Overview
Boka Relative Policy Optimization (GRPO) inzira yekusimbisa-yekudzidza yemhando dzemitauro inotonga mhinduro yega yega vachipokana neboka rehama mhinduro kune imwecheteyo kukurumidza, kubvisa yakaparadzana kukosha network inoshandiswa nePPO. Yakava nemukurumbira seyakanyanya kudzidzisa trick kuseri kweDeepSeek's kufunga modhi.
Boka Relative Policy Optimization inzvimbo yekuvaka yehunyanzvi inobata mhando yemhando, mutengo wezvivakwa, latency, uye kuvimbika pachiyero.
Deep Dive
GRPO musiyano wepolicy-gradient kusimbisa kudzidza kwakagadzirirwa kuita RL kugadzirisa zvakanaka kwemhando dzemitauro mikuru kudhura uye kugadzikana. PPO yakajairwa inoda akadzidza 'anotsoropodza' (value modhi), zvakakura segwaro racho pacharo, kufungidzira kunaka kwechiratidzo chega chega. GRPO inobvisa mutsoropodzi uyu zvachose. Pakuchimbidza kwega kwega inoisa sampuli boka rekupedzisa (inoti 8-64), inovaverengera vese nechiratidzo chemubairo, uyezve inoverengera mukana wekupedzisa kwega kwega nekuenzanisa mubairo wayo zvichienderana nekurevesa kweboka uye kutsauka kwakajairwa. Pamusoro-avhareji mhinduro dzinosimbiswa uye dzepasi-avhareji dzakatsikirirwa. Izwi reKL-divergence rinochengeta modhi iri padyo nereferensi mutemo. Yakaunzwa neDeepSeek, yakapa simba DeepSeekMath uye iyo DeepSeek-R1 yekufunga modhi.
Technical Insight
Pfungwa yakakosha kutsiva PPO's yakadzidza kukosha baseline neMonte Carlo boka yekutanga. Kune boka rezvabuda nemubairo r_i, mukana wega wega A_i = (r_i - zvinoreva (r)) / std(r). Icho chibodzwa chakajairwa chinowedzera chiyero chakachekwa, sezvakaita muPPO, uye chirango cheKL chinopesana nechando chereferensi modhi curbs kudonha. Nekuti hapana mutsoropodzi akadzidziswa, ndangariro uye compute ingangoita hafu, uye iyo-yekukurumidza kusimudzira inopa yakasarudzika yakayerwa, yakaderera-musiyano mabhenefiti.
Mastering Group Relative Policy Optimization
Boka Relative Policy Optimization (GRPO) inzira yekusimbisa-yekudzidza yemhando dzemitauro inotonga mhinduro yega yega vachipokana neboka rehama mhinduro kune imwecheteyo kukurumidza, kubvisa yakaparadzana kukosha network inoshandiswa nePPO. Yakava nemukurumbira seyakanyanya kudzidzisa trick kuseri kweDeepSeek's kufunga modhi. Boka Relative Policy Optimization inzvimbo yekuvaka yehunyanzvi inobata mhando yemhando, mutengo wezvivakwa, latency, uye kuvimbika pachiyero. Kuti uvake kunzwisisa kwakadzama, bata Boka Relative Policy Optimization semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvaunoda, tsanangura fungidziro, uye patsanura izvo zvinogona kuitwa nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Boka Relative Policy Optimization inokwidziridza zvivakwa, data, uye sarudzo dzezvivakwa zvinopesana nekuvimbika uye mutengo. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore. Panguva imwecheteyo, Kukwirisa imwe bhenji kunogona kuvanza yakafara system kushaya simba. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore.
Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Dzidzo yehunyanzvi inobatsira zvikwata kusarudza murwi wakakodzera, kwete iwo mutsva chete.
Dzidzo yehunyanzvi inobatsira zvikwata kusarudza murwi wakakodzera, kwete iwo mutsva chete. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Sarudzo dzeinjiniya dziri nani dzinoderedza zviitiko zvekuvimbika mukugadzira.
