Dubawa
Adam shine mai inganta dokin aiki a bayan yawancin hanyoyin sadarwa na zamani, yana daidaita ƙimar koyo ta atomatik ga kowane siga. Yana da mahimmanci saboda yana sa ƙirar ƙira mai zurfi da sauri kuma ba ta da ƙarfi fiye da zuriyar gradient.
Adam and Adaptive Optimizers wani shingen gini ne na fasaha wanda ke shafar ingancin samfuri, tsadar ababen more rayuwa, jinkiri, da aminci a sikeli.
Zurfafa nutsewa
Adam (Adaptive Moment Estimation), wanda Kingma da Ba suka gabatar a cikin 2014, ya haɗa ra'ayoyi biyu. Na farko, kuzari: yana kiyaye matsakaicin ruɓewa na ɓangarorin abubuwan da suka wuce (lokacin farko) don haka sabuntawa suna haɓaka gudu cikin madaidaiciyar kwatance. Na biyu, sikelin kowane siga: yana bin matsakaicin matsakaicin murabba'in gradients (lokaci na biyu) kuma yana rarraba kowane mataki da tushen murabba'in waccan darajar, don haka sigogi tare da manyan gradients masu hayaniya suna ɗaukar ƙananan matakai kuma waɗanda ba a sabunta su ba suna ɗaukar matakai mafi girma. Wannan daidaitawa yana nufin sau da yawa zaka iya amfani da ƙimar koyo guda ɗaya a duk hanyar sadarwa. Bambance-bambancen, AdamW, yana kawar da lalata nauyi daga sabuntawar gradient kuma ya zama tsoho don horar da manyan tashoshi da ƙirar harshe.
Fahimtar Fasaha
Adamu yana kula da matsakaita guda biyu a kowace siga: m (gradients) da v (squared gradients), sabuntawa tare da ƙimar lalata beta1 (yawanci 0.9) da beta2 (yawanci 0.999). Domin duka biyun suna farawa daga sifili, ana gyara son zuciya ta hanyar rarraba ta (1 - beta ^ t). Sabuntawa shine theta = theta - lr * m_hat / (sqrt (v_hat) + epsilon), inda epsilon (a kusa da 1e-8) yana hana rarraba ta sifili. Wannan shine dalilin da ya sa Adamu yana buƙatar ƙaramin daidaita ƙimar koyo idan aka kwatanta da SGD a sarari.
Mastering Adam da Adaptive Optimizers
Adam shine mai inganta dokin aiki a bayan yawancin hanyoyin sadarwa na zamani, yana daidaita ƙimar koyo ta atomatik ga kowane siga. Yana da mahimmanci saboda yana sa ƙirar ƙira mai zurfi da sauri kuma ba ta da ƙarfi fiye da zuriyar gradient. Adam and Adaptive Optimizers wani shingen gini ne na fasaha wanda ke shafar ingancin samfuri, tsadar ababen more rayuwa, jinkiri, da aminci a sikeli. Don gina fahimta mai zurfi, bi Adam da Masu haɓakawa masu daidaitawa azaman ƙirar aiki, ba fasali ɗaya ba: ayyana sakamakon da ake so, fayyace zato, da raba abin da tsarin zai iya yi da dogaro daga abin da har yanzu ke buƙatar yanke hukunci na ƙwararru.
A aikace, ƙungiyoyi masu ƙarfi da ke amfani da Adam da Masu haɓakawa Adawa suna haɓaka gine-gine, bayanai, da zaɓin abubuwan more rayuwa tare da dogaro da farashi. Suna rubuta ƙayyadaddun ƙa'idodin nasara, gwaji akan bayanan gaskiya da gudanawar aiki, da jujjuyawar bisa ga tsarin gazawar da aka lura maimakon cin nasara na lokaci ɗaya. Wannan shine inda fahimtar ka'idar ta juya zuwa iyawa mai dorewa a cikin samfura, manufofi, da ayyuka.
Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru. A lokaci guda, Haɓaka ma'auni ɗaya na iya ɓoye manyan raunin tsarin. Hanyar da ta fi dacewa ita ce haɗa saurin gwaji tare da horon gudanarwa: gudanar da matukin jirgi, kama shaida, buga rajistan ayyukan yanke shawara, da ci gaba da sabunta abubuwan tsaro kamar yadda halayen ƙira, tsammanin mai amfani, da buƙatun tsari ke tasowa.
