Namespace(batch=128, dataset='CIFAR10', epochs=50, k=2, lr=0.05, net='MyLeNetMatStochNoceil', postfix='__k2_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 : 25.34 / 29.78
Loss : 1.98 / 1.85
Time: 47.96411813329905
---------

Epoch: 5
Acc : 48.65 / 42.37
Loss : 1.42 / 1.55
Time: 287.80597504321486
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Epoch: 10
Acc : 56.07 / 38.00
Loss : 1.23 / 1.70
Time: 527.6232785293832
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Epoch: 15
Acc : 59.94 / 36.03
Loss : 1.12 / 1.76
Time: 767.5103654088452
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Epoch: 20
Acc : 62.89 / 43.49
Loss : 1.04 / 1.52
Time: 1007.4215006893501
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Epoch: 25
Acc : 65.90 / 43.04
Loss : 0.96 / 1.55
Time: 1247.2988663418218
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Epoch: 30
Acc : 68.11 / 41.09
Loss : 0.91 / 1.59
Time: 1487.2040980625898
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Epoch: 35
Acc : 71.02 / 40.45
Loss : 0.82 / 1.66
Time: 1727.0953295668587
---------

Epoch: 40
Acc : 72.37 / 46.05
Loss : 0.78 / 1.51
Time: 1966.9677904183045
---------

Epoch: 45
Acc : 73.65 / 46.43
Loss : 0.75 / 1.54
Time: 2206.9109367653728
---------
Best Acc : 47.12
Training time (min): 39.980595599099374
Log :" res/benchmark_NoCeil/log/MyLeNetMatStochNoceil-50epochs__k2_1.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatStochNoceil-50epochs__k2_1 " saved !

real	40m12.627s
user	55m24.324s
sys	12m21.461s