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license: afl-3.0
language:
  - kk
  - en
metrics:
  - bleu

Description: finetuned mt5-base

Dataset: https://github.com/Helsinki-NLP/Tatoeba-Challenge/blob/master/data/README.md

Evaluation: BLEU EN-KK 11.5; KK-EN 22.68

If you use this model, please consider citing the paper:

E. Bekbulatov and A. Kartbayev, "A study of certain morphological structures of Kazakh and their impact on the machine translation quality," 2014 IEEE 8th International Conference on Application of Information and Communication Technologies (AICT), 2014, pp. 1-5, doi: 10.1109/ICAICT.2014.7036013.