Namespace(batch=128, dataset='CIFAR10', epochs=50, k=3, lr=0.05, net='MyLeNetMatNormalNoceil', postfix='__k3_1', 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 : 36.16 / 46.20
Loss : 1.72 / 1.48
Time: 247.73547955136746
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Epoch: 5
Acc : 72.15 / 72.22
Loss : 0.80 / 0.79
Time: 1486.8846261743456
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Epoch: 10
Acc : 80.06 / 77.68
Loss : 0.57 / 0.65
Time: 2726.5283604683354
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Epoch: 15
Acc : 84.93 / 78.28
Loss : 0.44 / 0.62
Time: 3966.002595074475
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Epoch: 20
Acc : 88.39 / 81.81
Loss : 0.34 / 0.53
Time: 5205.35461238306
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Epoch: 25
Acc : 91.51 / 82.47
Loss : 0.26 / 0.52
Time: 6445.20023989398
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Epoch: 30
Acc : 94.24 / 83.09
Loss : 0.18 / 0.51
Time: 7685.129119827412
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Epoch: 35
Acc : 96.49 / 84.29
Loss : 0.13 / 0.49
Time: 8925.508030240424
---------

Epoch: 40
Acc : 98.33 / 84.07
Loss : 0.08 / 0.51
Time: 10166.46677840408
---------

Epoch: 45
Acc : 99.31 / 84.71
Loss : 0.05 / 0.51
Time: 11407.179788754322
---------
Best Acc : 84.74
Training time (min): 206.67341564196784
Log :" res/benchmark_NoCeil/log/MyLeNetMatNormalNoceil-50epochs__k3_1.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatNormalNoceil-50epochs__k3_1 " saved !

real	206m56.537s
user	164m29.383s
sys	69m32.644s