
=== 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 LabelFlippingWorker
=> Add worker LabelFlippingWorker

=== Start adding graph ===
<codes.graph_utils.DumbbellVariant object at 0x7f529f0d77c0>

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([6, 9, 7, 7, 8], device='cuda:0')
Worker 11 has targets: tensor([3, 2, 3, 1, 3], device='cuda:0')


[E 1B10 |   4224/60000 (  7%) ] Loss: 1.0476 top1= 65.3125
[E 1B20 |   8064/60000 ( 13%) ] Loss: 0.2705 top1= 91.2500
[E 1B30 |  11904/60000 ( 20%) ] Loss: 0.4190 top1= 87.1875
[E 1B40 |  15744/60000 ( 26%) ] Loss: 0.2637 top1= 90.0000
[E 1B50 |  19584/60000 ( 33%) ] Loss: 0.1788 top1= 95.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4930 top1= 86.8890


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.4195 top1= 51.0517


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1545 top1= 46.5946

Train epoch 2
[E 2B0  |    384/60000 (  1%) ] Loss: 0.1786 top1= 95.3125
[E 2B10 |   4224/60000 (  7%) ] Loss: 0.1914 top1= 94.3750
[E 2B20 |   8064/60000 ( 13%) ] Loss: 0.1433 top1= 95.6250
[E 2B30 |  11904/60000 ( 20%) ] Loss: 0.2219 top1= 94.0625
[E 2B40 |  15744/60000 ( 26%) ] Loss: 0.1610 top1= 94.0625
[E 2B50 |  19584/60000 ( 33%) ] Loss: 0.1094 top1= 95.6250

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3677 top1= 89.1927


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.2142 top1= 54.1567


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.9684 top1= 49.2989

Train epoch 3
[E 3B0  |    384/60000 (  1%) ] Loss: 0.1192 top1= 95.6250
[E 3B10 |   4224/60000 (  7%) ] Loss: 0.1349 top1= 95.0000
[E 3B20 |   8064/60000 ( 13%) ] Loss: 0.0941 top1= 97.1875
[E 3B30 |  11904/60000 ( 20%) ] Loss: 0.1331 top1= 96.5625
[E 3B40 |  15744/60000 ( 26%) ] Loss: 0.1127 top1= 96.5625
[E 3B50 |  19584/60000 ( 33%) ] Loss: 0.0715 top1= 98.7500

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3301 top1= 89.7937


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.2459 top1= 55.5990


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1166 top1= 49.3490

Train epoch 4
[E 4B0  |    384/60000 (  1%) ] Loss: 0.0929 top1= 96.5625
[E 4B10 |   4224/60000 (  7%) ] Loss: 0.0965 top1= 96.5625
[E 4B20 |   8064/60000 ( 13%) ] Loss: 0.0635 top1= 98.1250
[E 4B30 |  11904/60000 ( 20%) ] Loss: 0.0887 top1= 97.5000
[E 4B40 |  15744/60000 ( 26%) ] Loss: 0.0789 top1= 97.5000
[E 4B50 |  19584/60000 ( 33%) ] Loss: 0.0673 top1= 97.8125

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2910 top1= 90.8754


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.3239 top1= 55.8393


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.0146 top1= 51.2119

Train epoch 5
[E 5B0  |    384/60000 (  1%) ] Loss: 0.0469 top1= 99.6875
[E 5B10 |   4224/60000 (  7%) ] Loss: 0.0649 top1= 98.1250
[E 5B20 |   8064/60000 ( 13%) ] Loss: 0.0530 top1= 98.1250
[E 5B30 |  11904/60000 ( 20%) ] Loss: 0.0747 top1= 98.4375
[E 5B40 |  15744/60000 ( 26%) ] Loss: 0.0589 top1= 98.4375
[E 5B50 |  19584/60000 ( 33%) ] Loss: 0.0574 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2687 top1= 91.4663


