Namespace(batch=128, dataset='CIFAR10', epochs=50, k=1, lr=0.05, net='MyLeNetMatNormalNoceil', postfix='__k1_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 : 35.43 / 48.21
Loss : 1.73 / 1.43
Time: 46.12261764425784
---------

Epoch: 5
Acc : 70.44 / 69.29
Loss : 0.85 / 0.87
Time: 276.4114668201655
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Epoch: 10
Acc : 78.80 / 76.67
Loss : 0.61 / 0.68
Time: 506.5132551435381
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Epoch: 15
Acc : 83.43 / 80.02
Loss : 0.48 / 0.58
Time: 736.7161982152611
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Epoch: 20
Acc : 86.87 / 80.73
Loss : 0.38 / 0.55
Time: 966.8520798627287
---------

Epoch: 25
Acc : 90.07 / 83.00
Loss : 0.30 / 0.51
Time: 1197.1624066643417
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Epoch: 30
Acc : 92.45 / 82.59
Loss : 0.23 / 0.52
Time: 1427.6633465271443
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Epoch: 35
Acc : 94.93 / 83.86
Loss : 0.17 / 0.48
Time: 1658.0701657654718
---------

Epoch: 40
Acc : 96.97 / 84.58
Loss : 0.12 / 0.48
Time: 1888.4067949829623
---------

Epoch: 45
Acc : 98.12 / 84.77
Loss : 0.09 / 0.49
Time: 2118.8804153930396
---------
Best Acc : 84.89
Training time (min): 38.38393786516972
Log :" res/benchmark_NoCeil/log/MyLeNetMatNormalNoceil-50epochs__k1_1.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatNormalNoceil-50epochs__k1_1 " saved !

real	38m36.671s
user	52m22.204s
sys	12m0.649s