Namespace(batch=128, dataset='CIFAR10', epochs=50, k=3, lr=0.05, net='MyLeNetMatStochNoceil', postfix='__k3_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 : 25.43 / 30.27
Loss : 1.98 / 1.86
Time: 88.86627784278244
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Epoch: 5
Acc : 48.91 / 32.66
Loss : 1.41 / 1.83
Time: 533.099832713604
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Epoch: 10
Acc : 56.05 / 37.94
Loss : 1.23 / 1.67
Time: 977.4172119349241
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Epoch: 15
Acc : 60.28 / 38.37
Loss : 1.11 / 1.70
Time: 1421.747462933883
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Epoch: 20
Acc : 63.74 / 37.67
Loss : 1.02 / 1.68
Time: 1866.0527866259217
---------

Epoch: 25
Acc : 66.02 / 38.42
Loss : 0.96 / 1.74
Time: 2310.4425071775913
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Epoch: 30
Acc : 69.11 / 41.55
Loss : 0.88 / 1.64
Time: 2755.050319542177
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Epoch: 35
Acc : 71.41 / 46.73
Loss : 0.82 / 1.52
Time: 3199.463610848412
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Epoch: 40
Acc : 73.18 / 43.02
Loss : 0.76 / 1.65
Time: 3643.856560504064
---------

Epoch: 45
Acc : 74.14 / 45.88
Loss : 0.74 / 1.58
Time: 4088.410287500359
---------
Best Acc : 47.19
Training time (min): 74.06591026883883
Log :" res/benchmark_NoCeil/log/MyLeNetMatStochNoceil-50epochs__k3_1.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatStochNoceil-50epochs__k3_1 " saved !

real	74m18.154s
user	77m19.376s
sys	24m31.717s