Namespace(batch=128, dataset='CIFAR10', epochs=10, lr=0.05, net='MyLeNetMatStochNoceil', postfix='_noCrop_k3', res_folder='res/', 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 : 25.40 / 29.56
Loss : 1.99 / 1.83
Time: 88.82820883858949
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Epoch: 1
Acc : 35.13 / 32.19
Loss : 1.74 / 1.77
Time: 177.5576635012403
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Epoch: 2
Acc : 40.73 / 35.05
Loss : 1.61 / 1.76
Time: 266.2516449401155
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Epoch: 3
Acc : 45.58 / 38.76
Loss : 1.49 / 1.71
Time: 355.2165524791926
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Epoch: 4
Acc : 49.07 / 35.94
Loss : 1.41 / 1.71
Time: 443.9428597986698
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Epoch: 5
Acc : 52.32 / 32.03
Loss : 1.32 / 1.86
Time: 532.6662928508595
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Epoch: 6
Acc : 54.68 / 40.80
Loss : 1.26 / 1.59
Time: 621.3865936575457
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Epoch: 7
Acc : 58.03 / 41.34
Loss : 1.17 / 1.62
Time: 710.462741760537
---------

Epoch: 8
Acc : 59.08 / 44.26
Loss : 1.15 / 1.53
Time: 799.1782552432269
---------

Epoch: 9
Acc : 60.38 / 42.60
Loss : 1.11 / 1.58
Time: 887.9221545867622
---------
Best Acc : 44.26
Training time (min): 14.798702753568069
Log :" res/log/MyLeNetMatStochNoceil-10epochs_noCrop_k3.json " saved !
Plot :" res/MyLeNetMatStochNoceil-10epochs_noCrop_k3 " saved !

real	15m9.606s
user	15m45.480s
sys	4m48.638s