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.3797 top1= 55.7692


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.9064 top1= 54.6274

Train epoch 6
[E 6B0  |    384/60000 (  1%) ] Loss: 0.0380 top1= 99.3750
[E 6B10 |   4224/60000 (  7%) ] Loss: 0.0262 top1= 99.0625
[E 6B20 |   8064/60000 ( 13%) ] Loss: 0.0433 top1= 98.7500
[E 6B30 |  11904/60000 ( 20%) ] Loss: 0.0510 top1= 98.4375
[E 6B40 |  15744/60000 ( 26%) ] Loss: 0.0533 top1= 97.8125
[E 6B50 |  19584/60000 ( 33%) ] Loss: 0.0231 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2787 top1= 90.8253


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.9573 top1= 58.4936


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.3162 top1= 52.3137

Train epoch 7
[E 7B0  |    384/60000 (  1%) ] Loss: 0.0184 top1= 99.6875
[E 7B10 |   4224/60000 (  7%) ] Loss: 0.0465 top1= 97.8125
[E 7B20 |   8064/60000 ( 13%) ] Loss: 0.0195 top1=100.0000
[E 7B30 |  11904/60000 ( 20%) ] Loss: 0.0407 top1= 99.0625
[E 7B40 |  15744/60000 ( 26%) ] Loss: 0.0423 top1= 98.7500
[E 7B50 |  19584/60000 ( 33%) ] Loss: 0.0209 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2473 top1= 92.0573


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.0323 top1= 58.9744


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1945 top1= 53.0950

Train epoch 8
[E 8B0  |    384/60000 (  1%) ] Loss: 0.0199 top1= 99.3750
[E 8B10 |   4224/60000 (  7%) ] Loss: 0.0272 top1= 99.3750
[E 8B20 |   8064/60000 ( 13%) ] Loss: 0.0160 top1= 99.6875
[E 8B30 |  11904/60000 ( 20%) ] Loss: 0.0363 top1= 98.4375
[E 8B40 |  15744/60000 ( 26%) ] Loss: 0.0241 top1= 99.3750
[E 8B50 |  19584/60000 ( 33%) ] Loss: 0.0276 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2365 top1= 92.3678


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.0352 top1= 59.7055


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.2799 top1= 53.0148

Train epoch 9
[E 9B0  |    384/60000 (  1%) ] Loss: 0.0140 top1= 99.6875
[E 9B10 |   4224/60000 (  7%) ] Loss: 0.0180 top1=100.0000
[E 9B20 |   8064/60000 ( 13%) ] Loss: 0.0762 top1= 97.8125
[E 9B30 |  11904/60000 ( 20%) ] Loss: 0.0256 top1= 99.3750
[E 9B40 |  15744/60000 ( 26%) ] Loss: 0.0553 top1= 98.4375
[E 9B50 |  19584/60000 ( 33%) ] Loss: 0.0169 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2295 top1= 92.9788


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.9079 top1= 60.1963


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.3189 top1= 53.3854

Train epoch 10
[E10B0  |    384/60000 (  1%) ] Loss: 0.0169 top1= 99.6875
[E10B10 |   4224/60000 (  7%) ] Loss: 0.0194 top1= 99.0625
[E10B20 |   8064/60000 ( 13%) ] Loss: 0.0117 top1= 99.6875
[E10B30 |  11904/60000 ( 20%) ] Loss: 0.0345 top1= 98.7500
[E10B40 |  15744/60000 ( 26%) ] Loss: 0.0232 top1= 99.6875
[E10B50 |  19584/60000 ( 33%) ] Loss: 0.0087 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2314 top1= 93.0889


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.0209 top1= 60.9776


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1735 top1= 54.5673

Train epoch 11
[E11B0  |    384/60000 (  1%) ] Loss: 0.0072 top1=100.0000
[E11B10 |   4224/60000 (  7%) ] Loss: 0.0155 top1= 99.3750
[E11B20 |   8064/60000 ( 13%) ] Loss: 0.0245 top1= 99.3750
[E11B30 |  11904/60000 ( 20%) ] Loss: 0.0188 top1= 99.6875
[E11B40 |  15744/60000 ( 26%) ] Loss: 0.0069 top1=100.0000
[E11B50 |  19584/60000 ( 33%) ] Loss: 0.0192 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2154 top1= 93.5797


