Namespace(batch=128, dataset='CIFAR10', epochs=50, k=4, lr=0.05, net='MyLeNetMatStochNoceil', postfix='__k4_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 : 25.19 / 31.17
Loss : 1.99 / 1.84
Time: 138.68438915722072
---------

Epoch: 5
Acc : 48.85 / 40.39
Loss : 1.42 / 1.68
Time: 832.1555920224637
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Epoch: 10
Acc : 56.04 / 34.76
Loss : 1.23 / 1.76
Time: 1525.8188216267154
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Epoch: 15
Acc : 60.87 / 38.62
Loss : 1.10 / 1.81
Time: 2219.536086712964
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Epoch: 20
Acc : 63.73 / 40.78
Loss : 1.02 / 1.74
Time: 2913.3058100305498
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Epoch: 25
Acc : 66.55 / 39.24
Loss : 0.95 / 1.68
Time: 3607.307444162667
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Epoch: 30
Acc : 69.17 / 47.70
Loss : 0.88 / 1.48
Time: 4300.989568569697
---------

Epoch: 35
Acc : 71.81 / 41.68
Loss : 0.80 / 1.62
Time: 4994.865097979084
---------

Epoch: 40
Acc : 73.30 / 45.42
Loss : 0.76 / 1.55
Time: 5688.842534529977
---------

Epoch: 45
Acc : 74.59 / 46.82
Loss : 0.72 / 1.52
Time: 6382.720301232301
---------
Best Acc : 47.70
Training time (min): 115.63096341982795
Log :" res/benchmark_NoCeil/log/MyLeNetMatStochNoceil-50epochs__k4_3.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatStochNoceil-50epochs__k4_3 " saved !

real	115m50.643s
user	105m32.016s
sys	37m36.485s