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You're reading from  Mastering Transformers

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Published inSep 2021
PublisherPackt
ISBN-139781801077651
Edition1st Edition
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Authors (2):
Savaş Yıldırım
Savaş Yıldırım
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Savaş Yıldırım

Savaş Yıldırım graduated from the Istanbul Technical University Department of Computer Engineering and holds a Ph.D. degree in Natural Language Processing (NLP). Currently, he is an associate professor at the Istanbul Bilgi University, Turkey, and is a visiting researcher at the Ryerson University, Canada. He is a proactive lecturer and researcher with more than 20 years of experience teaching courses on machine learning, deep learning, and NLP. He has significantly contributed to the Turkish NLP community by developing a lot of open source software and resources. He also provides comprehensive consultancy to AI companies on their R&D projects. In his spare time, he writes and directs short films, and enjoys practicing yoga.
Read more about Savaş Yıldırım

Meysam Asgari- Chenaghlu
Meysam Asgari- Chenaghlu
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Meysam Asgari- Chenaghlu

Meysam Asgari-Chenaghlu is an AI manager at Carbon Consulting and is also a Ph.D. candidate at the University of Tabriz. He has been a consultant for Turkey's leading telecommunication and banking companies. He has also worked on various projects, including natural language understanding and semantic search.
Read more about Meysam Asgari- Chenaghlu

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Translation language modeling and cross-lingual knowledge sharing

So far, you have learned about Masked Language Modeling (MLM) as a cloze task. However, language modeling using neural networks is divided into three categories based on the approach itself and its practical usage, as follows:

  • MLM
  • Causal Language Modeling (CLM)
  • Translation Language Modeling (TLM)

It is also important to note that there are other pre-training approaches such as Next Sentence Prediction (NSP) and Sentence Order Prediction (SOP) too, but we just considered token-based language modeling. These three are the main approaches that are used in the literature. MLM, described and detailed in previous chapters, is a very close concept to a cloze task in language learning.

CLM is defined by predicting the next token, which is followed by some previous tokens. For example, if you see the following context, you can easily predict the next token:

<s>...

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Mastering Transformers
Published in: Sep 2021Publisher: PacktISBN-13: 9781801077651

Authors (2)

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Savaş Yıldırım

Savaş Yıldırım graduated from the Istanbul Technical University Department of Computer Engineering and holds a Ph.D. degree in Natural Language Processing (NLP). Currently, he is an associate professor at the Istanbul Bilgi University, Turkey, and is a visiting researcher at the Ryerson University, Canada. He is a proactive lecturer and researcher with more than 20 years of experience teaching courses on machine learning, deep learning, and NLP. He has significantly contributed to the Turkish NLP community by developing a lot of open source software and resources. He also provides comprehensive consultancy to AI companies on their R&D projects. In his spare time, he writes and directs short films, and enjoys practicing yoga.
Read more about Savaş Yıldırım

author image
Meysam Asgari- Chenaghlu

Meysam Asgari-Chenaghlu is an AI manager at Carbon Consulting and is also a Ph.D. candidate at the University of Tabriz. He has been a consultant for Turkey's leading telecommunication and banking companies. He has also worked on various projects, including natural language understanding and semantic search.
Read more about Meysam Asgari- Chenaghlu