Dabarun Tasiri
Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru.
Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Ilimin fasaha yana taimaka wa ƙungiyoyi su zaɓi tari mai kyau, ba kawai sabon abu ba.
Ilimin fasaha yana taimaka wa ƙungiyoyi su zaɓi tari mai kyau, ba kawai sabon abu ba. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Zaɓuɓɓukan injiniya mafi kyau suna rage abin dogaro a cikin samarwa.
Zaɓuɓɓukan injiniya mafi kyau suna rage abin dogaro a cikin samarwa. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Aiwatar da Gaskiyar Duniya
Horar da manyan nau'ikan harshe kamar GPT da Llama, waɗanda ke amfani da AdamW azaman madaidaicin ingantawa.
Kyakkyawan daidaita ma'aunin hoto da aka riga aka horar (misali, ResNet) akan saitin bayanai na al'ada tare da tsayayyen ƙimar koyan Adam.
Horar da samfuran watsawa a bayan masu samar da hoto kamar Stable Diffusion.
Gudun 8-bit Adam a cikin ɗakunan karatu kamar bitsandbytes don dacewa da jihohin ingantawa cikin ƙayyadaddun ƙwaƙwalwar GPU.
Hanyoyin Aiwatarwa
Adam and Adaptive Optimizers a aikace
Horar da manyan nau'ikan harshe kamar GPT da Llama, waɗanda ke amfani da AdamW azaman madaidaicin ingantawa.
Horar da manyan nau'ikan harshe kamar GPT da Llama, waɗanda ke amfani da AdamW azaman madaidaitan Ƙungiyoyin ingantawa yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ƙofofin inganci a gaba, kiyaye hanyar haɓakar ɗan adam don shari'o'i, da bin diddigin nasarorin samarwa da ƙimar kuskure akan lokaci.
Adam and Adaptive Optimizers a aikace
Kyakkyawan daidaita ma'aunin hoto da aka riga aka horar (misali, ResNet) akan saitin bayanai na al'ada tare da tsayayyen ƙimar koyan Adam.
Kyawawan gyare-gyaren rarrabuwar hoto da aka riga aka horar (misali, ResNet) akan saitin bayanan al'ada tare da tsohowar ƙimar koyon Adam Ƙungiyoyi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don shari'o'in gefe, da bin diddigin nasarorin samarwa da tsadar kurakurai a kan lokaci.
Adam and Adaptive Optimizers a aikace
Horar da samfuran watsawa a bayan masu samar da hoto kamar Stable Diffusion.
Horar da samfuran watsawa a bayan masu samar da hoto kamar Stable Diffusion Teams yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don shari'o'in gefe, da bin duk nasarorin samarwa da farashi na kuskure akan lokaci.
Adam and Adaptive Optimizers a aikace
Gudun 8-bit Adam a cikin ɗakunan karatu kamar bitsandbytes don dacewa da jihohin ingantawa cikin ƙayyadaddun ƙwaƙwalwar GPU.
Gudun 8-bit Adam a cikin ɗakunan karatu kamar bitsandbytes don dacewa da jihohi masu ingantawa cikin iyakantattun Ƙungiyoyin ƙwaƙwalwar ajiya na GPU yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don ƙararraki, da bin diddigin nasarorin samarwa da ƙimar kuskure akan lokaci.
Hatsari & Tsare-tsare
Haɓaka ma'auni ɗaya na iya ɓoye manyan raunin tsarin.
Sau da yawa ana raina kayan more rayuwa da kuma kuɗin kulawa.
Tsaro da gibin lura na iya girma yayin da tsarin ke ƙara haɓaka.
Taswirar Hanya
Ƙayyade latency, inganci, da maƙasudin farashi kafin aiwatarwa.
Ƙayyade latency, inganci, da maƙasudin farashi kafin aiwatarwa. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Alamar ma'auni a ƙarƙashin ainihin kaya da yanayin bayanai.
Alamar ma'auni a ƙarƙashin ainihin kaya da yanayin bayanai. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Kula da kayan aiki don kurakurai, ɗigo, da tasirin mai amfani.
Kula da kayan aiki don kurakurai, ɗigo, da tasirin mai amfani. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Shirya bijirowa da hanyoyin mayar da martani kafin sikeli.
Shirya bijirowa da hanyoyin mayar da martani kafin sikeli. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.