
=== 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 0x7f08ca3e8b80>

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: 1.0087 top1= 64.3750
[E 1B20 |   8064/60000 ( 13%) ] Loss: 0.2656 top1= 91.8750
[E 1B30 |  11904/60000 ( 20%) ] Loss: 0.4698 top1= 85.3125
[E 1B40 |  15744/60000 ( 26%) ] Loss: 0.2731 top1= 90.6250
[E 1B50 |  19584/60000 ( 33%) ] Loss: 0.1854 top1= 93.7500

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.7162 top1= 83.7640


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.1040 top1= 49.8798


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.5789 top1= 45.6230

Train epoch 2
[E 2B0  |    384/60000 (  1%) ] Loss: 0.1750 top1= 95.0000
[E 2B10 |   4224/60000 (  7%) ] Loss: 0.1651 top1= 95.0000
[E 2B20 |   8064/60000 ( 13%) ] Loss: 0.1248 top1= 96.2500
[E 2B30 |  11904/60000 ( 20%) ] Loss: 0.1512 top1= 95.3125
[E 2B40 |  15744/60000 ( 26%) ] Loss: 0.1351 top1= 95.3125
[E 2B50 |  19584/60000 ( 33%) ] Loss: 0.0823 top1= 97.5000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5973 top1= 85.7472


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=3.8485 top1= 50.3606


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.5135 top1= 46.1338

Train epoch 3
[E 3B0  |    384/60000 (  1%) ] Loss: 0.0960 top1= 96.8750
[E 3B10 |   4224/60000 (  7%) ] Loss: 0.0923 top1= 96.2500
[E 3B20 |   8064/60000 ( 13%) ] Loss: 0.0717 top1= 98.7500
[E 3B30 |  11904/60000 ( 20%) ] Loss: 0.1103 top1= 95.9375
[E 3B40 |  15744/60000 ( 26%) ] Loss: 0.0767 top1= 97.1875
[E 3B50 |  19584/60000 ( 33%) ] Loss: 0.0474 top1= 98.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4983 top1= 86.9091


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=3.8751 top1= 50.5108


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.7544 top1= 46.2640

Train epoch 4
[E 4B0  |    384/60000 (  1%) ] Loss: 0.0552 top1= 98.7500
[E 4B10 |   4224/60000 (  7%) ] Loss: 0.0494 top1= 98.1250
[E 4B20 |   8064/60000 ( 13%) ] Loss: 0.0311 top1= 99.3750
[E 4B30 |  11904/60000 ( 20%) ] Loss: 0.0663 top1= 97.8125
[E 4B40 |  15744/60000 ( 26%) ] Loss: 0.0394 top1= 99.0625
[E 4B50 |  19584/60000 ( 33%) ] Loss: 0.0233 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4284 top1= 88.2111


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.1504 top1= 50.5909


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.9047 top1= 46.4944

Train epoch 5
[E 5B0  |    384/60000 (  1%) ] Loss: 0.0327 top1= 99.0625
[E 5B10 |   4224/60000 (  7%) ] Loss: 0.0358 top1= 98.7500
[E 5B20 |   8064/60000 ( 13%) ] Loss: 0.0179 top1= 99.6875
[E 5B30 |  11904/60000 ( 20%) ] Loss: 0.0269 top1= 99.0625
[E 5B40 |  15744/60000 ( 26%) ] Loss: 0.0218 top1=100.0000
[E 5B50 |  19584/60000 ( 33%) ] Loss: 0.0160 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3573 top1= 89.9139


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.2916 top1= 50.5909


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.8873 top1= 47.1755

Train epoch 6
[E 6B0  |    384/60000 (  1%) ] Loss: 0.0194 top1= 99.0625
[E 6B10 |   4224/60000 (  7%) ] Loss: 0.0235 top1= 99.3750
[E 6B20 |   8064/60000 ( 13%) ] Loss: 0.0105 top1=100.0000
[E 6B30 |  11904/60000 ( 20%) ] Loss: 0.0168 top1= 99.6875
[E 6B40 |  15744/60000 ( 26%) ] Loss: 0.0186 top1= 99.6875
[E 6B50 |  19584/60000 ( 33%) ] Loss: 0.0150 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3295 top1= 90.3145


