
=== 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 0x7f6fbd2fc7c0>

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=0.2907 top1= 90.8654


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.3262 top1= 55.8193


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.0129 top1= 51.2220

Train epoch 5
[E 5B0  |    384/60000 (  1%) ] Loss: 0.0468 top1= 99.6875
[E 5B10 |   4224/60000 (  7%) ] Loss: 0.0653 top1= 98.1250
[E 5B20 |   8064/60000 ( 13%) ] Loss: 0.0532 top1= 98.4375
[E 5B30 |  11904/60000 ( 20%) ] Loss: 0.0753 top1= 98.7500
[E 5B40 |  15744/60000 ( 26%) ] Loss: 0.0590 top1= 98.4375
[E 5B50 |  19584/60000 ( 33%) ] Loss: 0.0572 top1= 98.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2691 top1= 91.4563


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.3820 top1= 55.7993


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.8945 top1= 54.7776

Train epoch 6
[E 6B0  |    384/60000 (  1%) ] Loss: 0.0376 top1= 99.3750
[E 6B10 |   4224/60000 (  7%) ] Loss: 0.0280 top1= 98.7500
[E 6B20 |   8064/60000 ( 13%) ] Loss: 0.0399 top1= 98.7500
[E 6B30 |  11904/60000 ( 20%) ] Loss: 0.0574 top1= 98.4375
[E 6B40 |  15744/60000 ( 26%) ] Loss: 0.0506 top1= 98.1250
[E 6B50 |  19584/60000 ( 33%) ] Loss: 0.0241 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2717 top1= 91.1859


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.9661 top1= 58.6038


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1650 top1= 53.1851

Train epoch 7
[E 7B0  |    384/60000 (  1%) ] Loss: 0.0192 top1= 99.6875
[E 7B10 |   4224/60000 (  7%) ] Loss: 0.0365 top1= 98.4375
[E 7B20 |   8064/60000 ( 13%) ] Loss: 0.0183 top1=100.0000
[E 7B30 |  11904/60000 ( 20%) ] Loss: 0.0328 top1= 99.0625
[E 7B40 |  15744/60000 ( 26%) ] Loss: 0.0424 top1= 99.0625
[E 7B50 |  19584/60000 ( 33%) ] Loss: 0.0220 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2479 top1= 92.1775


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.0195 top1= 59.2047


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.2156 top1= 54.3970

Train epoch 8
[E 8B0  |    384/60000 (  1%) ] Loss: 0.0207 top1= 99.3750
[E 8B10 |   4224/60000 (  7%) ] Loss: 0.0252 top1= 99.6875
[E 8B20 |   8064/60000 ( 13%) ] Loss: 0.0186 top1= 99.6875
[E 8B30 |  11904/60000 ( 20%) ] Loss: 0.0412 top1= 98.4375
[E 8B40 |  15744/60000 ( 26%) ] Loss: 0.0268 top1= 99.3750
[E 8B50 |  19584/60000 ( 33%) ] Loss: 0.0176 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2463 top1= 92.0974


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.0423 top1= 59.6955


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.2933 top1= 53.3554

Train epoch 9
[E 9B0  |    384/60000 (  1%) ] Loss: 0.0193 top1= 99.3750
[E 9B10 |   4224/60000 (  7%) ] Loss: 0.0339 top1= 98.4375
[E 9B20 |   8064/60000 ( 13%) ] Loss: 0.0480 top1= 99.0625
[E 9B30 |  11904/60000 ( 20%) ] Loss: 0.0273 top1= 99.6875
[E 9B40 |  15744/60000 ( 26%) ] Loss: 0.0149 top1=100.0000
[E 9B50 |  19584/60000 ( 33%) ] Loss: 0.0125 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2347 top1= 92.7784