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.8900 top1= 61.2580


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5873 top1= 62.3698

Train epoch 12
[E12B0  |    384/60000 (  1%) ] Loss: 0.0062 top1=100.0000
[E12B10 |   4224/60000 (  7%) ] Loss: 0.0109 top1= 99.6875
[E12B20 |   8064/60000 ( 13%) ] Loss: 0.0043 top1=100.0000
[E12B30 |  11904/60000 ( 20%) ] Loss: 0.0082 top1= 99.6875
[E12B40 |  15744/60000 ( 26%) ] Loss: 0.0077 top1=100.0000
[E12B50 |  19584/60000 ( 33%) ] Loss: 0.0111 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2216 top1= 93.2492


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.5803 top1= 63.6719


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.8985 top1= 59.7356

Train epoch 13
[E13B0  |    384/60000 (  1%) ] Loss: 0.0089 top1=100.0000
[E13B10 |   4224/60000 (  7%) ] Loss: 0.0050 top1=100.0000
[E13B20 |   8064/60000 ( 13%) ] Loss: 0.0043 top1=100.0000
[E13B30 |  11904/60000 ( 20%) ] Loss: 0.0041 top1=100.0000
[E13B40 |  15744/60000 ( 26%) ] Loss: 0.0026 top1=100.0000
[E13B50 |  19584/60000 ( 33%) ] Loss: 0.0049 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2350 top1= 93.1490


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1274 top1= 71.0737


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.8753 top1= 60.9776

Train epoch 14
[E14B0  |    384/60000 (  1%) ] Loss: 0.0037 top1=100.0000
[E14B10 |   4224/60000 (  7%) ] Loss: 0.0039 top1=100.0000
[E14B20 |   8064/60000 ( 13%) ] Loss: 0.0034 top1=100.0000
[E14B30 |  11904/60000 ( 20%) ] Loss: 0.0025 top1=100.0000
[E14B40 |  15744/60000 ( 26%) ] Loss: 0.0028 top1=100.0000
[E14B50 |  19584/60000 ( 33%) ] Loss: 0.0040 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2285 top1= 93.5597


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1853 top1= 70.6230


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.7607 top1= 61.7488

Train epoch 15
[E15B0  |    384/60000 (  1%) ] Loss: 0.0023 top1=100.0000
[E15B10 |   4224/60000 (  7%) ] Loss: 0.0024 top1=100.0000
[E15B20 |   8064/60000 ( 13%) ] Loss: 0.0029 top1=100.0000
[E15B30 |  11904/60000 ( 20%) ] Loss: 0.0044 top1=100.0000
[E15B40 |  15744/60000 ( 26%) ] Loss: 0.0025 top1=100.0000
[E15B50 |  19584/60000 ( 33%) ] Loss: 0.0027 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2262 top1= 93.4696


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1543 top1= 70.6831


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.7477 top1= 62.2596

Train epoch 16
[E16B0  |    384/60000 (  1%) ] Loss: 0.0019 top1=100.0000
[E16B10 |   4224/60000 (  7%) ] Loss: 0.0028 top1=100.0000
[E16B20 |   8064/60000 ( 13%) ] Loss: 0.0021 top1=100.0000
[E16B30 |  11904/60000 ( 20%) ] Loss: 0.0181 top1= 99.6875
[E16B40 |  15744/60000 ( 26%) ] Loss: 0.0018 top1=100.0000
[E16B50 |  19584/60000 ( 33%) ] Loss: 0.0019 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2220 top1= 93.8502


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1486 top1= 71.1438


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.7351 top1= 61.9291

Train epoch 17
[E17B0  |    384/60000 (  1%) ] Loss: 0.0016 top1=100.0000
[E17B10 |   4224/60000 (  7%) ] Loss: 0.0029 top1=100.0000
[E17B20 |   8064/60000 ( 13%) ] Loss: 0.0024 top1=100.0000
[E17B30 |  11904/60000 ( 20%) ] Loss: 0.0018 top1=100.0000
[E17B40 |  15744/60000 ( 26%) ] Loss: 0.0018 top1=100.0000
[E17B50 |  19584/60000 ( 33%) ] Loss: 0.0020 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2183 top1= 94.1106


