Namespace(batch=128, dataset='CIFAR10', epochs=50, k=1, lr=0.05, net='MyLeNetMatStochNoceil', postfix='__k1_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 : 25.68 / 28.52
Loss : 1.97 / 1.88
Time: 22.80050491821021
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Epoch: 5
Acc : 47.17 / 33.95
Loss : 1.45 / 1.80
Time: 136.88718870654702
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Epoch: 10
Acc : 54.93 / 35.39
Loss : 1.26 / 1.72
Time: 250.9757927497849
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Epoch: 15
Acc : 58.73 / 41.05
Loss : 1.15 / 1.68
Time: 364.77219730988145
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Epoch: 20
Acc : 61.29 / 36.65
Loss : 1.09 / 1.75
Time: 478.69057740084827
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Epoch: 25
Acc : 64.54 / 38.35
Loss : 1.00 / 1.87
Time: 592.9431653441861
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Epoch: 30
Acc : 67.13 / 38.56
Loss : 0.93 / 1.71
Time: 707.10416641552
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Epoch: 35
Acc : 69.71 / 42.13
Loss : 0.86 / 1.68
Time: 821.3001165790483
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Epoch: 40
Acc : 71.33 / 42.99
Loss : 0.81 / 1.67
Time: 935.0861265612766
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Epoch: 45
Acc : 72.50 / 44.22
Loss : 0.78 / 1.64
Time: 1049.0620342679322
---------
Best Acc : 46.14
Training time (min): 18.99982411774496
Log :" res/benchmark_NoCeil/log/MyLeNetMatStochNoceil-50epochs__k1_1.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatStochNoceil-50epochs__k1_1 " saved !

real	19m12.168s
user	40m45.219s
sys	5m20.754s