Namespace(batch=128, dataset='CIFAR10', epochs=50, k=4, lr=0.05, net='MyLeNetMatStochNoceil', postfix='__k4_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 : 25.53 / 31.27
Loss : 1.98 / 1.83
Time: 138.69305455219
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Epoch: 5
Acc : 49.02 / 37.01
Loss : 1.41 / 1.75
Time: 832.2641551829875
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Epoch: 10
Acc : 56.74 / 39.72
Loss : 1.22 / 1.72
Time: 1526.109748011455
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Epoch: 15
Acc : 60.87 / 42.71
Loss : 1.11 / 1.59
Time: 2219.8009980134666
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Epoch: 20
Acc : 63.56 / 39.88
Loss : 1.03 / 1.67
Time: 2913.56171762757
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Epoch: 25
Acc : 66.38 / 41.00
Loss : 0.95 / 1.56
Time: 3607.454514555633
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Epoch: 30
Acc : 68.79 / 42.87
Loss : 0.88 / 1.56
Time: 4301.280980648473
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Epoch: 35
Acc : 71.48 / 43.23
Loss : 0.81 / 1.58
Time: 4995.14941327367
---------

Epoch: 40
Acc : 73.54 / 46.15
Loss : 0.75 / 1.57
Time: 5689.165943298489
---------

Epoch: 45
Acc : 74.85 / 46.25
Loss : 0.72 / 1.57
Time: 6383.023234537803
---------
Best Acc : 47.23
Training time (min): 115.63643312873319
Log :" res/benchmark_NoCeil/log/MyLeNetMatStochNoceil-50epochs__k4_2.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatStochNoceil-50epochs__k4_2 " saved !

real	115m51.013s
user	106m48.549s
sys	38m31.911s