Namespace(batch=128, dataset='CIFAR10', epochs=50, k=1, lr=0.05, net='MyLeNetMatStochBUNoceil', postfix='__k1_1', 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 : 22.40 / 33.33
Loss : 2.07 / 1.88
Time: 23.69926338084042
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Epoch: 5
Acc : 39.01 / 32.53
Loss : 1.66 / 1.82
Time: 142.7658422710374
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Epoch: 10
Acc : 45.48 / 38.35
Loss : 1.49 / 1.62
Time: 260.89411601331085
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Epoch: 15
Acc : 48.70 / 35.44
Loss : 1.41 / 1.69
Time: 379.99177754390985
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Epoch: 20
Acc : 52.10 / 38.83
Loss : 1.33 / 1.69
Time: 497.3336850358173
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Epoch: 25
Acc : 54.84 / 42.42
Loss : 1.26 / 1.55
Time: 616.1871792878956
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Epoch: 30
Acc : 57.42 / 40.18
Loss : 1.19 / 1.60
Time: 734.6347392667085
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Epoch: 35
Acc : 60.00 / 43.08
Loss : 1.12 / 1.55
Time: 852.3725217897445
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Epoch: 40
Acc : 61.69 / 43.45
Loss : 1.07 / 1.55
Time: 971.9417355190963
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Epoch: 45
Acc : 62.51 / 45.85
Loss : 1.05 / 1.53
Time: 1090.8980515552685
---------
Best Acc : 46.76
Training time (min): 19.73898232462816
Log :" res/benchmark_NoCeil/log/MyLeNetMatStochBUNoceil-50epochs__k1_1.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatStochBUNoceil-50epochs__k1_1 " saved !

real	19m56.378s
user	41m16.163s
sys	4m49.607s