Namespace(batch=128, dataset='CIFAR10', epochs=50, k=1, lr=0.05, net='MyLeNetMatStochBUNoceil', postfix='__k1_3', 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 : 22.71 / 22.38
Loss : 2.05 / 1.98
Time: 23.942733087576926
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Epoch: 5
Acc : 39.64 / 32.36
Loss : 1.65 / 1.86
Time: 144.20551797002554
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Epoch: 10
Acc : 45.79 / 33.74
Loss : 1.50 / 1.76
Time: 264.1239112522453
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Epoch: 15
Acc : 49.18 / 37.71
Loss : 1.40 / 1.66
Time: 382.70462130755186
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Epoch: 20
Acc : 52.63 / 41.70
Loss : 1.32 / 1.58
Time: 501.70173474773765
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Epoch: 25
Acc : 55.52 / 42.16
Loss : 1.24 / 1.55
Time: 620.2704349383712
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Epoch: 30
Acc : 57.60 / 42.07
Loss : 1.19 / 1.61
Time: 740.046815501526
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Epoch: 35
Acc : 59.83 / 40.80
Loss : 1.13 / 1.64
Time: 860.0331608653069
---------

Epoch: 40
Acc : 60.89 / 41.76
Loss : 1.09 / 1.63
Time: 980.0542129781097
---------

Epoch: 45
Acc : 62.60 / 42.83
Loss : 1.05 / 1.61
Time: 1099.9315661629662
---------
Best Acc : 47.46
Training time (min): 19.902773757139222
Log :" res/benchmark_NoCeil/log/MyLeNetMatStochBUNoceil-50epochs__k1_3.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatStochBUNoceil-50epochs__k1_3 " saved !

real	20m6.443s
user	41m56.250s
sys	4m44.181s