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.2043 top1= 58.6238


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.0271 top1= 55.6891

Train epoch 10
[E10B0  |    384/60000 (  1%) ] Loss: 0.0096 top1=100.0000
[E10B10 |   4224/60000 (  7%) ] Loss: 0.0082 top1=100.0000
[E10B20 |   8064/60000 ( 13%) ] Loss: 0.0105 top1=100.0000
[E10B30 |  11904/60000 ( 20%) ] Loss: 0.0359 top1= 99.0625
[E10B40 |  15744/60000 ( 26%) ] Loss: 0.0480 top1= 98.7500
[E10B50 |  19584/60000 ( 33%) ] Loss: 0.0132 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2422 top1= 92.4079


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.8422 top1= 62.3097


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.4785 top1= 52.6042

Train epoch 11
[E11B0  |    384/60000 (  1%) ] Loss: 0.0145 top1= 99.6875
[E11B10 |   4224/60000 (  7%) ] Loss: 0.0077 top1=100.0000
[E11B20 |   8064/60000 ( 13%) ] Loss: 0.0085 top1=100.0000
[E11B30 |  11904/60000 ( 20%) ] Loss: 0.0156 top1= 99.6875
[E11B40 |  15744/60000 ( 26%) ] Loss: 0.0089 top1=100.0000
[E11B50 |  19584/60000 ( 33%) ] Loss: 0.0118 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2192 top1= 93.5096


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.7706 top1= 63.0108


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6474 top1= 61.1278

Train epoch 12
[E12B0  |    384/60000 (  1%) ] Loss: 0.0050 top1=100.0000
[E12B10 |   4224/60000 (  7%) ] Loss: 0.0110 top1=100.0000
[E12B20 |   8064/60000 ( 13%) ] Loss: 0.0077 top1=100.0000
[E12B30 |  11904/60000 ( 20%) ] Loss: 0.0147 top1=100.0000
[E12B40 |  15744/60000 ( 26%) ] Loss: 0.0042 top1=100.0000
[E12B50 |  19584/60000 ( 33%) ] Loss: 0.0049 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2341 top1= 92.9387


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.3343 top1= 66.2660


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.7051 top1= 62.1695

Train epoch 13
[E13B0  |    384/60000 (  1%) ] Loss: 0.0081 top1=100.0000
[E13B10 |   4224/60000 (  7%) ] Loss: 0.0115 top1= 99.6875
[E13B20 |   8064/60000 ( 13%) ] Loss: 0.0083 top1=100.0000
[E13B30 |  11904/60000 ( 20%) ] Loss: 0.0249 top1= 99.3750
[E13B40 |  15744/60000 ( 26%) ] Loss: 0.0101 top1=100.0000
[E13B50 |  19584/60000 ( 33%) ] Loss: 0.0064 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2382 top1= 92.8185


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.4828 top1= 65.5549


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.8520 top1= 61.5785

Train epoch 14
[E14B0  |    384/60000 (  1%) ] Loss: 0.0083 top1=100.0000
[E14B10 |   4224/60000 (  7%) ] Loss: 0.0181 top1= 99.6875
[E14B20 |   8064/60000 ( 13%) ] Loss: 0.0030 top1=100.0000
[E14B30 |  11904/60000 ( 20%) ] Loss: 0.0028 top1=100.0000
[E14B40 |  15744/60000 ( 26%) ] Loss: 0.0034 top1=100.0000
[E14B50 |  19584/60000 ( 33%) ] Loss: 0.0058 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2162 top1= 93.9002


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.5028 top1= 66.3962


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.8096 top1= 60.6270

Train epoch 15
[E15B0  |    384/60000 (  1%) ] Loss: 0.0026 top1=100.0000
[E15B10 |   4224/60000 (  7%) ] Loss: 0.0042 top1=100.0000
[E15B20 |   8064/60000 ( 13%) ] Loss: 0.0029 top1=100.0000
[E15B30 |  11904/60000 ( 20%) ] Loss: 0.0027 top1=100.0000
[E15B40 |  15744/60000 ( 26%) ] Loss: 0.0024 top1=100.0000
[E15B50 |  19584/60000 ( 33%) ] Loss: 0.0031 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2196 top1= 93.7600


