) ] Loss: 0.0003 top1=100.0000
[E23B10 |   4224/60000 (  7%) ] Loss: 0.0003 top1=100.0000
[E23B20 |   8064/60000 ( 13%) ] Loss: 0.0003 top1=100.0000
[E23B30 |  11904/60000 ( 20%) ] Loss: 0.0005 top1=100.0000
[E23B40 |  15744/60000 ( 26%) ] Loss: 0.0005 top1=100.0000
[E23B50 |  19584/60000 ( 33%) ] Loss: 0.0003 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3053 top1= 89.6735


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.1672 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.1937 top1= 47.4359

Train epoch 24
[E24B0  |    384/60000 (  1%) ] Loss: 0.0003 top1=100.0000
[E24B10 |   4224/60000 (  7%) ] Loss: 0.0003 top1=100.0000
[E24B20 |   8064/60000 ( 13%) ] Loss: 0.0003 top1=100.0000
[E24B30 |  11904/60000 ( 20%) ] Loss: 0.0004 top1=100.0000
[E24B40 |  15744/60000 ( 26%) ] Loss: 0.0004 top1=100.0000
[E24B50 |  19584/60000 ( 33%) ] Loss: 0.0003 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3061 top1= 89.6835


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.2151 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.2452 top1= 47.4559

Train epoch 25
[E25B0  |    384/60000 (  1%) ] Loss: 0.0003 top1=100.0000
[E25B10 |   4224/60000 (  7%) ] Loss: 0.0003 top1=100.0000
[E25B20 |   8064/60000 ( 13%) ] Loss: 0.0003 top1=100.0000
[E25B30 |  11904/60000 ( 20%) ] Loss: 0.0004 top1=100.0000
[E25B40 |  15744/60000 ( 26%) ] Loss: 0.0004 top1=100.0000
[E25B50 |  19584/60000 ( 33%) ] Loss: 0.0003 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3067 top1= 89.6735


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.2606 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.2911 top1= 47.4459

Train epoch 26
[E26B0  |    384/60000 (  1%) ] Loss: 0.0003 top1=100.0000
[E26B10 |   4224/60000 (  7%) ] Loss: 0.0003 top1=100.0000
[E26B20 |   8064/60000 ( 13%) ] Loss: 0.0002 top1=100.0000
[E26B30 |  11904/60000 ( 20%) ] Loss: 0.0004 top1=100.0000
[E26B40 |  15744/60000 ( 26%) ] Loss: 0.0004 top1=100.0000
[E26B50 |  19584/60000 ( 33%) ] Loss: 0.0003 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3074 top1= 89.6534


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.3042 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.3352 top1= 47.4559

Train epoch 27
[E27B0  |    384/60000 (  1%) ] Loss: 0.0002 top1=100.0000
[E27B10 |   4224/60000 (  7%) ] Loss: 0.0002 top1=100.0000
[E27B20 |   8064/60000 ( 13%) ] Loss: 0.0002 top1=100.0000
[E27B30 |  11904/60000 ( 20%) ] Loss: 0.0004 top1=100.0000
[E27B40 |  15744/60000 ( 26%) ] Loss: 0.0003 top1=100.0000
[E27B50 |  19584/60000 ( 33%) ] Loss: 0.0003 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3079 top1= 89.6134


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.3456 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.3761 top1= 47.4559

Train epoch 28
[E28B0  |    384/60000 (  1%) ] Loss: 0.0002 top1=100.0000
[E28B10 |   4224/60000 (  7%) ] Loss: 0.0002 top1=100.0000
[E28B20 |   8064/60000 ( 13%) ] Loss: 0.0002 top1=100.0000
[E28B30 |  11904/60000 ( 20%) ] Loss: 0.0003 top1=100.0000
[E28B40 |  15744/60000 ( 26%) ] Loss: 0.0003 top1=100.0000
[E28B50 |  19584/60000 ( 33%) ] Loss: 0.0003 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3083 top1= 89.5833


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.3841 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4176 top1= 47.4659

Train epoch 29
[E29B0  |    384/60000 (  1%) ] Loss: 0.0002 top1=100.0000
[E29B10 |   4224/60000 (  7%) ] Loss: 0.0002 top1=100.0000
[E29B20 |   8064/60000 ( 13%) ] Loss: 0.0002 top1=100.0000
[E29B30 |  11904/60000 ( 20%) ] Loss: 0.0003 top1=100.0000
[E29B40 |  15744/60000 ( 26%) ] Loss: 0.0003 top1=100.0000
[E29B50 |  19584/60000 ( 33%) ] Loss: 0.0002 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3088 top1= 89.5833


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.4209 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4555 top1= 47.4659

Train epoch 30
[E30B0  |    384/60000 (  1%) ] Loss: 0.0002 top1=100.0000
[E30B10 |   4224/60000 (  7%) ] Loss: 0.0002 top1=100.0000
[E30B20 |   8064/60000 ( 13%) ] Loss: 0.0002 top1=100.0000
[E30B30 |  11904/60000 ( 20%) ] Loss: 0.0003 top1=100.0000
[E30B40 |  15744/60000 ( 26%) ] Loss: 0.0003 top1=100.0000
[E30B50 |  19584/60000 ( 33%) ] Loss: 0.0002 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3091 top1= 89.5633


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.4561 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4904 top1= 47.4659

