Namespace(batch=128, dataset='CIFAR10', epochs=50, k=4, lr=0.05, net='MyLeNetMatNormalNoceil', postfix='__k4_2', res_folder='res/benchmark_NoCeil/', resume=False, scheduler='cosine', stoch=False, warmup_ep=5, warmup_mul=0)
==> Preparing data..
==> Building model..
==> Training model..
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Epoch: 0
Acc : 36.29 / 46.76
Loss : 1.72 / 1.45
Time: 413.4330958928913
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Epoch: 5
Acc : 72.84 / 73.12
Loss : 0.78 / 0.77
Time: 2481.541083334014
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Epoch: 10
Acc : 80.54 / 77.11
Loss : 0.56 / 0.67
Time: 4550.451236174442
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Epoch: 15
Acc : 85.16 / 80.44
Loss : 0.43 / 0.57
Time: 6619.68952109199
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Epoch: 20
Acc : 88.79 / 81.69
Loss : 0.33 / 0.54
Time: 8689.100086900406
---------

Epoch: 25
Acc : 91.94 / 81.74
Loss : 0.25 / 0.58
Time: 10758.489818972535
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Epoch: 30
Acc : 94.65 / 82.18
Loss : 0.17 / 0.56
Time: 12827.756879460067
---------

Epoch: 35
Acc : 97.02 / 84.21
Loss : 0.11 / 0.51
Time: 14896.387511295266
---------

Epoch: 40
Acc : 98.82 / 84.45
Loss : 0.07 / 0.51
Time: 16964.967554398812
---------

Epoch: 45
Acc : 99.51 / 85.09
Loss : 0.05 / 0.51
Time: 19033.166706252843
---------
Best Acc : 85.09
Training time (min): 344.792250782003
Log :" res/benchmark_NoCeil/log/MyLeNetMatNormalNoceil-50epochs__k4_2.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatNormalNoceil-50epochs__k4_2 " saved !

real	345m2.760s
user	257m11.566s
sys	114m37.729s