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.2539 top1= 50.6110


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.8374 top1= 47.1655

Train epoch 7
[E 7B0  |    384/60000 (  1%) ] Loss: 0.0094 top1= 99.6875
[E 7B10 |   4224/60000 (  7%) ] Loss: 0.0147 top1= 99.6875
[E 7B20 |   8064/60000 ( 13%) ] Loss: 0.0053 top1=100.0000
[E 7B30 |  11904/60000 ( 20%) ] Loss: 0.0185 top1= 99.6875
[E 7B40 |  15744/60000 ( 26%) ] Loss: 0.0164 top1= 99.6875
[E 7B50 |  19584/60000 ( 33%) ] Loss: 0.0195 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3364 top1= 89.3429


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.1091 top1= 50.4507


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.1401 top1= 46.9251

Train epoch 8
[E 8B0  |    384/60000 (  1%) ] Loss: 0.0109 top1= 99.6875
[E 8B10 |   4224/60000 (  7%) ] Loss: 0.0102 top1= 99.6875
[E 8B20 |   8064/60000 ( 13%) ] Loss: 0.0046 top1=100.0000
[E 8B30 |  11904/60000 ( 20%) ] Loss: 0.0122 top1= 99.3750
[E 8B40 |  15744/60000 ( 26%) ] Loss: 0.0113 top1= 99.6875
[E 8B50 |  19584/60000 ( 33%) ] Loss: 0.0061 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3066 top1= 90.4347


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.0934 top1= 50.6510


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.0731 top1= 47.2356

Train epoch 9
[E 9B0  |    384/60000 (  1%) ] Loss: 0.0065 top1=100.0000
[E 9B10 |   4224/60000 (  7%) ] Loss: 0.0162 top1= 99.3750
[E 9B20 |   8064/60000 ( 13%) ] Loss: 0.0065 top1=100.0000
[E 9B30 |  11904/60000 ( 20%) ] Loss: 0.0139 top1= 99.6875
[E 9B40 |  15744/60000 ( 26%) ] Loss: 0.0055 top1=100.0000
[E 9B50 |  19584/60000 ( 33%) ] Loss: 0.0071 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2889 top1= 91.6166


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.1644 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.1992 top1= 47.3157

Train epoch 10
[E10B0  |    384/60000 (  1%) ] Loss: 0.0052 top1=100.0000
[E10B10 |   4224/60000 (  7%) ] Loss: 0.0035 top1=100.0000
[E10B20 |   8064/60000 ( 13%) ] Loss: 0.0035 top1=100.0000
[E10B30 |  11904/60000 ( 20%) ] Loss: 0.0045 top1= 99.6875
[E10B40 |  15744/60000 ( 26%) ] Loss: 0.0029 top1=100.0000
[E10B50 |  19584/60000 ( 33%) ] Loss: 0.0013 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2841 top1= 91.2861


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.4297 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.0144 top1= 47.3558

Train epoch 11
[E11B0  |    384/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E11B10 |   4224/60000 (  7%) ] Loss: 0.0023 top1=100.0000
[E11B20 |   8064/60000 ( 13%) ] Loss: 0.0013 top1=100.0000
[E11B30 |  11904/60000 ( 20%) ] Loss: 0.0035 top1=100.0000
[E11B40 |  15744/60000 ( 26%) ] Loss: 0.0029 top1=100.0000
[E11B50 |  19584/60000 ( 33%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2819 top1= 91.3562


