Namespace(batch=128, dataset='CIFAR10', epochs=50, k=3, lr=0.05, net='MyLeNetMatNormalNoceil', postfix='__k3_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 : 36.50 / 46.49
Loss : 1.72 / 1.47
Time: 247.84990867320448
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Epoch: 5
Acc : 71.88 / 68.91
Loss : 0.80 / 0.89
Time: 1487.8860270297155
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Epoch: 10
Acc : 80.39 / 78.03
Loss : 0.57 / 0.64
Time: 2728.763779843226
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Epoch: 15
Acc : 85.00 / 80.67
Loss : 0.44 / 0.57
Time: 3969.208628097549
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Epoch: 20
Acc : 88.49 / 80.28
Loss : 0.34 / 0.57
Time: 5209.553945231251
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Epoch: 25
Acc : 91.64 / 82.31
Loss : 0.25 / 0.53
Time: 6450.321215154603
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Epoch: 30
Acc : 94.55 / 82.92
Loss : 0.18 / 0.50
Time: 7690.907434923574
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Epoch: 35
Acc : 96.83 / 83.45
Loss : 0.12 / 0.52
Time: 8931.464527050033
---------

Epoch: 40
Acc : 98.60 / 84.15
Loss : 0.07 / 0.51
Time: 10172.187801788561
---------

Epoch: 45
Acc : 99.43 / 84.93
Loss : 0.05 / 0.51
Time: 11412.973015635274
---------
Best Acc : 84.93
Training time (min): 206.75552665510526
Log :" res/benchmark_NoCeil/log/MyLeNetMatNormalNoceil-50epochs__k3_2.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatNormalNoceil-50epochs__k3_2 " saved !

real	206m59.928s
user	165m3.232s
sys	69m9.800s