Namespace(batch=128, dataset='CIFAR10', epochs=50, k=4, lr=0.05, net='MyLeNetMatNormalNoceil', postfix='__k4_1', res_folder='res/benchmark_NoCeil/', resume=False, scheduler='cosine', stoch=False, warmup_ep=5, warmup_mul=0)
==> Preparing data..
==> Building model..
==> Training model..
---------

Epoch: 0
Acc : 35.99 / 47.12
Loss : 1.73 / 1.43
Time: 413.15663176588714
---------

Epoch: 5
Acc : 72.51 / 69.89
Loss : 0.78 / 0.87
Time: 2480.58620422706
---------

Epoch: 10
Acc : 80.56 / 76.70
Loss : 0.56 / 0.67
Time: 4549.522261521779
---------

Epoch: 15
Acc : 85.25 / 79.85
Loss : 0.43 / 0.59
Time: 6618.715358470567
---------

Epoch: 20
Acc : 88.85 / 80.16
Loss : 0.33 / 0.58
Time: 8688.104032479227
---------

Epoch: 25
Acc : 91.80 / 82.65
Loss : 0.25 / 0.51
Time: 10757.39982889127
---------

Epoch: 30
Acc : 94.70 / 83.66
Loss : 0.17 / 0.50
Time: 12826.700856998563
---------

Epoch: 35
Acc : 97.03 / 83.37
Loss : 0.11 / 0.54
Time: 14895.382152607664
---------

Epoch: 40
Acc : 98.66 / 84.33
Loss : 0.07 / 0.51
Time: 16965.023936793208
---------

Epoch: 45
Acc : 99.53 / 84.55
Loss : 0.05 / 0.52
Time: 19034.066288430244
---------
Best Acc : 84.77
Training time (min): 344.79890690402436
Log :" res/benchmark_NoCeil/log/MyLeNetMatNormalNoceil-50epochs__k4_1.json " saved !
Plot :" res/benchmark_NoCeil/MyLeNetMatNormalNoceil-50epochs__k4_1 " saved !

real	345m2.785s
user	255m9.074s
sys	118m22.763s