TURNA: A Turkish Encoder-Decoder Language Model for Enhanced Understanding and Generation
Gökçe Uludoğan, Zeynep Balal, Furkan Akkurt, Meliksah Turker, Onur Gungor, Susan Üsküdarlı
Abstract
The recent advances in natural language processing have predominantly favored well-resourced English-centric models, resulting in a significant gap with low-resource languages. In this work, we introduce TURNA, a language model developed for the low-resource language Turkish and is capable of both natural language understanding and generation tasks.TURNA is pretrained with an encoder-decoder architecture based on the unified framework UL2 with a diverse corpus that we specifically curated for this purpose. We evaluated TURNA with three generation tasks and five understanding tasks for Turkish. The results show that TURNA outperforms several multilingual models in both understanding and generation tasks and competes with monolingual Turkish models in understanding tasks.- Anthology ID:
- 2024.findings-acl.600
- Volume:
- Findings of the Association for Computational Linguistics ACL 2024
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand and virtual meeting
- Editors:
- Lun-Wei Ku, Andre Martins, Vivek Srikumar
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 10103–10117
- Language:
- URL:
- https://aclanthology.org/2024.findings-acl.600
- DOI:
- Cite (ACL):
- Gökçe Uludoğan, Zeynep Balal, Furkan Akkurt, Meliksah Turker, Onur Gungor, and Susan Üsküdarlı. 2024. TURNA: A Turkish Encoder-Decoder Language Model for Enhanced Understanding and Generation. In Findings of the Association for Computational Linguistics ACL 2024, pages 10103–10117, Bangkok, Thailand and virtual meeting. Association for Computational Linguistics.
- Cite (Informal):
- TURNA: A Turkish Encoder-Decoder Language Model for Enhanced Understanding and Generation (Uludoğan et al., Findings 2024)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2024.findings-acl.600.pdf