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城ヶ崎美嘉で学ぶRNNLM
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Kento Nozawa
June 05, 2016
Programming
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城ヶ崎美嘉で学ぶRNNLM
オタク機械学習勉強会#0 のLT
Kento Nozawa
June 05, 2016
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Transcript
ϲ࡚ඒՅ Λը૾ݕࡧ͓ͯͪ͠Լ͍͞
ϲ࡚ඒՅͰֶͿ RNNLM 2016/6/5 ΦλΫػցֶशษڧձ #0 @nzw0301
Ϟνϕʔγϣϯ ϲ࡚ඒՅͷηϦϑੜ
Recurrent Neural Network Language Model • ηϦϑੜ: લ·Ͱͷ୯ޠ͔Β࣍ͷ1୯ޠΛ༧ଌ͠ଓ͚Δ • ྫɿΊΔΊΔʜᣦՅʹϝʔϧૹ৴ͬ˒
• ୯ޠׂ: <BOS> ΊΔΊΔʜᣦՅʹϝʔϧૹ৴ͬ˒&04 • ֶश: Q ΊΔΊΔc#04 ͱ͔ Q ᣦՅc<BOS>, ΊΔΊΔ ʜ
RNNLMͷߏ ޠኮV࣍ݩͷϕΫτϧ softmax ؔ 1ͭલͷதؒͷϕΫτϧ RNNͷ༝ԑ h࣍ݩͷதؒ
p(ΊΔΊΔ|<BOS>) ͷܭࢉྫɿೖྗ w #04ͷPOFPG,දݱΛೖྗ w ࣍ݩͰີͳϕΫτϧʹม <BOS> ΊΔΊΔ 0 B
B B B B @ 0 1 0 . . . 0 1 C C C C C A
p(ΊΔΊΔ|<BOS>) ͷܭࢉྫɿதؒ • ີͳϕΫτϧΛதؒʹ͢ • ଟύʔηϓτϩϯͱಉ͡ <BOS> ΊΔΊΔ
p(ΊΔΊΔ|<BOS>) ͷܭࢉྫɿग़ྗ • ग़ྗʹதؒͷϕΫτϧΛ͢ • ݱࡏͷதؒͷΛอ࣋ <BOS> ΊΔΊΔ
p(ΊΔΊΔ|<BOS>) ͷܭࢉྫɿॏΈߋ৽ • SoftmaxؔͰ֬Λܭࢉ • Backpropagation Ͱ ΊΔΊΔ ͷ͕֬େ͖͘ͳΔΑ͏ʹߋ৽ <BOS>
ΊΔΊΔ
p(ʜc#04 ΊΔΊΔ) ͷܭࢉྫɿೖྗ ૄΊΔΊΔϕΫτϧΛೖྗ͠ɼີͳΊΔΊΔϕΫτϧʹม p(ΊΔΊΔ|<BOS>)Ͱܭࢉͨ͠தؒͷϕΫτϧ ʜ ΊΔΊΔ 0 B B
B B B B B B B B @ 0 . . . 0 1 0 . . . 0 1 C C C C C C C C C C A
p(ʜc#04 ΊΔΊΔ) ͷܭࢉྫɿதؒ ີͳΊΔΊΔϕΫτϧͱલʹܭࢉͨ͠தؒͷϕΫτϧΛதؒ p(ΊΔΊΔ|<BOS>)Ͱܭࢉͨ͠தؒͷϕΫτϧ ʜ ΊΔΊΔ
p(ʜc#04 ΊΔΊΔ) ͷܭࢉྫɿग़ྗ • ग़ྗʹதؒͷϕΫτϧΛͯ͠ɼݱࡏͷதؒͷϕΫτϧΛอ࣋ p(ʜ|<BOS>, ΊΔΊΔ)Ͱܭࢉͨ͠தؒͷϕΫτϧ ʜ ΊΔΊΔ
p(ʜc#04 ΊΔΊΔ) ͷܭࢉྫɿॏΈߋ৽ • SoftmaxؔͰ֬Λܭࢉ • Backpropagation Ͱ ʜ ͷ͕֬େ͖͘ͳΔΑ͏ʹߋ৽
ʜ ΊΔΊΔ
࣮ݧ
࣮ݧ֓ཁ • SCRNΛ༻ • LSTM GRU ΛΘͳ͍ • Keras
Ͱ࣮ • લॲཧ • ܗଶૉղੳͤͣʹจࣈ୯ҐͰֶश • /。|★|?|!|♪/ ͰηϦϑΛׂ • 900ηϦϑ (Վࢺ) Λ༻ • ϞόϚε • σϨες • TOKIMEKIΤεΧϨʔτ
݁Ռ
10epochޙɿϓϩσϡʔαʔͷҰ෦͕ͱΕͯΔ ϓϩσϩσϡʔͯͳͪʙʹෲΞλ γ΄ϡʔαʔΒతͳʔɺͨ͜ͳ
40epochޙɿΪϟϧޠʁ ϓϩσϡʔαʔʹ͍ͪΌΜɺ ݟ͘ͳ͍ʔ͘ͱԿߴͩ͠ʔͬ̇
80epochޙɿݺΕͨؾ͕ͨ͠ ϓϩσϡʔαʔ!
“<BOS> ϓ” ͔Β࠷ਪఆɿϧʔϓ ϓϩσϡʔαʔɺΞλγͷ͜ͱ͔Βɺ ϓϩσϡʔαʔɺΞλγͷ͜ͱ
ϥϯμϜʹηϦϑੜ
ॴײ • ηϦϑΛͲ͜ͰΔ͖͔ • ྫɿ͝Μʹ͢Δ?͓෩࿊ʹ͢Δ?…͜ΕͪΐͬͱϕλͬΆ͍ͳ͊ • ? Ͱ۠Δ͖͔൱͔ • …લޙͲͬͪͰ۠Δ͔൱͔ʁͦΕͱͳ͘͢ʁ
• ήʔϜը໘ͷͨΊ͔1ηϦϑܥྻ͕΄΅Ұఆʢֶͼʣ
ࢀߟจݙͳͲ • http://keras.io/ • DLͷϥΠϒϥϦ • ָ͍͢͝ʹॻ͚Δ • Mikolov at.el.
Recurrent neural network based language model. 2010. • RNNͷը૾͜ͷจͷͷΛ༻ • Mikolov at.el Learning Longer Memory in Recurrent Neural Networks. 2014. • ࠓճ༻ͨ͠Ϟσϧ