Kedis ku xidhan hagaha · Adag Heerka
Muunad la qorsheeyay iyo Kediska Eexda Soo Bandhigida
Waxay hubisaa sida muunad jadwalaysan u beddesho macnaha guud, sababta ixtimaalka summada dahabka ahi u qudhunto, iyo isbeddellada is-dhaafsiga ee muunada.
Su'aal 1 ee 8
Eexda soo bandhigista ayaa soo baxda sababtoo ah moodooyinka loo tababaray macalinka oo ku qasbaya shardi kaliya:
Horudhac su'aal kasta8 su'aalo
Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.
- Eexda soo bandhigista ayaa soo baxda sababtoo ah moodooyinka loo tababaray macalinka oo ku qasbaya shardi kaliya:
- Calaamadaha dhabta ah ee dhabta ah, laakiin waa inay adeegsadaan tooda marka la eego
- Calaamadahooda la saadaaliyay
- Calaamadaha qaylada random
- Calaamadaha mustaqbalka
- Muxuu sameeyaa muunad jadwalaysan inta lagu jiro tababarka?
- Had iyo jeer quudiya calaamadda runta ah
- Si aan kala sooc lahayn u kala doorta calaamadda runta ah iyo saadaasha moodeelka
- Wuxuu curyaamiyaa shaqada luminta si xilliyo ah
- Waxay labanlaabtaa heerka waxbarashada waqti ka dib
- Sidee bay suurtogalnimada isticmaalka calaamadda runta dhabta ah isu beddeshaa tababarka muunad la qorsheeyay?
- Waa joogto
- Hoos ayay ku bilaabataa wayna korodhaa
- Waxay ku bilaabataa sare waxayna u qudhuntaa ilaa eber
- Si aan kala sooc lahayn ayay u ruxaysaa
- Yaa soo bandhigay muunad la qorsheeyay, iyo qiyaas ahaan goorma?
- Vaswani iyo al., 2017
- Hinton iyo al., 2006
- LeCun iyo al., 1998
- Bengio et al., 2015
- Dib u dhac farsamo oo la aqoonsan yahay ee quudinta calaamadihii muunadyada ahaa ee dib loogu soo celiyay muddada tababarka ayaa ah:
- Talaabada muunada gaarka ah waa mid aan la kala sooci karin, oo adkaynaysa gradients
- Waxay ka dhigtaa tababarka mid si buuxda loo go'aamiyo
- Uma baahna xog xaqiijin
- Waxay meesha ka saartaa baahida loo qabo in la isku dhejiyo
- Jadwalka qaabkee ayaa inta badan loo soo qaatay inuu burburiyo suurtagalnimada qasabka macalinka?
- Joogto ah
- Sigmoid suus ah
- Kor u kaca toosan ee kor u kaca
- Socod random
- At a decoding step where scheduled sampling chooses the model-output branch, what is fed as the next context token?
- The next ground-truth token every time
- A token from a separate validation sequence
- A token sampled from the model’s predicted distribution
- The average of all vocabulary embeddings
- Why does scheduled sampling usually begin with a high probability of using ground truth?
- It guarantees unbiased gradients
- It removes the need for a training schedule
- It makes inference use ground-truth tokens
- Early predictions are poor, so a correct prefix can stabilize initial learning