Namespace(batch=128, dataset='CIFAR10', epochs=50, k=1, lr=0.05, net='MyLeNetMatNormalNoceil', 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 : 36.34 / 46.99
Loss : 1.72 / 1.43
Time: 45.97680170927197
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Epoch: 5
Acc : 70.85 / 70.73
Loss : 0.83 / 0.83
Time: 275.01454721949995
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Epoch: 10
Acc : 78.84 / 75.75
Loss : 0.61 / 0.70
Time: 504.2062480049208
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Epoch: 15
Acc : 83.54 / 79.54
Loss : 0.47 / 0.60
Time: 733.3581873718649
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Epoch: 20
Acc : 86.82 / 81.49
Loss : 0.38 / 0.54
Time: 962.6645513242111
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Epoch: 25
Acc : 89.89 / 81.93
Loss : 0.29 / 0.54
Time: 1191.833936353214
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Epoch: 30
Acc : 92.88 / 83.44
Loss : 0.22 / 0.49
Time: 1421.0683761807159
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Epoch: 35
Acc : 95.38 / 83.74
Loss : 0.16 / 0.50
Time: 1650.2434674538672
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Epoch: 40
Acc : 97.26 / 84.41
Loss : 0.11 / 0.50
Time: 1879.4910161253065
---------

Epoch: 45
Acc : 98.51 / 84.84
Loss : 0.08 / 0.49
Time: 2108.9041818892583
---------
Best Acc : 84.94
Training time (min): 38.20426822579466
Log :" res/benchmark_NoCeil/log/MyLeNetMatNormalNoceil-50epochs__k1_2.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatNormalNoceil-50epochs__k1_2 " saved !

real	38m24.983s
user	54m3.179s
sys	11m47.645s