
=== 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 0x7f4d33e447c0>

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: 0.2687 top1= 91.2500
[E 1B30 |  11904/60000 ( 20%) ] Loss: 0.4264 top1= 87.5000
[E 1B40 |  15744/60000 ( 26%) ] Loss: 0.2638 top1= 90.3125
[E 1B50 |  19584/60000 ( 33%) ] Loss: 0.1785 top1= 94.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5005 top1= 86.7989


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.4571 top1= 50.5008


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1965 top1= 46.4343

Train epoch 2
[E 2B0  |    384/60000 (  1%) ] Loss: 0.1803 top1= 95.6250
[E 2B10 |   4224/60000 (  7%) ] Loss: 0.1969 top1= 94.0625
[E 2B20 |   8064/60000 ( 13%) ] Loss: 0.1511 top1= 95.6250
[E 2B30 |  11904/60000 ( 20%) ] Loss: 0.2317 top1= 93.4375
[E 2B40 |  15744/60000 ( 26%) ] Loss: 0.1651 top1= 93.1250
[E 2B50 |  19584/60000 ( 33%) ] Loss: 0.1082 top1= 96.5625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3726 top1= 89.2328


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.1561 top1= 54.0565


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.0972 top1= 48.3974

Train epoch 3
[E 3B0  |    384/60000 (  1%) ] Loss: 0.1229 top1= 95.9375
[E 3B10 |   4224/60000 (  7%) ] Loss: 0.1308 top1= 95.0000
[E 3B20 |   8064/60000 ( 13%) ] Loss: 0.0955 top1= 97.1875
[E 3B30 |  11904/60000 ( 20%) ] Loss: 0.1371 top1= 96.2500
[E 3B40 |  15744/60000 ( 26%) ] Loss: 0.1123 top1= 97.5000
[E 3B50 |  19584/60000 ( 33%) ] Loss: 0.0665 top1= 98.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3342 top1= 89.3329


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.1703 top1= 55.9595


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1191 top1= 49.3189

Train epoch 4
[E 4B0  |    384/60000 (  1%) ] Loss: 0.0886 top1= 97.5000
[E 4B10 |   4224/60000 (  7%) ] Loss: 0.0984 top1= 96.8750
[E 4B20 |   8064/60000 ( 13%) ] Loss: 0.0670 top1= 98.4375
[E 4B30 |  11904/60000 ( 20%) ] Loss: 0.0882 top1= 97.1875
[E 4B40 |  15744/60000 ( 26%) ] Loss: 0.0828 top1= 97.8125
[E 4B50 |  19584/60000 ( 33%) ] Loss: 0.0626 top1= 98.7500

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2865 top1= 90.9756


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.2195 top1= 56.1098


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.0322 top1= 51.4022

Train epoch 5
[E 5B0  |    384/60000 (  1%) ] Loss: 0.0480 top1= 99.0625
[E 5B10 |   4224/60000 (  7%) ] Loss: 0.0682 top1= 97.8125
[E 5B20 |   8064/60000 ( 13%) ] Loss: 0.0395 top1= 99.6875
[E 5B30 |  11904/60000 ( 20%) ] Loss: 0.0734 top1= 98.7500
[E 5B40 |  15744/60000 ( 26%) ] Loss: 0.0649 top1= 98.4375
[E 5B50 |  19584/60000 ( 33%) ] Loss: 0.0451 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2593 top1= 91.9271


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.1639 top1= 57.3718


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.8981 top1= 54.4271

Train epoch 6
[E 6B0  |    384/60000 (  1%) ] Loss: 0.0363 top1= 99.3750
[E 6B10 |   4224/60000 (  7%) ] Loss: 0.0356 top1= 98.7500
[E 6B20 |   8064/60000 ( 13%) ] Loss: 0.0331 top1= 99.3750
[E 6B30 |  11904/60000 ( 20%) ] Loss: 0.0479 top1= 99.0625
[E 6B40 |  15744/60000 ( 26%) ] Loss: 0.0490 top1= 99.0625
[E 6B50 |  19584/60000 ( 33%) ] Loss: 0.0339 top1= 98.7500

