GUIDE teknik

Akorde hiperparametre

Hyperparametre yi ñooy jekkal yi nga tànn balaa ngay tàggat, lu melni tolluwaayu jàng wala dayo model bi, model bi jàngul boppam.

Déglul tegtal biiIA-nettali · ~2 min

Ci xët wii2 simili jàng
  1. Résumé
  2. Plongeur bu xóot
  3. Doxal ci àdduna dëgg
  4. Ëlëgu tuning hyperparametre
  5. Teg ko ci jëf
  6. Weyal di banneexu
  7. Laaj yi ñuy faral di laaj

Résumé

Tuning them well is often the difference between a mediocre model and a great one.

Plongeur bu xóot

Parametru model bi (poid yi) ñu ngi koy jàngee ci done yi ci diiru tàggat bi. Hyperparameters yi wuute nañu: ñooy knob yi nga njëkka def ñuy doxal ni jàng bi di doxee, lu melni taxawaayu jàng, dayo batch, limu layers, dooley regularisation, ak diir bi nga wara tàggat. Mënu leen optimiser ci wàcci gradient ci saasi, kon dangay seet valeur yu baax ci tàggat model candidat yu bari te nga méngale leen ci ensemble validation. Li gëna yomba def mooy seetlu ci griy, jéem bépp boole ci griy buñ tànn bu njëkk, waaye dafay yokk bu baax. Seetug aleatër mooy gëna gaaw ci gis jekkal yu baax ci boole ay misaal. Optimisation bayesien bu gëna xarañ dafa tabax xeetu probabilite buy wane ni jekkal yi dañu am yaakaar, ba noppi fokalise seetlu bi. Tolluwaayu jàng mooy faral di nekk benn hyperparametre bi gëna am solo ngir mëna jub.

Doxal ci àdduna dëgg

Tolluwaayu jàng bu bari ci xeetu magnitude yu bari ngir gis valeur bi reso bi di tàggatee gaaw te du sori.

Jëfandikoo seetug aleatër ngir méngale xóotaayu garab gi, limu garab yi, ak ni ñuy jàngee ngir am xeetu gradient buy yokk ci done tablo.

Doxal njariñu Bayesian ngir boole dooley regularisasioŋ ak dayo lote ngir reso bu xóot ci budget GPU bu néew.

Jëfandikoo Hyperband ngir tàggat fukki-fukki configurations ci diir bu gàtt, ba noppi jox yeneen epochs ci ñi gëna am yaakaar ci mucc.

Ëlëgu tuning hyperparametre

Tuning manuel ak griy dafay may yoon jàngu masin otomatik (AutoML) ak seetlu bu gëna am xel lu melni optimisation Bayesian ak Hyperband, ñoom ñooy jëfandikoo ordinatër ci anam wu gëna xéewale. Lu modelu fondation yi di màgg, retraining bu mat sëkk ci trial bu nekk dafay seer lool, moo tax bàyyi xel ci proxy yu gëna yomb, yooni scaling yuy wax lu baax ci runs yu ndaw, ak tuning adaptateur yu woyof ci barabu model yu mat. Xaarandil tuning mu gëna otomatise ak budget-aware, ak jumtukaay yuy njënd ak njaay seetlu njëg ak benefiis yi ñuy seentu.

Teg ko ci jëf

Lu tax mu am solo

  • Njëgg ak budget. Dogal yi architecture di jël dañuy indi njariñ ak njëgu liggéey bi ay at ci ginaaw.
  • dogal yu gëna leer. Njàngalem xarala yi dafay jàppale ekip yi ñu tànn li gën, te baña yam ci li gëna bees daal.
  • Xool kalite. Tanneef yu gëna baax ci wàllu ingeñër dina wàññi jafe-jafe yi ci wàllu wóor ci liggéey bi.

Moytul

  • Optimize benn benchmark mën na nëbb ñakk kattan yu gëna yaatu ci sistem bi.
  • Njëg li ñuy fay ci infrastructure yi ak ci toppatoo dañuy faral di suufeel.
  • Bu sistem yi di gëna xawa jafee xam, jafe-jafe yi am ci wàllu kaaraange ak seetlu mën nañu gëna bari.

Jéego yi ci topp

  1. Mandargal latency, kalite, ak njëg yi laata ngay jëfandikoo.
  2. Benchmark ci biir sargal ak done yu dëggu.
  3. Jumtukaay bi di saytu njuumte yi, derive bi ak njeextalu jëfandikukat bi.
  4. Waajal rollback ak yooni tontu ci jafe-jafe yi laata ngay eskale.

Weyal di banneexu

Bulletin bu amul fayda

Jàngal xibaar AI bu bes

Ñatti jaar-jaari IA yuñ firndeel bis bu nekk ci ayu-bis bi, ñu bind leen ci Àngle bu leer. Gratis ba fàww, amul yëgle.

Benn email bis bu nekk ci ayu-bis bi. Benn klik nga dindi abonemaa bi. Dunu musa jaay wala séddoo sa adres.

Nattal sa bopp

Take the Hyperparameter Tuning quiz

Feedback ci saasi ci bépp tontu, ak sertifikaa buñ mëna séddoo ak ID buñ mëna saytu soo jàllee ci njàng mi.

Tambalil quiz

Jàppale njàngum IA te doo fay. AI Understanding mbootaay la buy def te Yàlla tax — amul yëgle, amul paywall, musul am. Defal ab sarax

Laaj yi ñuy faral di laaj

What is Hyperparameter Tuning?

Hyperparametre yi ñooy jekkal yi nga tànn balaa ngay tàggat, lu melni tolluwaayu jàng wala dayo model bi, model bi jàngul boppam. Soo leen méngale bu baax mooy wuutale model bu baaxul ak model bu baax.

Lan mooy wuutale hyperparamètre ak parametre model buñ miin?

Poid yi (parametre yi) ñu ngi leen jàngee ci done yi ci diiru tàggat yaram. Hyperparametre yi, lu ci melni taxawaayu jàng wala limu diisaay yi, dañu leen di tànnee bu njëkk ba noppi di saytu ni tàggat bi di doxee.

Lan mooy hyperparametre bi gëna am solo ngir mëna jàng bu xóot?

Tolluwaayu jàng amna njeexital yu am solo ci gaawaayu model bi ak ni muy gaawe. Kawe lool ak tàggat yaram wuute; mu wàcci lool mu raam wala mu tëju.

Lan moo waral seetlu aleatër di faral di raw seetlu griy ngir akor hyperparametre?

Seetug griy dafay yàq natt ci dimension yu amul solo. Seetug aleatër mooy gëna xéewale bayaal bi ba noppi di faral di yegg ci configurasioŋ yu baax ak jéem yu néew.

naka la ko optimaasioŋ bayesien di tànnee ban taabal hiperparametre lay jéem ci topp?

Optimisation Bayesian dafay wane lëkkaloo gi am ci digganté configurations ak poñ yiñ am ci validation, ba noppi tànnee test bi ci topp ngir ekilibre exploration ci gox yu wóorul ak exploitation ci gox yu am yaakaar.

Lan moo waral ñu wara baña laal ensemble test bu mujj bi ñuy ajuste hyperparamètre bi?

Tuning dafay tànn jekkal yi gëna baax ci bépp done booy jàngat. Sudee loolu mooy setu test bi, sa performance biñu def dafa yokk. Tuning dafay jëfandikoo ensemble validation bu wuute.