InoteveraGaidhi rinotevera
Kumiririra uye Sampling Bias muDatasets
Tekinoroji
Nhungamiro yehunyanzvi
Yakarongwa Sampling uye Exposure Bias
Exposure bias ndiyo mukaha unoonekwa kana modhi yakadzidziswa chete pazvivakamberi zvakakwana inofanira, pakufungidzira, mamiriro ezvazvinobuda zvisina kukwana.
Teerera kugwaro iriAI-yakarondedzerwa · ~2 min
Pa peji ino2 min verenga
Pfupiso
Scheduled sampling is a curriculum that gradually closes that gap.
Kudzika Kwakadzika
Mamodheru akadzidziswa nekumanikidza mudzidzisi anongoona zviratidzo-zvechokwadi semamiriro ezvinhu, asi panguva yechizvarwa vanodzosa fungidziro dzavo. Kana kukanganisa kwekutanga kwakaisa modhi munzvimbo yayaisambosangana nayo panguva yekudzidziswa, zvikanganiso zvinogona bhora rechando, nzira yekutadza inonzi exposure bias. Yakarongwa sampling, yakaunzwa naBengio uye vaanoshanda navo muna 2015, inogadzirisa izvi nekupenengura mari padanho rega rega rekunyora panguva yekudzidziswa: neimwe mukana inodyisa chiratidzo chechokwadi (kumanikidza mudzidzisi) uye neimwe nzira inodyisa iyo modhi yesampled kufanotaura. Mukana wekushandisa chokwadi chepasi unotanga pedyo neimwe uye unoora pamusoro pekudzidziswa kuburikidza nehurongwa (mutsara, exponential, kana inverse-sigmoid), saka modhi yacho inoburitswa zvishoma nezvishoma kune yayo yakabuda uye inodzidza kupora kubva mukukanganisa kwayo.
Kuitwa muNyika yeChokwadi
Kudzidzira mufananidzo-yemifananidzo ine sampling yakarongwa kuti idzidze kuenderera nenyasha mushure meshoko risina kukwana rakafanotaurwa.
Kuora mukana wekumanikidza mudzidzisi neyakasiyana-sigmoid hurongwa mune neural muchina kududzira system.
Kuongorora chatbot inonyura muzvishwe zvisina kubatana sechiratidzo chekusarura kubva kumudzidzisi akamanikidza.
Kuenzanisa zvibodzwa zveBLEU zvemuchidimbu akadzidziswa nemudzidzisi akazara achimanikidza maringe neakadzidziswa nesampling yakarongwa
Ramangwana Rezvakarongwa Sampling uye Exposure Bias
Kune mahombe emitauro yeTransformer maitiro anoshanda ekufumurwa anopokana, sezvo data hombe uye chikero chinoideredza, uye nzira dzakaita seRLHF dzinogadzirisa maitiro echizvarwa zvakananga. Zvakadaro, sampling yakarongwa uye vazukuru vayo vanoramba vakakodzera kune madiki mamodheru, yakarongeka chizvarwa, uye mabasa ane chakanyanya kurongeka zvinodiwa. Basa remangwana rinosanganisa kuratidzwa kwekharikhulamu, yekusimbisa-maitiro ekutevedzana zvinangwa, uye kushoma-njodzi kudzidziswa kuenzanirana kuti mamodheru anodzidziswa sei nemanyorero aanoita.
Kuzvishandisa
Nei zvichikosha
- Mutengo uye bhajeti. Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore.
- Sarudzo dzakajeka. Dzidzo yehunyanzvi inobatsira zvikwata kusarudza murwi wakakodzera, kwete iwo mutsva chete.
- Kudzora kwemhando yepamusoro. Sarudzo dzeinjiniya dziri nani dzinoderedza zviitiko zvekuvimbika mukugadzira.
Chenjera
- Kugadzirisa imwe bhenji kunogona kuvanza yakafara system kushaya simba.
- Infrastructure uye mari yekugadzirisa inowanzotarisirwa pasi.
- Chengetedzo uye kucherechedzwa mapundu anogona kukura sezvo masisitimu anowedzera kuoma.
Matanho anotevera
- Tsanangura latency, mhando, uye mutengo zvinangwa usati waitwa.
- Benchmark pasi pechokwadi mutoro uye data mamiriro.
- Chishandiso chekutarisa zvikanganiso, kudonha, uye mushandisi maitiro.
- Gadzirira nzira dzekudzosera kumashure uye dzezviitiko usati wawedzera.
Ramba Uchiongorora
Tsamba yemahara
Tora iyo yemazuva ese AI pfupiso
Nhatu dzakasimbiswa dzeAI nyaya mangwanani ega ega pakati pevhiki, dzakanyorwa neChirungu chakajeka. Yemahara zvachose, hapana ads.
Imwe email zuva rega rega revhiki. Bvisa kunyoresa kamwe chete. Hatimbotengese kana kugovera kero yako.
Zviedze iwe pachako
Take the Scheduled Sampling and Exposure Bias quiz
Mhinduro yepakarepo pamhinduro yega yega, uye chitupa chinogovaniswa chine ID inobatika kana wapedza kosi.
Tsigira dzidzo yemahara yeAI. AI Understanding ndeye 501(c)(3) isingabatsiri - hapana ads, hapana paywall, zvachose. Ita chipo
Mibvunzo inowanzo bvunzwa
What is Scheduled Sampling and Exposure Bias?
Exposure bias ndiyo mukaha unoonekwa kana modhi yakadzidziswa chete pazvivakamberi zvakakwana inofanira, pakufungidzira, mamiriro ezvazvinobuda zvisina kukwana. Sampling yakarongwa icurriculum inovhara iyo zvishoma nezvishoma.
Chii chinoitwa sampling yakarongwa panguva yekudzidziswa?
Sampling yakarongwa stochastically inosanganisa pasi-chokwadi uye modhi-yakagadzirwa tokens seyekuisa decoder, inodzorwa neinoora ingangove.
Ko mukana wekushandisa pasi-chokwadi chiratidzo chinoshanduka sei pane kudzidziswa mune yakarongwa sampling?
Iyo purogiramu inotanga pedyo nemudzidzisi akazara kumanikidza uye kuora kuitira kuti modhi yacho iwedzere kuratidzwa kune yayo yekufungidzira sezvainovandudza.
Ndiani akatanga sampling yakarongwa, uye riini?
Yakarongwa sampling yakakurudzirwa naSamy Bengio uye vaaishanda navo muna 2015 kuitira kuteedzana kufanotaura nema network anodzokororwa.
Ndechipi chimiro chehurongwa chinowanzo kutaurwa pakuora mukana wekumanikidza mudzidzisi?
Basa rekutanga rakakurudzira mutsara, exponential, uye inverse-sigmoid kuora marongero ekudzikisa pasi-chokwadi sampling mukana.
At a decoding step where scheduled sampling chooses the model-output branch, what is fed as the next context token?
Scheduled sampling sometimes feeds the model’s own sampled prediction instead of the gold previous token.
Ramba uchidzidza
Mazano anoenderana
Mamwe madhairekitori akasarudzirwa nyaya iyi