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.5898 top1= 50.6711


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.9678 top1= 47.3458

Train epoch 12
[E12B0  |    384/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E12B10 |   4224/60000 (  7%) ] Loss: 0.0008 top1=100.0000
[E12B20 |   8064/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E12B30 |  11904/60000 ( 20%) ] Loss: 0.0018 top1=100.0000
[E12B40 |  15744/60000 ( 26%) ] Loss: 0.0009 top1=100.0000
[E12B50 |  19584/60000 ( 33%) ] Loss: 0.0008 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2903 top1= 90.8754


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.8968 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.0775 top1= 47.3057

Train epoch 13
[E13B0  |    384/60000 (  1%) ] Loss: 0.0008 top1=100.0000
[E13B10 |   4224/60000 (  7%) ] Loss: 0.0008 top1=100.0000
[E13B20 |   8064/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E13B30 |  11904/60000 ( 20%) ] Loss: 0.0012 top1=100.0000
[E13B40 |  15744/60000 ( 26%) ] Loss: 0.0006 top1=100.0000
[E13B50 |  19584/60000 ( 33%) ] Loss: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2782 top1= 91.1258


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.0843 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.3993 top1= 47.4860

Train epoch 14
[E14B0  |    384/60000 (  1%) ] Loss: 0.0006 top1=100.0000
[E14B10 |   4224/60000 (  7%) ] Loss: 0.0005 top1=100.0000
[E14B20 |   8064/60000 ( 13%) ] Loss: 0.0006 top1=100.0000
[E14B30 |  11904/60000 ( 20%) ] Loss: 0.0009 top1=100.0000
[E14B40 |  15744/60000 ( 26%) ] Loss: 0.0005 top1=100.0000
[E14B50 |  19584/60000 ( 33%) ] Loss: 0.0005 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2753 top1= 91.2460


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.2082 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.5906 top1= 47.4960

Train epoch 15
[E15B0  |    384/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E15B10 |   4224/60000 (  7%) ] Loss: 0.0005 top1=100.0000
[E15B20 |   8064/60000 ( 13%) ] Loss: 0.0005 top1=100.0000
[E15B30 |  11904/60000 ( 20%) ] Loss: 0.0008 top1=100.0000
[E15B40 |  15744/60000 ( 26%) ] Loss: 0.0005 top1=100.0000
[E15B50 |  19584/60000 ( 33%) ] Loss: 0.0004 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2735 top1= 91.2760


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.3052 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.7365 top1= 47.4860

Train epoch 16
[E16B0  |    384/60000 (  1%) ] Loss: 0.0004 top1=100.0000
[E16B10 |   4224/60000 (  7%) ] Loss: 0.0004 top1=100.0000
[E16B20 |   8064/60000 ( 13%) ] Loss: 0.0004 top1=100.0000
[E16B30 |  11904/60000 ( 20%) ] Loss: 0.0007 top1=100.0000
[E16B40 |  15744/60000 ( 26%) ] Loss: 0.0005 top1=100.0000
[E16B50 |  19584/60000 ( 33%) ] Loss: 0.0004 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2729 top1= 91.2961


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.3913 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.8425 top1= 47.4760

Train epoch 17
[E17B0  |    384/60000 (  1%) ] Loss: 0.0004 top1=100.0000
[E17B10 |   4224/60000 (  7%) ] Loss: 0.0003 top1=100.0000
[E17B20 |   8064/60000 ( 13%) ] Loss: 0.0004 top1=100.0000
[E17B30 |  11904/60000 ( 20%) ] Loss: 0.0006 top1=100.0000
[E17B40 |  15744/60000 ( 26%) ] Loss: 0.0004 top1=100.0000
[E17B50 |  19584/60000 ( 33%) ] Loss: 0.0003 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2727 top1= 91.3061


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.4682 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.9278 top1= 47.4860