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2641 top1= 91.4764


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.8514 top1= 59.5954


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1539 top1= 53.5958

Train epoch 7
[E 7B0  |    384/60000 (  1%) ] Loss: 0.0167 top1= 99.6875
[E 7B10 |   4224/60000 (  7%) ] Loss: 0.0317 top1= 99.0625
[E 7B20 |   8064/60000 ( 13%) ] Loss: 0.0267 top1= 99.3750
[E 7B30 |  11904/60000 ( 20%) ] Loss: 0.0324 top1= 99.3750
[E 7B40 |  15744/60000 ( 26%) ] Loss: 0.0327 top1= 99.6875
[E 7B50 |  19584/60000 ( 33%) ] Loss: 0.0203 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2471 top1= 92.0272


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.9410 top1= 59.8558


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.3701 top1= 53.4155

Train epoch 8
[E 8B0  |    384/60000 (  1%) ] Loss: 0.0194 top1= 99.3750
[E 8B10 |   4224/60000 (  7%) ] Loss: 0.0536 top1= 98.1250
[E 8B20 |   8064/60000 ( 13%) ] Loss: 0.0144 top1=100.0000
[E 8B30 |  11904/60000 ( 20%) ] Loss: 0.0320 top1= 99.0625
[E 8B40 |  15744/60000 ( 26%) ] Loss: 0.0282 top1= 99.0625
[E 8B50 |  19584/60000 ( 33%) ] Loss: 0.0247 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2286 top1= 92.9087


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.0194 top1= 60.9375


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1416 top1= 55.9295

Train epoch 9
[E 9B0  |    384/60000 (  1%) ] Loss: 0.0169 top1= 99.6875
[E 9B10 |   4224/60000 (  7%) ] Loss: 0.0282 top1= 99.0625
[E 9B20 |   8064/60000 ( 13%) ] Loss: 0.0339 top1= 99.0625
[E 9B30 |  11904/60000 ( 20%) ] Loss: 0.0222 top1= 99.0625
[E 9B40 |  15744/60000 ( 26%) ] Loss: 0.0160 top1=100.0000
[E 9B50 |  19584/60000 ( 33%) ] Loss: 0.0125 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2337 top1= 92.7985


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.0428 top1= 60.3766


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.9980 top1= 55.9896

Train epoch 10
[E10B0  |    384/60000 (  1%) ] Loss: 0.0249 top1= 99.6875
[E10B10 |   4224/60000 (  7%) ] Loss: 0.0174 top1= 99.3750
[E10B20 |   8064/60000 ( 13%) ] Loss: 0.0337 top1= 98.7500
[E10B30 |  11904/60000 ( 20%) ] Loss: 0.0136 top1= 99.6875
[E10B40 |  15744/60000 ( 26%) ] Loss: 0.0206 top1= 99.3750
[E10B50 |  19584/60000 ( 33%) ] Loss: 0.0166 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2247 top1= 93.1490


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.1467 top1= 60.0561


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.0494 top1= 56.0998

Train epoch 11
[E11B0  |    384/60000 (  1%) ] Loss: 0.0101 top1=100.0000
[E11B10 |   4224/60000 (  7%) ] Loss: 0.0140 top1= 99.3750
[E11B20 |   8064/60000 ( 13%) ] Loss: 0.0081 top1=100.0000
[E11B30 |  11904/60000 ( 20%) ] Loss: 0.0186 top1= 99.3750
[E11B40 |  15744/60000 ( 26%) ] Loss: 0.0183 top1= 99.6875
[E11B50 |  19584/60000 ( 33%) ] Loss: 0.0112 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2355 top1= 92.7183


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.1643 top1= 61.0677


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.2082 top1= 53.5757

Train epoch 12
[E12B0  |    384/60000 (  1%) ] Loss: 0.0077 top1=100.0000
[E12B10 |   4224/60000 (  7%) ] Loss: 0.0050 top1=100.0000
[E12B20 |   8064/60000 ( 13%) ] Loss: 0.0279 top1= 98.4375
[E12B30 |  11904/60000 ( 20%) ] Loss: 0.0152 top1= 99.6875
[E12B40 |  15744/60000 ( 26%) ] Loss: 0.0075 top1=100.0000
[E12B50 |  19584/60000 ( 33%) ] Loss: 0.0303 top1= 98.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2114 top1= 93.6599


