Namespace(batch=128, dataset='CIFAR10', epochs=50, k=3, lr=0.05, net='MyLeNetMatStochNoceil', postfix='__k3_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 : 25.51 / 29.79
Loss : 1.99 / 1.85
Time: 88.86880144290626
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Epoch: 5
Acc : 48.73 / 36.95
Loss : 1.41 / 1.75
Time: 533.375917987898
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Epoch: 10
Acc : 56.15 / 35.34
Loss : 1.23 / 1.73
Time: 978.0676415488124
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Epoch: 15
Acc : 60.08 / 38.06
Loss : 1.13 / 1.68
Time: 1422.6883844202384
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Epoch: 20
Acc : 64.37 / 39.67
Loss : 1.00 / 1.65
Time: 1867.38415880315
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Epoch: 25
Acc : 66.28 / 35.38
Loss : 0.95 / 1.96
Time: 2312.077256356366
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Epoch: 30
Acc : 68.93 / 41.81
Loss : 0.88 / 1.61
Time: 2756.5770405810326
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Epoch: 35
Acc : 71.02 / 44.29
Loss : 0.82 / 1.61
Time: 3200.8784932522103
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Epoch: 40
Acc : 73.21 / 45.35
Loss : 0.76 / 1.58
Time: 3645.313464949839
---------

Epoch: 45
Acc : 75.00 / 45.84
Loss : 0.71 / 1.56
Time: 4089.6597863975912
---------
Best Acc : 46.56
Training time (min): 74.08285954588403
Log :" res/benchmark_NoCeil/log/MyLeNetMatStochNoceil-50epochs__k3_3.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatStochNoceil-50epochs__k3_3 " saved !

real	74m17.415s
user	79m1.446s
sys	24m21.474s