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1895 top1= 70.2624


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.7426 top1= 61.8690

Train epoch 16
[E16B0  |    384/60000 (  1%) ] Loss: 0.0025 top1=100.0000
[E16B10 |   4224/60000 (  7%) ] Loss: 0.0030 top1=100.0000
[E16B20 |   8064/60000 ( 13%) ] Loss: 0.0023 top1=100.0000
[E16B30 |  11904/60000 ( 20%) ] Loss: 0.0024 top1=100.0000
[E16B40 |  15744/60000 ( 26%) ] Loss: 0.0018 top1=100.0000
[E16B50 |  19584/60000 ( 33%) ] Loss: 0.0024 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2265 top1= 93.6899


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1106 top1= 71.7248


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.8584 top1= 58.9343

Train epoch 17
[E17B0  |    384/60000 (  1%) ] Loss: 0.0018 top1=100.0000
[E17B10 |   4224/60000 (  7%) ] Loss: 0.0027 top1=100.0000
[E17B20 |   8064/60000 ( 13%) ] Loss: 0.0019 top1=100.0000
[E17B30 |  11904/60000 ( 20%) ] Loss: 0.0016 top1=100.0000
[E17B40 |  15744/60000 ( 26%) ] Loss: 0.0017 top1=100.0000
[E17B50 |  19584/60000 ( 33%) ] Loss: 0.0019 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2182 top1= 93.9804


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0962 top1= 71.9251


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5964 top1= 63.0709

Train epoch 18
[E18B0  |    384/60000 (  1%) ] Loss: 0.0016 top1=100.0000
[E18B10 |   4224/60000 (  7%) ] Loss: 0.0017 top1=100.0000
[E18B20 |   8064/60000 ( 13%) ] Loss: 0.0018 top1=100.0000
[E18B30 |  11904/60000 ( 20%) ] Loss: 0.0018 top1=100.0000
[E18B40 |  15744/60000 ( 26%) ] Loss: 0.0016 top1=100.0000
[E18B50 |  19584/60000 ( 33%) ] Loss: 0.0017 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2179 top1= 94.1106


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0954 top1= 71.8850


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5659 top1= 63.0609

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

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2172 top1= 94.1707


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0977 top1= 71.7147


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5350 top1= 63.3814

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: 0.0013 top1=100.0000
[E20B30 |  11904/60000 ( 20%) ] Loss: 0.0014 top1=100.0000
[E20B40 |  15744/60000 ( 26%) ] Loss: 0.0012 top1=100.0000
[E20B50 |  19584/60000 ( 33%) ] Loss: 0.0013 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2175 top1= 94.2107


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0942 top1= 71.9752


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5201 top1= 63.4816

Train epoch 21
[E21B0  |    384/60000 (  1%) ] Loss: 0.0014 top1=100.0000
[E21B10 |   4224/60000 (  7%) ] Loss: 0.0013 top1=100.0000
[E21B20 |   8064/60000 ( 13%) ] Loss: 0.0012 top1=100.0000
[E21B30 |  11904/60000 ( 20%) ] Loss: 0.0013 top1=100.0000
[E21B40 |  15744/60000 ( 26%) ] Loss: 0.0010 top1=100.0000
[E21B50 |  19584/60000 ( 33%) ] Loss: 0.0012 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2195 top1= 94.2107


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0570 top1= 72.9067


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5058 top1= 63.7320

Train epoch 22
[E22B0  |    384/60000 (  1%) ] Loss: 0.0013 top1=100.0000
[E22B10 |   4224/60000 (  7%) ] Loss: 0.0011 top1=100.0000
[E22B20 |   8064/60000 ( 13%) ] Loss: 0.0011 top1=100.0000
[E22B30 |  11904/60000 ( 20%) ] Loss: 0.0011 top1=100.0000
[E22B40 |  15744/60000 ( 26%) ] Loss: 0.0010 top1=100.0000
[E22B50 |  19584/60000 ( 33%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2203 top1= 94.2208