Train epoch 18
[E18B0  |    384/60000 (  1%) ] Loss: 0.0003 top1=100.0000
[E18B10 |   4224/60000 (  7%) ] Loss: 0.0003 top1=100.0000
[E18B20 |   8064/60000 ( 13%) ] Loss: 0.0003 top1=100.0000
[E18B30 |  11904/60000 ( 20%) ] Loss: 0.0005 top1=100.0000
[E18B40 |  15744/60000 ( 26%) ] Loss: 0.0004 top1=100.0000
[E18B50 |  19584/60000 ( 33%) ] Loss: 0.0003 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2726 top1= 91.2660


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.5358 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.9982 top1= 47.4860

Train epoch 19
[E19B0  |    384/60000 (  1%) ] Loss: 0.0003 top1=100.0000
[E19B10 |   4224/60000 (  7%) ] Loss: 0.0003 top1=100.0000
[E19B20 |   8064/60000 ( 13%) ] Loss: 0.0003 top1=100.0000
[E19B30 |  11904/60000 ( 20%) ] Loss: 0.0004 top1=100.0000
[E19B40 |  15744/60000 ( 26%) ] Loss: 0.0004 top1=100.0000
[E19B50 |  19584/60000 ( 33%) ] Loss: 0.0003 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2727 top1= 91.3061


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.5966 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.0612 top1= 47.4860

Train epoch 20
[E20B0  |    384/60000 (  1%) ] Loss: 0.0003 top1=100.0000
[E20B10 |   4224/60000 (  7%) ] Loss: 0.0003 top1=100.0000
[E20B20 |   8064/60000 ( 13%) ] Loss: 0.0003 top1=100.0000
[E20B30 |  11904/60000 ( 20%) ] Loss: 0.0004 top1=100.0000
[E20B40 |  15744/60000 ( 26%) ] Loss: 0.0003 top1=100.0000
[E20B50 |  19584/60000 ( 33%) ] Loss: 0.0003 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2729 top1= 91.2861


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.6534 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.1144 top1= 47.4760

Train epoch 21
[E21B0  |    384/60000 (  1%) ] Loss: 0.0002 top1=100.0000
[E21B10 |   4224/60000 (  7%) ] Loss: 0.0002 top1=100.0000
[E21B20 |   8064/60000 ( 13%) ] Loss: 0.0002 top1=100.0000
[E21B30 |  11904/60000 ( 20%) ] Loss: 0.0004 top1=100.0000
[E21B40 |  15744/60000 ( 26%) ] Loss: 0.0003 top1=100.0000
[E21B50 |  19584/60000 ( 33%) ] Loss: 0.0003 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2731 top1= 91.2660


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.7051 top1= 50.7011


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.1659 top1= 47.4860

Train epoch 22
[E22B0  |    384/60000 (  1%) ] Loss: 0.0002 top1=100.0000
[E22B10 |   4224/60000 (  7%) ] Loss: 0.0002 top1=100.0000
[E22B20 |   8064/60000 ( 13%) ] Loss: 0.0002 top1=100.0000
[E22B30 |  11904/60000 ( 20%) ] Loss: 0.0003 top1=100.0000
[E22B40 |  15744/60000 ( 26%) ] Loss: 0.0003 top1=100.0000
[E22B50 |  19584/60000 ( 33%) ] Loss: 0.0002 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2733 top1= 91.2460


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.7557 top1= 50.7011


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.2138 top1= 47.5060

Train epoch 23
[E23B0  |    384/60000 (  1%) ] Loss: 0.0002 top1=100.0000
[E23B10 |   4224/60000 (  7%) ] Loss: 0.0002 top1=100.0000
[E23B20 |   8064/60000 ( 13%) ] Loss: 0.0002 top1=100.0000
[E23B30 |  11904/60000 ( 20%) ] Loss: 0.0003 top1=100.0000
[E23B40 |  15744/60000 ( 26%) ] Loss: 0.0003 top1=100.0000
[E23B50 |  19584/60000 ( 33%) ] Loss: 0.0002 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2736 top1= 91.2460