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1473 top1= 71.3041


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5242 top1= 64.0224

Train epoch 18
[E18B0  |    384/60000 (  1%) ] Loss: 0.0016 top1=100.0000
[E18B10 |   4224/60000 (  7%) ] Loss: 0.0022 top1=100.0000
[E18B20 |   8064/60000 ( 13%) ] Loss: 0.0019 top1=100.0000
[E18B30 |  11904/60000 ( 20%) ] Loss: 0.0016 top1=100.0000
[E18B40 |  15744/60000 ( 26%) ] Loss: 0.0015 top1=100.0000
[E18B50 |  19584/60000 ( 33%) ] Loss: 0.0016 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2159 top1= 94.2508


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.2108 top1= 70.1723


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5531 top1= 63.2212

Train epoch 19
[E19B0  |    384/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E19B10 |   4224/60000 (  7%) ] Loss: 0.0017 top1=100.0000
[E19B20 |   8064/60000 ( 13%) ] Loss: 0.0016 top1=100.0000
[E19B30 |  11904/60000 ( 20%) ] Loss: 0.0014 top1=100.0000
[E19B40 |  15744/60000 ( 26%) ] Loss: 0.0014 top1=100.0000
[E19B50 |  19584/60000 ( 33%) ] Loss: 0.0014 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2172 top1= 94.2508


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1492 top1= 71.3542


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5116 top1= 63.9623

Train epoch 20
[E20B0  |    384/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E20B10 |   4224/60000 (  7%) ] Loss: 0.0014 top1=100.0000
[E20B20 |   8064/60000 ( 13%) ] Loss: 0.0015 top1=100.0000
[E20B30 |  11904/60000 ( 20%) ] Loss: 0.0014 top1=100.0000
[E20B40 |  15744/60000 ( 26%) ] Loss: 0.0011 top1=100.0000
[E20B50 |  19584/60000 ( 33%) ] Loss: 0.0012 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2271 top1= 93.8802


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.0884 top1= 60.5669


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6186 top1= 60.9575

Train epoch 21
[E21B0  |    384/60000 (  1%) ] Loss: 0.0018 top1=100.0000
[E21B10 |   4224/60000 (  7%) ] Loss: 0.0012 top1=100.0000
[E21B20 |   8064/60000 ( 13%) ] Loss: 0.0013 top1=100.0000
[E21B30 |  11904/60000 ( 20%) ] Loss: 0.0012 top1=100.0000
[E21B40 |  15744/60000 ( 26%) ] Loss: 0.0012 top1=100.0000
[E21B50 |  19584/60000 ( 33%) ] Loss: 0.0013 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2234 top1= 94.2408


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1312 top1= 71.5144


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6291 top1= 61.0176

Train epoch 22
[E22B0  |    384/60000 (  1%) ] Loss: 0.0013 top1=100.0000
[E22B10 |   4224/60000 (  7%) ] Loss: 0.0012 top1=100.0000
[E22B20 |   8064/60000 ( 13%) ] Loss: 0.0011 top1=100.0000
[E22B30 |  11904/60000 ( 20%) ] Loss: 0.0012 top1=100.0000
[E22B40 |  15744/60000 ( 26%) ] Loss: 0.0012 top1=100.0000
[E22B50 |  19584/60000 ( 33%) ] Loss: 0.0014 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2203 top1= 94.2909


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1411 top1= 71.3241


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5330 top1= 63.0609

Train epoch 23
[E23B0  |    384/60000 (  1%) ] Loss: 0.0012 top1=100.0000
[E23B10 |   4224/60000 (  7%) ] Loss: 0.0010 top1=100.0000
[E23B20 |   8064/60000 ( 13%) ] Loss: 0.0013 top1=100.0000
[E23B30 |  11904/60000 ( 20%) ] Loss: 0.0011 top1=100.0000
[E23B40 |  15744/60000 ( 26%) ] Loss: 0.0009 top1=100.0000
[E23B50 |  19584/60000 ( 33%) ] Loss: 0.0012 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2249 top1= 94.2408


