Namespace(batch=128, dataset='CIFAR10', epochs=50, k=2, lr=0.05, net='MyLeNetMatNormalNoceil', postfix='__k2_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 : 36.03 / 48.99
Loss : 1.73 / 1.44
Time: 123.21687715034932
---------

Epoch: 5
Acc : 71.80 / 72.91
Loss : 0.82 / 0.78
Time: 739.4670832967386
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Epoch: 10
Acc : 79.74 / 78.42
Loss : 0.58 / 0.62
Time: 1355.8709250381216
---------

Epoch: 15
Acc : 84.44 / 79.47
Loss : 0.45 / 0.60
Time: 1972.987782953307
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Epoch: 20
Acc : 87.94 / 82.06
Loss : 0.35 / 0.53
Time: 2590.0748241245747
---------

Epoch: 25
Acc : 91.02 / 82.41
Loss : 0.27 / 0.53
Time: 3207.198580466211
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Epoch: 30
Acc : 93.75 / 83.29
Loss : 0.20 / 0.51
Time: 3824.246278378181
---------

Epoch: 35
Acc : 96.25 / 84.13
Loss : 0.13 / 0.49
Time: 4441.094482817687
---------

Epoch: 40
Acc : 98.26 / 84.04
Loss : 0.09 / 0.53
Time: 5057.893284536898
---------

Epoch: 45
Acc : 99.16 / 84.72
Loss : 0.06 / 0.51
Time: 5674.5474897976965
---------
Best Acc : 84.99
Training time (min): 102.79756409196804
Log :" res/benchmark_NoCeil/log/MyLeNetMatNormalNoceil-50epochs__k2_2.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatNormalNoceil-50epochs__k2_2 " saved !

real	103m1.616s
user	96m38.047s
sys	34m9.080s