Nlereanya ahaziri ahazi na nhụsianya
Nhụsianya mkpughe bụ oghere na-apụta mgbe ụdị zụrụ naanị na prefixes zuru oke ga-abụrịrị, n'echiche, ọnọdụ na nsonaazụ ezughị oke nke ya.
Nchịkọta
Scheduled sampling is a curriculum that gradually closes that gap.
Ime miri emi
Modelsdị ndị a zụrụ azụ site na ịmanye onye nkuzi naanị na-ahụta akara ala-eziokwu dị ka ihe gbara ya gburugburu, mana n'oge ọgbọ ha na-azụghachi amụma nke ha. Mgbe mmejọ mbụ rutere ihe nlereanya ahụ n'ọnọdụ ọ na-ahụtụbeghị n'oge ọzụzụ, mmejọ nwere ike ịkụ snowball, ọnọdụ ọdịda nke a na-akpọ nhụsianya mkpughe. Nlele ahaziri ahazi, nke Bengio na ndị ọrụ ibe webatara na 2015, na-ekwu nke a site n'ịtụgharị mkpụrụ ego na usoro ngbanwe ọ bụla n'oge ọzụzụ: na ụfọdụ ihe gbasara nke puru omume ọ na-enye ezi akara (ịmanye onye nkuzi) ma ọ bụghị ya, ọ na-enye amụma amụma nke ihe nlereanya ahụ. Ihe gbasara nke puru omume iji eziokwu nke ala na-amalite nso ma na-emebi ọzụzụ site na nhazi oge (linear, exponential, ma ọ bụ inverse-sigmoid), ya mere ihe nlereanya ahụ na-eji nwayọọ nwayọọ kpughee ihe nke ya ma mụta ịghachite na mmejọ ya.
Nghọta nka nka
Na nzọụkwụ t nlereanya samples a Bernoulli variable na ihe gbasara nke puru omume epsilon_i nke ịhọrọ ọla edo token; epsilon_i rere ka ọzụzụ na-aga n'ihu. Ihe dị nhịahụ bụ na inye akara ngosi atụpụtara na-eme ka ebumnobi ahụ bụrụ nke na-enweghị isi yana nleba anya enweghị ihe dị iche, yabụ gradients anaghị aga nke ọma site na akara azụ azụ. Ndị dị iche iche na-eji Gumbel-softmax kwụ ọtọ ma ọ bụ ezumike dị iche iche iji belata nke a, na usoro usoro na-ebuli metric dị ka BLEU ozugbo.
Mmetụta atụmatụ
Ọnụ ego na mmefu ego
Mkpebi ihe owuwu ụlọ na-akwalite arụmọrụ yana ọnụ ahịa ọrụ ruo ọtụtụ afọ.
Mkpebi doro anya
Nkà mmụta nka na-enyere ndị otu egwuregwu aka ịhọrọ nchịkọta ziri ezi, ọ bụghị naanị nke kachasị ọhụrụ.
Quality akara
Nhọrọ injinia ka mma na-ebelata ihe omume ntụkwasị obi na mmepụta.
Ọdịnihu nke nlere anya akwadoro na nhụsianya mkpughe
Maka nnukwu ụdị asụsụ Transformer, a na-arụrịta ụka banyere mmetụta bara uru nke nhụsianya mkpughe, ebe ọ bụ na nnukwu data na ọnụ ọgụgụ na-ebelata ya, yana ụzọ dịka RLHF na-emegharị omume ọgbọ ozugbo. N'agbanyeghị nke ahụ, nlere anya nke ahaziri na ụmụ ya ka dị mkpa maka obere ụdị, ọgbọ ahaziri ahazi, yana ọrụ ndị nwere mkpa ziri ezi. Ọrụ ga-eme n'ọdịnihu na-agwakọta mkpughe usoro ọmụmụ, ebumnobi ụdị agbam ume, yana ọzụzụ ihe egwu kacha nta iji kwado ka esi zụọ ụdị na otu ha si ewepụta koodu.
Mmejuputa n'ezie n'ụwa
Ọzụzụ ihe atụ-ese onyinyo na nhazi nhazi ka ọ mụta ịga n'ihu n'ọmarịcha mgbe okwu amụma ezughị oke.
Na-emebi ihe gbasara omume na-amanye onye nkuzi site na usoro sigmoid inverse-sigmoid na sistemụ ntụgharị igwe akwara.
Ịchọpụta ihe nkata nkata nke na-abanye n'ime loops na-enweghị isi dị ka ihe nhụta mkpughe sitere na mmanye onye nkuzi dị ọcha.
Na-atụnyere ọtụtụ BLEU nke nchịkọta ihe zụrụ ya na onye nkuzi zuru oke na-amanye karịa nke a zụrụ azụ na nlele ahaziri.
Ihe ize ndụ & okporo ụzọ nche
Ịkwalite otu akara ngosi nwere ike zoo adịghị ike sistemụ sara mbara.
A na-eledakarị ihe akụrụngwa na ụgwọ ọrụ anya.
Ọdịiche nchekwa na nleba anya nwere ike itolite ka sistemu na-adịwanye mgbagwoju anya.
Map mmejuputa
Kọwaa latency, ịdịmma na ebumnuche ọnụ ahịa tupu mmejuputa ya.
Benchmark n'okpuru ibu dị adị na ọnọdụ data.
Nleba anya akụrụngwa maka mperi, ịkpafu na mmetụta onye ọrụ.
Kwadebe ụzọ nzaghachi azụghachi azụ na ihe omume tupu ịchachaa.
Nọgide na-eme nchọpụta
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Ntuziaka na-esote
Nlele na-adịghị mma na ntule dị iche iche nke mkpọtụ
Ajụjụ a na-ajụkarị
What is Scheduled Sampling and Exposure Bias?
Nhụsianya mkpughe bụ oghere na-apụta mgbe ụdị zụrụ naanị na prefixes zuru oke ga-abụrịrị, n'echiche, ọnọdụ na nsonaazụ ezughị oke nke ya. Nlere anya ahaziri bụ usoro ọmụmụ nke na-eji nwayọ mechie oghere ahụ.
Kedu ihe nlele ahaziri na-eme n'oge ọzụzụ?
Nlele ahaziri ahazi na-agwakọta eziokwu ala yana ihe nlebanya ewepụtara dị ka ntinye decoder, nke nwere ike ire ere na-achịkwa.
Kedu ka ihe gbasara nke puru omume iji akara-eziokwu nke ala si agbanwe n'ọzụzụ n'ime nhazi nhazi?
Oge nhazi oge na-amalite nso nsonye onye nkuzi zuru oke na-amanye na ire ere ka ihe nlereanya ahụ na-agbasawanye na amụma nke ya ka ọ na-akawanye mma.
Kedu onye webatara nlele ahaziri, ma olee mgbe?
Samy Bengio na ndị ọrụ ibe ha tụpụtara n'usoro n'usoro n'usoro amụma ya na netwọk na-aga n'ihu.
Kedu ụdị nhazi oge a na-ekwukarị maka imebi ihe omume ịmanye onye nkuzi?
Ọrụ mbụ ahụ tụrụ aro usoro ire ere linear, exponential, na inverse-sigmoid maka ibelata ohere nlele ala-eziokwu.