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ZeRO uye Sharded Optimizers
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Adam uye Adaptive Optimizers
Adam ndiye workhorse optimizer kuseri kweakawanda azvino neural network, achigadzirisa otomatiki mwero wekudzidza wakasiyana kune yega paramita.
Teerera kugwaro iriAI-yakarondedzerwa · ~2 min
Pa peji ino2 min verenga
Pfupiso
Izvo zvine basa nekuti inoita kuti kudzidzisa kwakadzama modhi ikurumidze uye kushoma zvakanyanya kupfuura plain gradient descent.
Kudzika Kwakadzika
Adam (Adaptive Moment Estimation), yakaunzwa naKingma naBa mu2014, inosanganisa pfungwa mbiri. Chekutanga, kusimba: inochengeta yakawedzera kuora avhareji yeakapfuura gradients (nguva yekutanga) saka zvigadziriso zvinovaka kumhanya munzira dzinoenderana. Chechipiri, per-parameta kuyera: inoteedzera avhareji yemasikweya gradients (nguva yechipiri) uye inokamura nhanho imwe neimwe neskweya mudzi weiyo kukosha, saka maparamita ane hombe, ane ruzha gradients anotora matanho madiki uye kashoma-akagadziridzwa anotora matanho akakura. Uku kuchinjika kunoreva kuti iwe unogona kazhinji kushandisa mwero wekudzidza muinetiweki yese. Musiyano, AdamW, unobvisa huremu hwekuora kubva kune gradient yekuvandudza uye yave iyo yekusarudzika yekudzidzisa matransformer makuru uye mhando dzemitauro.
Kuitwa muNyika yeChokwadi
Kudzidzisa mhando dzemitauro mikuru seGPT neLlama, iyo inoshandisa AdamW seyakajairwa optimizer.
Kunyatsogadzirisa dhizaini yemufananidzo yakadzidziswa (semuenzaniso, ResNet) pane yakasarudzika dhatabheti ine yakasarudzika chiyero chekudzidza kwaAdhamu.
Kudzidzira madhizaini modhi kuseri kwemifananidzo jenareta seStable Diffusion.
Kumhanya 8-bit Adamu mumaraibhurari akaita sebitandbytes kuti ikwane optimizer nyika mune shoma GPU ndangariro.
Ramangwana raAdhamu neAdaptive Optimizers
Adamu naAdamW vanoramba vaine masimba, asi tsvagiridzo iri kusundira kushanda kwematrion-parameter modhi, uko kuchengetedza maviri ekuwedzera kukosha pahuremu kunodhura. Memory-light variants seAdafactor, 8-bit Adam, uye nyowani optimizers seShumba (iyo inoshandisa chete sign-based momentum) uye Sophia anovavarira kuenzanisa hunhu hwaAdhamu nendangariro shoma kana kukurumidza kusangana. Tarisira ma adaptive optimizers akarongedzerwa akagoverwa, yakaderera-chaiyo kudzidziswa kuti irambe ichishanduka.
Kuzvishandisa
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Chenjera
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- Infrastructure uye mari yekugadzirisa inowanzotarisirwa pasi.
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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
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Take the Adam and Adaptive Optimizers quiz
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Chii chinonzi Adam uye Adaptive Optimizers?
Adam ndiye workhorse optimizer kuseri kweakawanda azvino neural network, achigadzirisa otomatiki mwero wekudzidza wakasiyana kune yega paramita. Izvo zvine basa nekuti inoita kuti kudzidzisa kwakadzama modhi ikurumidze uye kushoma zvakanyanya kupfuura plain gradient descent.
Ndeapi uwandu huviri hunotevedzwa naAdam paparameter yega yega?
Adamu anochengeta avhareji iri kuora zvakanyanya yeavhareji (nguva yekutanga) uye yeakaenzana magiradhi (nguva yechipiri) kune yega paramita.
Nei Adhama achishandisa kururamisa kwakarerekera kune fungidziro yake yenguva?
Ose m uye v anotangwa kuenda ku zero, saka fungidziro dzekutanga dzakarerekera pasi; kupatsanura ne (1 - beta^t) inogadzirisa izvi.
Ndeupi musiyano mukuru pakati paAdam naAdamW?
AdamW inoshandisa kuora kwehuremu zvakananga kune huremu kwete kuisanganisa mune inogadzirisa gradient term, iyo inovandudza generalization mumashanduri.
Ibasa rei iro diki epsilon inobata mumutemo wekuvandudza waAdam?
Epsilon (yakatenderedza 1e-8) inowedzerwa kune dhinominata kuitira kuti paramita dzine pedyo-zero squared-gradient maavhareji arege kukonzera kuputika.
Nei Adhamu achiwanzorondedzerwa se'anochinja'?
Nekukamura neskweya mudzi weparameta yega yega-skwea-gradient avhareji, Adamu anoyera saizi yenhanho paparameta pane kushandisa kukosha kwepasirese.
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