Sarudzo dzeinjiniya dziri nani dzinoderedza zviitiko zvekuvimbika mukugadzira. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Kudzidzisa DeepSeek-R1 uye DeepSeekMath kuburitsa refu ketani-ye-yekufunga kufunga uchishandisa mutemo-wakavakirwa kurongeka mibairo pamatambudziko esvomhu.
Yakanaka-tuning kodhi-chizvarwa modhi apo yega yega mhinduro inopihwa kana ichipfuura bvunzo dzeyuniti, uye boka rinojairwa kusarudza vanokunda.
Open-source RLHF mapaipi (semuenzaniso, muTRL uye verl maraibhurari) uchishandisa GRPO kurongedza mhando dzekutaura pasina kubhadhara kune yakaparadzana kukosha network.
Kuvandudza kuraira-kutevera kana kuchengetedza maitiro nekuenzanisa akati wandei mhinduro nekukasira uye kupa mubairo iwo mubairo wemubairo mitengo yepamusoro kune vezera ravo.
Maitiro Ekuita
Boka Relative Policy Optimization mukuita
Kudzidzisa DeepSeek-R1 uye DeepSeekMath kuburitsa refu cheni-ye-yekufunga kufunga uchishandisa mutemo-wakavakirwa kurongeka mibairo pamatambudziko esvomhu.
Kudzidzisa DeepSeek-R1 uye DeepSeekMath kuburitsa chain-ye-pfungwa yekufunga uchishandisa mutemo-wakavakirwa kurongeka mibairo pamatambudziko esvomhu Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Boka Relative Policy Optimization mukuita
Yakanaka-tuning kodhi-yechizvarwa modhi apo yega yega sample mhinduro inopihwa kana ikapasa bvunzo dzeyuniti, uye boka rinojairwa kusarudza vanokunda.
Yakanaka-tuning kodhi-yechizvarwa modhi uko yega yega mhinduro inopihwa kana ichipfuura bvunzo dzeyuniti, uye boka rinojairwa kusarudza vanokunda Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura mhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Boka Relative Policy Optimization mukuita
Open-source RLHF mapaipi (semuenzaniso, muTRL uye verl maraibhurari) uchishandisa GRPO kurongedza mhando dzekutaura pasina kubhadhara kune yakaparadzana kukosha network.
Yakavhurika-sosi RLHF mapaipi (semuenzaniso, muTRL uye verl maraibhurari) uchishandisa GRPO kuenzanisa mhando dzekutaura pasina kubhadhara kune yakaparadzana kukosha network Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Boka Relative Policy Optimization mukuita
Kuvandudza kuraira-kutevera kana kuchengetedza maitiro nekuenzanisa akati wandei mhinduro nekukasira uye kupa mubairo iwo emubairo wemhando yepamusoro inoenderana nevezera ravo.
Kuvandudza dzidziso-kutevera kana hunhu hwekuchengetedza nekutora mhinduro dzakati wandei nekukasira uye kupa mubairo iwo emhando yepamusoro-soro kune vezera ravo Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura hunhu hwepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
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.
Implementation Roadmap
Tsanangura latency, mhando, uye mutengo zvinangwa usati waitwa.
Tsanangura latency, mhando, uye mutengo zvinangwa usati waitwa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Benchmark pasi pechokwadi mutoro uye data mamiriro.
Benchmark pasi pechokwadi mutoro uye data mamiriro. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Chishandiso chekutarisa zvikanganiso, kudonha, uye mushandisi maitiro.
Chishandiso chekutarisa zvikanganiso, kudonha, uye mushandisi maitiro. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Gadzirira nzira dzekudzosera kumashure uye dzezviitiko usati wawedzera.
Gadzirira nzira dzekudzosera kumashure uye dzezviitiko usati wawedzera. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.