- Version_1
Performance: 0.99171(402/1579)
Use CNN with batchnorm, initilization... - Version_2
Performance: 0.99192(390/1594)
Preprocess the data in range of[-1,1]
- Version_3
Performance: 0.99303(310/1595)
Use data augmentation by usingalbumentation
- Version_4
Performance: 0.99428(214/1592)
Use 10-fold cross validation which has 100 epochs per one fold by usingsklearn.model_selection.stratifiedKFold
to get more training datasets.
Performance: 0.99460(189/1592)
Use Early stopped 10-fold cross validation model - Version_5
Performance:0.99514(146/1592)
Change batch size 64->256
Performance: 0.99535(132/1592)
Use Early stopped model whch has 256 batch size by usingdataloader
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