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Introducing cosmosGPT: Monolingual Training for Turkish Language Models

dc.contributor.authorKesgin, H. Toprak
dc.contributor.authorYuce, M. Kaan
dc.contributor.authorDogan, Eren
dc.contributor.authorUzun, M. Egemen
dc.contributor.authorUz, Atahan
dc.contributor.authorSeyrek, H. Emre
dc.contributor.authorZeer, Ahmed
dc.contributor.authorAmasyali, M. Fatih
dc.date.accessioned2026-06-27T14:58:20Z
dc.date.issued2024
dc.description.abstractThe number of open source language models that can produce Turkish is increasing day by day, as in other languages. In order to create the basic versions of such models, the training of multilingual models is usually continued with Turkish corpora. The alternative is to train the model with only Turkish corpora. In this study, we first introduce the cosmosGPT models that we created with this alternative method. Then, we introduce new finetune datasets for basic language models to fulfill user requests and new evaluation datasets for measuring the capabilities of Turkish language models. Finally, a comprehensive comparison of the adapted Turkish language models on different capabilities is presented. The results show that the language models we built with the monolingual corpus have promising performance despite being about 10 times smaller than the others.en
dc.description.sponsorshipGoogle's TPU Research Cloud (TRC)
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [124E055]
dc.description.urihttps://doi.org/10.1109/inista62901.2024.10683863
dc.identifier.doi10.1109/inista62901.2024.10683863
dc.identifier.isbn979-8-3503-6813-0
dc.identifier.issn2380-9337
dc.identifier.urihttps://hdl.handle.net/20.500.14981/66599
dc.identifier.wos001329858400046
dc.language.isoeng
dc.publisherIEEE
dc.relation.conference18th International Conference on Innovations in Intelligent Systems and Applications (INISTA)
dc.relation.ispartof2024 INTERNATIONAL CONFERENCE ON INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS, INISTA
dc.subjectturkish language models
dc.subjectlarge language models
dc.subjectinstruction-finetuning
dc.subjectevaluation datasets
dc.subjectLLM performance comparison
dc.subjectnatural language processing
dc.subjectTurkish NLP
dc.subjectComputer Science
dc.subjectTelecommunications
dc.titleIntroducing cosmosGPT: Monolingual Training for Turkish Language Models
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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