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README.md
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- chrf
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#
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<div align="center">
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- **Score:** 48.80 CHRF++
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- **Code:** [GitHub Repository](https://github.com/Voldisoriginal/LoResMT-2026-Russian-Bashkir)
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##
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```python
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import torch
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print(tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0])
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```
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##
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- **Hardware:** Trained on a single NVIDIA RTX 3080.
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##
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```bibtex
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}
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```
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# DevLake: M2M-100 (418M) for Russian-Bashkir
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<div align="center">
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- **Score:** 48.80 CHRF++
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- **Code:** [GitHub Repository](https://github.com/Voldisoriginal/LoResMT-2026-Russian-Bashkir)
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## Usage
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```python
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import torch
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print(tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0])
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```
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## Training Details
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- **Hardware:** Trained on a single NVIDIA RTX 3080.
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## Citation
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```bibtex
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@inproceedings{tyurin-2026-devlake,
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title = "{D}ev{L}ake at {L}o{R}es{MT} 2026: The Impact of Pre-training and Model Scale on {R}ussian-{B}ashkir Low-Resource Translation",
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author = "Tyurin, Vyacheslav",
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booktitle = "Proceedings for the Ninth Workshop on Technologies for Machine Translation of Low Resource Languages (LoResMT 2026)",
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month = mar,
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year = "2026",
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address = "Rabat, Morocco",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2026.loresmt-1.18",
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doi = "10.18653/v1/2026.loresmt-1.18",
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pages = "209--212",
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}
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```
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