Namespace(batch=128, dataset='CIFAR10', epochs=50, k=1, lr=0.05, net='MyLeNetMatStochNoceil', 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 : 25.65 / 27.44
Loss : 1.98 / 1.93
Time: 22.87828525621444
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Epoch: 5
Acc : 47.19 / 34.34
Loss : 1.45 / 1.73
Time: 136.54613589681685
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Epoch: 10
Acc : 54.83 / 34.87
Loss : 1.26 / 1.79
Time: 250.1823681294918
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Epoch: 15
Acc : 58.61 / 36.11
Loss : 1.16 / 1.67
Time: 364.1771142780781
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Epoch: 20
Acc : 61.51 / 41.69
Loss : 1.07 / 1.61
Time: 477.91743985097855
---------

Epoch: 25
Acc : 64.63 / 42.91
Loss : 1.00 / 1.60
Time: 591.6240369612351
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Epoch: 30
Acc : 66.87 / 42.92
Loss : 0.94 / 1.60
Time: 705.5203553121537
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Epoch: 35
Acc : 69.64 / 40.97
Loss : 0.86 / 1.71
Time: 819.437248964794
---------

Epoch: 40
Acc : 71.34 / 45.05
Loss : 0.82 / 1.57
Time: 933.206932798028
---------

Epoch: 45
Acc : 72.89 / 46.70
Loss : 0.78 / 1.52
Time: 1047.1215672474355
---------
Best Acc : 47.16
Training time (min): 18.968624996906147
Log :" res/benchmark_NoCeil/log/MyLeNetMatStochNoceil-50epochs__k1_2.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatStochNoceil-50epochs__k1_2 " saved !

real	19m10.751s
user	39m32.089s
sys	5m24.696s