Qeexid
Batch normalization waxay dib u xarunaysaa oo dib u cabbirtaa firaysiga iyadoo la adeegsanayo tirakoobka batch-ka, ka dibna waxay barataa parameter-yo scale iyo shift ah. Waxay yaraysan kartaa internal covariate shift-ka waxayna u ogolaataa heerar barasho oo sare.
LayerNorm ayaa ku door bidan transformers badan; BatchNorm ayaa weli caan ku ah CNN-yada.
Si fudud
Waa sida in dhibcaha imtixaanka la caddeeyo si fasal kasta uu leeyahay celceliska isku eg — taasoo qiimaynta danbe (layers) ka dhigaysa mid xasilloon.
Halka aad ka aragto
- Moodeelada computer vision ee qaabka ResNet.
- Moodeelo qoto-dheer oo hadal iyo tabular ah qaarkood.
Sida ay u shaqeyso
1.Xisaabi tirakoobka batch-ka
Celcelis iyo kala-duwanaan gudaha mini-batch-ka.
2.Dejin
Simo firaysiga.
3.Scale iyo shift
γ iyo β la baran karo ayaa soo celinaya awoodda matalaadda.
Maxay muhiim u tahay
- Layers-ka normalization-ku waxay tababarka shabakadaha aad u qoto-dheer ka dhigeen mid suurtagal ah.
Inta badan la khaldo
BatchNorm waa lagama-maarmaan qaab-dhismeed kasta.
Transformers badanaa waxay isticmaalaan LayerNorm; BatchNorm si aan caadi ahayn ayay u dhaqmi kartaa marka batch-yadu aad u yaryahiin.