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.8001 top1= 50.7011


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.2563 top1= 47.5060

Train epoch 24
[E24B0  |    384/60000 (  1%) ] Loss: 0.0002 top1=100.0000
[E24B10 |   4224/60000 (  7%) ] Loss: 0.0002 top1=100.0000
[E24B20 |   8064/60000 ( 13%) ] Loss: 0.0002 top1=100.0000
[E24B30 |  11904/60000 ( 20%) ] Loss: 0.0003 top1=100.0000
[E24B40 |  15744/60000 ( 26%) ] Loss: 0.0002 top1=100.0000
[E24B50 |  19584/60000 ( 33%) ] Loss: 0.0002 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2737 top1= 91.2260


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.8423 top1= 50.7011


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.2980 top1= 47.4960

Train epoch 25
[E25B0  |    384/60000 (  1%) ] Loss: 0.0002 top1=100.0000
[E25B10 |   4224/60000 (  7%) ] Loss: 0.0002 top1=100.0000
[E25B20 |   8064/60000 ( 13%) ] Loss: 0.0002 top1=100.0000
[E25B30 |  11904/60000 ( 20%) ] Loss: 0.0003 top1=100.0000
[E25B40 |  15744/60000 ( 26%) ] Loss: 0.0002 top1=100.0000
[E25B50 |  19584/60000 ( 33%) ] Loss: 0.0002 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2740 top1= 91.2159


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.8833 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.3365 top1= 47.4960

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

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2741 top1= 91.1959


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9197 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.3723 top1= 47.4860

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: 0.0002 top1=100.0000
[E27B40 |  15744/60000 ( 26%) ] Loss: 0.0002 top1=100.0000
[E27B50 |  19584/60000 ( 33%) ] Loss: 0.0002 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2743 top1= 91.1759


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9554 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4082 top1= 47.4960

Train epoch 28
[E28B0  |    384/60000 (  1%) ] Loss: 0.0001 top1=100.0000
[E28B10 |   4224/60000 (  7%) ] Loss: 0.0001 top1=100.0000
[E28B20 |   8064/60000 ( 13%) ] Loss: 0.0002 top1=100.0000
[E28B30 |  11904/60000 ( 20%) ] Loss: 0.0002 top1=100.0000
[E28B40 |  15744/60000 ( 26%) ] Loss: 0.0002 top1=100.0000
[E28B50 |  19584/60000 ( 33%) ] Loss: 0.0002 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2745 top1= 91.1659


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9899 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4412 top1= 47.4960

Train epoch 29
[E29B0  |    384/60000 (  1%) ] Loss: 0.0001 top1=100.0000
[E29B10 |   4224/60000 (  7%) ] Loss: 0.0001 top1=100.0000
[E29B20 |   8064/60000 ( 13%) ] Loss: 0.0001 top1=100.0000
[E29B30 |  11904/60000 ( 20%) ] Loss: 0.0002 top1=100.0000
[E29B40 |  15744/60000 ( 26%) ] Loss: 0.0002 top1=100.0000
[E29B50 |  19584/60000 ( 33%) ] Loss: 0.0002 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2747 top1= 91.1558


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.0216 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4730 top1= 47.4960

Train epoch 30
[E30B0  |    384/60000 (  1%) ] Loss: 0.0001 top1=100.0000
[E30B10 |   4224/60000 (  7%) ] Loss: 0.0001 top1=100.0000
[E30B20 |   8064/60000 ( 13%) ] Loss: 0.0001 top1=100.0000
[E30B30 |  11904/60000 ( 20%) ] Loss: 0.0002 top1=100.0000
[E30B40 |  15744/60000 ( 26%) ] Loss: 0.0002 top1=100.0000
[E30B50 |  19584/60000 ( 33%) ] Loss: 0.0001 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2750 top1= 91.1258


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.0526 top1= 50.7011


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.5027 top1= 47.4960

