Namespace(batch=128, dataset='CIFAR10', epochs=10, lr=0.05, net='MyLeNetMatStochBUNoceil', 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 : 22.73 / 30.49
Loss : 2.06 / 1.90
Time: 73.46249075420201
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Epoch: 1
Acc : 30.11 / 30.61
Loss : 1.87 / 1.79
Time: 146.35232928954065
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Epoch: 2
Acc : 34.14 / 33.30
Loss : 1.77 / 1.73
Time: 219.46285958588123
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Epoch: 3
Acc : 38.18 / 34.64
Loss : 1.68 / 1.74
Time: 292.7825370589271
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Epoch: 4
Acc : 40.50 / 37.73
Loss : 1.62 / 1.68
Time: 366.0361840762198
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Epoch: 5
Acc : 43.22 / 38.42
Loss : 1.54 / 1.61
Time: 439.2800999926403
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Epoch: 6
Acc : 46.57 / 39.54
Loss : 1.47 / 1.61
Time: 513.1152702141553
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Epoch: 7
Acc : 48.72 / 38.11
Loss : 1.41 / 1.69
Time: 586.3596808109432
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Epoch: 8
Acc : 50.07 / 37.34
Loss : 1.37 / 1.67
Time: 660.0147361075506
---------

Epoch: 9
Acc : 51.24 / 40.30
Loss : 1.35 / 1.60
Time: 733.1694793645293
---------
Best Acc : 40.30
Training time (min): 12.219491492429126
Log :" res/log/MyLeNetMatStochBUNoceil-10epochs_noCrop_k3.json " saved !
Plot :" res/MyLeNetMatStochBUNoceil-10epochs_noCrop_k3 " saved !

real	12m34.154s
user	14m9.534s
sys	3m43.740s