Qeexid
Parameter-yada (miisaannada) waxaa laga baraa tababarka. Hyperparameter-yadu waa qalabka aad dejiso: learning rate, tirada layers-ka, dropout rate, temperature-ka inference-ka, iyo wax kale.
Habaynta wanaagsan ee kuwaan badanaa waxay u muhiim tahay sida qaabdhismeedka moodeelka.
Si fudud
Miisaannadu waa cuntada foornadu ay abuurto; hyperparameter-yadu waa heerkulka foornada iyo waqtiga karinta — kuwaas waad dejisaa ka hor inta aan karinta bilaaban.
Halka aad ka aragto
- Grid search ama Bayesian optimization oo lagu doorto learning rates.
- Doorashada dherer context-ka iyo temperature-ka ee API-yada LLM.
Sida ay u shaqeyso
1.Dooro musharraxiin
Qeex booska raadinta ee dejinnada.
2.Tababar oo qiimee
Cabbir waxqabadka validation-ka dejin kasta.
3.Dooro tan ugu fiican
Sii wado dejinta guud ahaan wanaagsan; mar kale ku tijaabi xog aan la taaban.
Maxay muhiim u tahay
- Hyperparameter-yo liidata waxay ka dhigi karaan qaab-dhismeed xoog leh mid liita u eg.
Inta badan la khaldo
Layers badan had iyo jeer way caawiyaan.
Dherer (depth) waa hyperparameter — awood xad-dhaaf ah oo aan xog lagu haysan waxay keentaa overfitting.