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0613 top1= 72.8265


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.4822 top1= 63.9123

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: 0.0010 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: 0.0017 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5749 top1= 82.7324


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.3977 top1= 67.6182


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.4953 top1= 48.1070

Train epoch 24
[E24B0  |    384/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E24B10 |   4224/60000 (  7%) ] Loss: 0.0019 top1=100.0000
[E24B20 |   8064/60000 ( 13%) ] Loss: 0.0010 top1=100.0000
[E24B30 |  11904/60000 ( 20%) ] Loss: 0.0011 top1=100.0000
[E24B40 |  15744/60000 ( 26%) ] Loss: 0.0009 top1=100.0000
[E24B50 |  19584/60000 ( 33%) ] Loss: 0.0020 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=1.1111 top1= 69.2608


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.9576 top1= 75.0501


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.7690 top1= 47.5962

Train epoch 25
[E25B0  |    384/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E25B10 |   4224/60000 (  7%) ] Loss: 0.0011 top1=100.0000
[E25B20 |   8064/60000 ( 13%) ] Loss: 0.0019 top1=100.0000
[E25B30 |  11904/60000 ( 20%) ] Loss: 0.0043 top1= 99.6875
[E25B40 |  15744/60000 ( 26%) ] Loss: 0.0016 top1=100.0000
[E25B50 |  19584/60000 ( 33%) ] Loss: 0.0025 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3361 top1= 91.0256


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.9765 top1= 73.9383


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.0049 top1= 50.8814

Train epoch 26
[E26B0  |    384/60000 (  1%) ] Loss: 0.0023 top1=100.0000
[E26B10 |   4224/60000 (  7%) ] Loss: 0.0027 top1=100.0000
[E26B20 |   8064/60000 ( 13%) ] Loss: 0.0009 top1=100.0000
[E26B30 |  11904/60000 ( 20%) ] Loss: 0.0010 top1=100.0000
[E26B40 |  15744/60000 ( 26%) ] Loss: 0.0009 top1=100.0000
[E26B50 |  19584/60000 ( 33%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2294 top1= 94.1306


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.3488 top1= 57.2316


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1996 top1= 56.7708

Train epoch 27
[E27B0  |    384/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E27B10 |   4224/60000 (  7%) ] Loss: 0.0010 top1=100.0000
[E27B20 |   8064/60000 ( 13%) ] Loss: 0.0013 top1=100.0000
[E27B30 |  11904/60000 ( 20%) ] Loss: 0.0013 top1=100.0000
[E27B40 |  15744/60000 ( 26%) ] Loss: 0.0010 top1=100.0000
[E27B50 |  19584/60000 ( 33%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2344 top1= 94.0505


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.9596 top1= 74.7196


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6399 top1= 61.1679

Train epoch 28
[E28B0  |    384/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E28B10 |   4224/60000 (  7%) ] Loss: 0.0009 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: 0.0008 top1=100.0000
[E28B50 |  19584/60000 ( 33%) ] Loss: 0.0008 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2333 top1= 94.1907


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.9359 top1= 75.4507


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5904 top1= 61.7588

Train epoch 29
[E29B0  |    384/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E29B10 |   4224/60000 (  7%) ] Loss: 0.0007 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: 0.0007 top1=100.0000
[E29B50 |  19584/60000 ( 33%) ] Loss: 0.0008 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2342 top1= 94.2408


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.8964 top1= 76.5525


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5355 top1= 62.2696

Train epoch 30
[E30B0  |    384/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E30B10 |   4224/60000 (  7%) ] Loss: 0.0006 top1=100.0000
[E30B20 |   8064/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E30B30 |  11904/60000 ( 20%) ] Loss: 0.0007 top1=100.0000
[E30B40 |  15744/60000 ( 26%) ] Loss: 0.0007 top1=100.0000
[E30B50 |  19584/60000 ( 33%) ] Loss: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2367 top1= 94.2007


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.8656 top1= 77.0132


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5330 top1= 62.2696

