Namespace(batch=128, dataset='CIFAR10', epochs=50, k=1, lr=0.05, net='MyLeNetMatStochBUNoceil', postfix='__k1_2', 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 : 21.82 / 26.99
Loss : 2.06 / 1.88
Time: 23.74811160005629
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Epoch: 5
Acc : 39.08 / 38.52
Loss : 1.66 / 1.71
Time: 144.02691594604403
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Epoch: 10
Acc : 45.10 / 35.87
Loss : 1.51 / 1.83
Time: 264.6037198500708
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Epoch: 15
Acc : 48.87 / 38.52
Loss : 1.41 / 1.64
Time: 384.93165539298207
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Epoch: 20
Acc : 52.06 / 38.93
Loss : 1.33 / 1.64
Time: 506.40114451851696
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Epoch: 25
Acc : 55.01 / 39.44
Loss : 1.25 / 1.66
Time: 628.3252009730786
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Epoch: 30
Acc : 57.14 / 37.17
Loss : 1.19 / 1.69
Time: 748.4351985407993
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Epoch: 35
Acc : 59.74 / 42.78
Loss : 1.13 / 1.62
Time: 869.0831191660836
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Epoch: 40
Acc : 61.07 / 43.44
Loss : 1.09 / 1.58
Time: 989.6546215675771
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Epoch: 45
Acc : 63.31 / 43.17
Loss : 1.04 / 1.63
Time: 1112.0879259789363
---------
Best Acc : 46.04
Training time (min): 20.136301828424134
Log :" res/benchmark_NoCeil/log/MyLeNetMatStochBUNoceil-50epochs__k1_2.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatStochBUNoceil-50epochs__k1_2 " saved !

real	20m20.589s
user	42m38.377s
sys	4m32.509s