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1101 top1= 71.7448


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5320 top1= 63.6518

Train epoch 24
[E24B0  |    384/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E24B10 |   4224/60000 (  7%) ] Loss: 0.0010 top1=100.0000
[E24B20 |   8064/60000 ( 13%) ] Loss: 0.0011 top1=100.0000
[E24B30 |  11904/60000 ( 20%) ] Loss: 0.0010 top1=100.0000
[E24B40 |  15744/60000 ( 26%) ] Loss: 0.0008 top1=100.0000
[E24B50 |  19584/60000 ( 33%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2256 top1= 94.2808


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0639 top1= 72.9067


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5181 top1= 63.2412

Train epoch 25
[E25B0  |    384/60000 (  1%) ] Loss: 0.0012 top1=100.0000
[E25B10 |   4224/60000 (  7%) ] Loss: 0.0009 top1=100.0000
[E25B20 |   8064/60000 ( 13%) ] Loss: 0.0011 top1=100.0000
[E25B30 |  11904/60000 ( 20%) ] Loss: 0.0010 top1=100.0000
[E25B40 |  15744/60000 ( 26%) ] Loss: 0.0007 top1=100.0000
[E25B50 |  19584/60000 ( 33%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3107 top1= 91.9772


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.2336 top1= 69.8417


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.8628 top1= 50.0701

Train epoch 26
[E26B0  |    384/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E26B10 |   4224/60000 (  7%) ] Loss: 0.0011 top1=100.0000
[E26B20 |   8064/60000 ( 13%) ] Loss: 0.0010 top1=100.0000
[E26B30 |  11904/60000 ( 20%) ] Loss: 0.0011 top1=100.0000
[E26B40 |  15744/60000 ( 26%) ] Loss: 0.0007 top1=100.0000
[E26B50 |  19584/60000 ( 33%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2327 top1= 94.1807


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0887 top1= 72.3357


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.7012 top1= 59.0946

Train epoch 27
[E27B0  |    384/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E27B10 |   4224/60000 (  7%) ] Loss: 0.0009 top1=100.0000
[E27B20 |   8064/60000 ( 13%) ] Loss: 0.0009 top1=100.0000
[E27B30 |  11904/60000 ( 20%) ] Loss: 0.0009 top1=100.0000
[E27B40 |  15744/60000 ( 26%) ] Loss: 0.0007 top1=100.0000
[E27B50 |  19584/60000 ( 33%) ] Loss: 0.0008 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2288 top1= 94.2608


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0049 top1= 74.0585


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5210 top1= 62.2196

Train epoch 28
[E28B0  |    384/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E28B10 |   4224/60000 (  7%) ] Loss: 0.0008 top1=100.0000
[E28B20 |   8064/60000 ( 13%) ] Loss: 0.0009 top1=100.0000
[E28B30 |  11904/60000 ( 20%) ] Loss: 0.0008 top1=100.0000
[E28B40 |  15744/60000 ( 26%) ] Loss: 0.0007 top1=100.0000
[E28B50 |  19584/60000 ( 33%) ] Loss: 0.0008 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2297 top1= 94.3810


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0448 top1= 73.3273


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5255 top1= 62.5701

Train epoch 29
[E29B0  |    384/60000 (  1%) ] Loss: 0.0008 top1=100.0000
[E29B10 |   4224/60000 (  7%) ] Loss: 0.0008 top1=100.0000
[E29B20 |   8064/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E29B30 |  11904/60000 ( 20%) ] Loss: 0.0007 top1=100.0000
[E29B40 |  15744/60000 ( 26%) ] Loss: 0.0006 top1=100.0000
[E29B50 |  19584/60000 ( 33%) ] Loss: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2326 top1= 94.3610


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.9612 top1= 75.0501


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5108 top1= 62.7404

Train epoch 30
[E30B0  |    384/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E30B10 |   4224/60000 (  7%) ] Loss: 0.0007 top1=100.0000
[E30B20 |   8064/60000 ( 13%) ] Loss: 0.0007 top1=100.0000
[E30B30 |  11904/60000 ( 20%) ] Loss: 0.0007 top1=100.0000
[E30B40 |  15744/60000 ( 26%) ] Loss: 0.0006 top1=100.0000
[E30B50 |  19584/60000 ( 33%) ] Loss: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2335 top1= 94.3409


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.9407 top1= 75.5008


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.4983 top1= 62.8005

