Namespace(batch=128, dataset='CIFAR10', epochs=50, k=2, lr=0.05, net='MyLeNetMatNormalNoceil', postfix='__k2_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 : 36.99 / 46.90
Loss : 1.71 / 1.47
Time: 123.3850756874308
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Epoch: 5
Acc : 71.92 / 70.74
Loss : 0.81 / 0.84
Time: 740.4402446337044
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Epoch: 10
Acc : 79.88 / 76.11
Loss : 0.58 / 0.70
Time: 1357.5990120908245
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Epoch: 15
Acc : 84.43 / 80.63
Loss : 0.45 / 0.56
Time: 1975.4050657227635
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Epoch: 20
Acc : 88.04 / 80.34
Loss : 0.35 / 0.57
Time: 2593.1981341233477
---------

Epoch: 25
Acc : 91.30 / 82.08
Loss : 0.26 / 0.53
Time: 3211.109001107514
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Epoch: 30
Acc : 94.06 / 82.95
Loss : 0.19 / 0.51
Time: 3828.7535809641704
---------

Epoch: 35
Acc : 96.45 / 83.79
Loss : 0.13 / 0.50
Time: 4446.439873588271
---------

Epoch: 40
Acc : 98.28 / 84.44
Loss : 0.08 / 0.51
Time: 5064.219255410135
---------

Epoch: 45
Acc : 99.23 / 84.78
Loss : 0.06 / 0.51
Time: 5681.4778324710205
---------
Best Acc : 84.92
Training time (min): 102.92114744419231
Log :" res/benchmark_NoCeil/log/MyLeNetMatNormalNoceil-50epochs__k2_1.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatNormalNoceil-50epochs__k2_1 " saved !

real	103m8.605s
user	98m5.937s
sys	33m32.017s