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.4056 top1= 67.2376


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6682 top1= 61.3181

Train epoch 13
[E13B0  |    384/60000 (  1%) ] Loss: 0.0046 top1=100.0000
[E13B10 |   4224/60000 (  7%) ] Loss: 0.0049 top1=100.0000
[E13B20 |   8064/60000 ( 13%) ] Loss: 0.0042 top1=100.0000
[E13B30 |  11904/60000 ( 20%) ] Loss: 0.0094 top1= 99.6875
[E13B40 |  15744/60000 ( 26%) ] Loss: 0.0033 top1=100.0000
[E13B50 |  19584/60000 ( 33%) ] Loss: 0.0040 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2161 top1= 93.4996


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.6616 top1= 64.1326


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6688 top1= 62.2796

Train epoch 14
[E14B0  |    384/60000 (  1%) ] Loss: 0.0053 top1=100.0000
[E14B10 |   4224/60000 (  7%) ] Loss: 0.0048 top1=100.0000
[E14B20 |   8064/60000 ( 13%) ] Loss: 0.0028 top1=100.0000
[E14B30 |  11904/60000 ( 20%) ] Loss: 0.0030 top1=100.0000
[E14B40 |  15744/60000 ( 26%) ] Loss: 0.0029 top1=100.0000
[E14B50 |  19584/60000 ( 33%) ] Loss: 0.0038 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2100 top1= 93.8401


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.3386 top1= 68.7200


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6046 top1= 63.0809

Train epoch 15
[E15B0  |    384/60000 (  1%) ] Loss: 0.0038 top1=100.0000
[E15B10 |   4224/60000 (  7%) ] Loss: 0.0028 top1=100.0000
[E15B20 |   8064/60000 ( 13%) ] Loss: 0.0030 top1=100.0000
[E15B30 |  11904/60000 ( 20%) ] Loss: 0.0024 top1=100.0000
[E15B40 |  15744/60000 ( 26%) ] Loss: 0.0021 top1=100.0000
[E15B50 |  19584/60000 ( 33%) ] Loss: 0.0022 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2154 top1= 93.9403


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1429 top1= 71.2640


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5591 top1= 63.7921

Train epoch 16
[E16B0  |    384/60000 (  1%) ] Loss: 0.0022 top1=100.0000
[E16B10 |   4224/60000 (  7%) ] Loss: 0.0021 top1=100.0000
[E16B20 |   8064/60000 ( 13%) ] Loss: 0.0026 top1=100.0000
[E16B30 |  11904/60000 ( 20%) ] Loss: 0.0020 top1=100.0000
[E16B40 |  15744/60000 ( 26%) ] Loss: 0.0017 top1=100.0000
[E16B50 |  19584/60000 ( 33%) ] Loss: 0.0019 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2158 top1= 94.0004


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1163 top1= 71.8850


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5696 top1= 63.2412

Train epoch 17
[E17B0  |    384/60000 (  1%) ] Loss: 0.0016 top1=100.0000
[E17B10 |   4224/60000 (  7%) ] Loss: 0.0020 top1=100.0000
[E17B20 |   8064/60000 ( 13%) ] Loss: 0.0021 top1=100.0000
[E17B30 |  11904/60000 ( 20%) ] Loss: 0.0019 top1=100.0000
[E17B40 |  15744/60000 ( 26%) ] Loss: 0.0016 top1=100.0000
[E17B50 |  19584/60000 ( 33%) ] Loss: 0.0016 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2169 top1= 94.1006


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1312 top1= 71.8750


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5561 top1= 63.4215

Train epoch 18
[E18B0  |    384/60000 (  1%) ] Loss: 0.0016 top1=100.0000
[E18B10 |   4224/60000 (  7%) ] Loss: 0.0021 top1=100.0000
[E18B20 |   8064/60000 ( 13%) ] Loss: 0.0019 top1=100.0000
[E18B30 |  11904/60000 ( 20%) ] Loss: 0.0015 top1=100.0000
[E18B40 |  15744/60000 ( 26%) ] Loss: 0.0014 top1=100.0000
[E18B50 |  19584/60000 ( 33%) ] Loss: 0.0015 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2184 top1= 94.0505


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0923 top1= 72.6963


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5692 top1= 62.9607

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: 0.0015 top1=100.0000
[E19B40 |  15744/60000 ( 26%) ] Loss: 0.0012 top1=100.0000
[E19B50 |  19584/60000 ( 33%) ] Loss: 0.0012 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2198 top1= 94.0905


