Namespace(batch=128, dataset='CIFAR10', epochs=50, k=1, lr=0.05, net='MyLeNetMatStochNoceil', 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 : 25.31 / 32.71
Loss : 1.97 / 1.80
Time: 23.04006605129689
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Epoch: 5
Acc : 47.91 / 37.56
Loss : 1.44 / 1.63
Time: 137.0359864262864
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Epoch: 10
Acc : 54.32 / 38.65
Loss : 1.28 / 1.77
Time: 250.97384090255946
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Epoch: 15
Acc : 59.07 / 35.07
Loss : 1.15 / 1.64
Time: 365.1462406516075
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Epoch: 20
Acc : 61.75 / 33.37
Loss : 1.07 / 1.84
Time: 479.1790603613481
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Epoch: 25
Acc : 64.43 / 40.65
Loss : 1.00 / 1.69
Time: 593.1814860291779
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Epoch: 30
Acc : 67.26 / 43.06
Loss : 0.92 / 1.60
Time: 707.3531251512468
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Epoch: 35
Acc : 69.03 / 42.53
Loss : 0.88 / 1.67
Time: 821.4921944644302
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Epoch: 40
Acc : 71.71 / 42.02
Loss : 0.81 / 1.68
Time: 935.5345202535391
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Epoch: 45
Acc : 72.13 / 45.46
Loss : 0.79 / 1.57
Time: 1049.5861575081944
---------
Best Acc : 46.35
Training time (min): 19.014818465150892
Log :" res/benchmark_NoCeil/log/MyLeNetMatStochNoceil-50epochs__k1_3.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatStochNoceil-50epochs__k1_3 " saved !

real	19m13.464s
user	39m30.936s
sys	5m26.684s