From Bytes to Borsch: Fine-Tuning Gemma and Mistral for the Ukrainian Language Representation

Artur Kiulian, Anton Polishko, Mykola Khandoga, Oryna Chubych, Jack Connor, Raghav Ravishankar, Adarsh Shirawalmath


Abstract
In the rapidly advancing field of AI and NLP, generative large language models (LLMs) stand at the forefront of innovation, showcasing unparalleled abilities in text understanding and generation. However, the limited representation of low-resource languages like Ukrainian poses a notable challenge, restricting the reach and relevance of this technology. Our paper addresses this by fine-tuning the open-source Gemma and Mistral LLMs with Ukrainian datasets, aiming to improve their linguistic proficiency and benchmarking them against other existing models capable of processing Ukrainian language. This endeavor not only aims to mitigate language bias in technology but also promotes inclusivity in the digital realm. Our transparent and reproducible approach encourages further NLP research and development. Additionally, we present the Ukrainian Knowledge and Instruction Dataset (UKID) to aid future efforts in language model fine-tuning. Our research not only advances the field of NLP but also highlights the importance of linguistic diversity in AI, which is crucial for cultural preservation, education, and expanding AI’s global utility. Ultimately, we advocate for a future where technology is inclusive, enabling AI to communicate effectively across all languages, especially those currently underrepresented.
Anthology ID:
2024.unlp-1.11
Volume:
Proceedings of the Third Ukrainian Natural Language Processing Workshop (UNLP) @ LREC-COLING 2024
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Mariana Romanyshyn, Nataliia Romanyshyn, Andrii Hlybovets, Oleksii Ignatenko
Venue:
UNLP
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
83–94
Language:
URL:
https://aclanthology.org/2024.unlp-1.11
DOI:
Bibkey:
Cite (ACL):
Artur Kiulian, Anton Polishko, Mykola Khandoga, Oryna Chubych, Jack Connor, Raghav Ravishankar, and Adarsh Shirawalmath. 2024. From Bytes to Borsch: Fine-Tuning Gemma and Mistral for the Ukrainian Language Representation. In Proceedings of the Third Ukrainian Natural Language Processing Workshop (UNLP) @ LREC-COLING 2024, pages 83–94, Torino, Italia. ELRA and ICCL.
Cite (Informal):
From Bytes to Borsch: Fine-Tuning Gemma and Mistral for the Ukrainian Language Representation (Kiulian et al., UNLP 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.unlp-1.11.pdf