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0863 top1= 72.8466


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5712 top1= 62.6302

Train epoch 20
[E20B0  |    384/60000 (  1%) ] Loss: 0.0014 top1=100.0000
[E20B10 |   4224/60000 (  7%) ] Loss: 0.0015 top1=100.0000
[E20B20 |   8064/60000 ( 13%) ] Loss: 0.0014 top1=100.0000
[E20B30 |  11904/60000 ( 20%) ] Loss: 0.0013 top1=100.0000
[E20B40 |  15744/60000 ( 26%) ] Loss: 0.0011 top1=100.0000
[E20B50 |  19584/60000 ( 33%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2166 top1= 94.1707


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1389 top1= 71.7849


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5259 top1= 63.1811

Train epoch 21
[E21B0  |    384/60000 (  1%) ] Loss: 0.0013 top1=100.0000
[E21B10 |   4224/60000 (  7%) ] Loss: 0.0012 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: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2189 top1= 94.1306


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0557 top1= 73.5877


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.4847 top1= 63.1911

Train epoch 22
[E22B0  |    384/60000 (  1%) ] Loss: 0.0013 top1=100.0000
[E22B10 |   4224/60000 (  7%) ] Loss: 0.0013 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=0.2251 top1= 94.0004


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.8714 top1= 62.5601


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5193 top1= 62.9207

Train epoch 23
[E23B0  |    384/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E23B10 |   4224/60000 (  7%) ] Loss: 0.0010 top1=100.0000
[E23B20 |   8064/60000 ( 13%) ] Loss: 0.0011 top1=100.0000
[E23B30 |  11904/60000 ( 20%) ] Loss: 0.0013 top1=100.0000
[E23B40 |  15744/60000 ( 26%) ] Loss: 0.0009 top1=100.0000
[E23B50 |  19584/60000 ( 33%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3000 top1= 91.9571


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1374 top1= 72.2356


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.7131 top1= 50.4607

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: 0.0012 top1=100.0000
[E24B30 |  11904/60000 ( 20%) ] Loss: 0.0009 top1=100.0000
[E24B40 |  15744/60000 ( 26%) ] Loss: 0.0010 top1=100.0000
[E24B50 |  19584/60000 ( 33%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2419 top1= 93.7400


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0104 top1= 74.4091


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.7002 top1= 59.8057

Train epoch 25
[E25B0  |    384/60000 (  1%) ] Loss: 0.0012 top1=100.0000
[E25B10 |   4224/60000 (  7%) ] Loss: 0.0010 top1=100.0000
[E25B20 |   8064/60000 ( 13%) ] Loss: 0.0012 top1=100.0000
[E25B30 |  11904/60000 ( 20%) ] Loss: 0.0010 top1=100.0000
[E25B40 |  15744/60000 ( 26%) ] Loss: 0.0008 top1=100.0000
[E25B50 |  19584/60000 ( 33%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2305 top1= 94.2308


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0219 top1= 74.1787


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6410 top1= 60.7973

Train epoch 26
[E26B0  |    384/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E26B10 |   4224/60000 (  7%) ] Loss: 0.0010 top1=100.0000
[E26B20 |   8064/60000 ( 13%) ] Loss: 0.0010 top1=100.0000
[E26B30 |  11904/60000 ( 20%) ] Loss: 0.0010 top1=100.0000
[E26B40 |  15744/60000 ( 26%) ] Loss: 0.0007 top1=100.0000
[E26B50 |  19584/60000 ( 33%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2420 top1= 93.8802


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.8819 top1= 77.0032


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.7349 top1= 59.2949

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: 0.0010 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=0.2337 top1= 94.2107


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.8615 top1= 77.4239


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5428 top1= 62.0192

Train epoch 28
[E28B0  |    384/60000 (  1%) ] Loss: 0.0010 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: 0.0006 top1=100.0000
[E28B50 |  19584/60000 ( 33%) ] Loss: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2341 top1= 94.2508


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.8645 top1= 77.4139


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5355 top1= 62.1795

Train epoch 29
[E29B0  |    384/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E29B10 |   4224/60000 (  7%) ] Loss: 0.0008 top1=100.0000
[E29B20 |   8064/60000 ( 13%) ] Loss: 0.0009 top1=100.0000
[E29B30 |  11904/60000 ( 20%) ] Loss: 0.0008 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=0.2356 top1= 94.2508


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.8476 top1= 77.9347


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5198 top1= 62.3998

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: 0.0008 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=0.2396 top1= 94.1206


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.8266 top1= 78.3754


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5589 top1= 61.7688

