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  ## TL;DR & Quick results
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- Try it on [Space demo](https://huggingface.co/spaces/XSkills/nllb-turkmen-english) Article with full technical journey is available [Medium]().
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- ### Test Results
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- | Direction | BLEU ↑ | chrF ↑ | TER ↓ | Test pairs |
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- |-----------|-------:|-------:|------:|-----------:|
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- | **tk → en** | **26.07** | 52.97 | 68.39 | 50 |
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- | **en → tk** | **8.13** | 39.39 | 87.30 | 50 |
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  ### Model Comparison (Fine-tuned vs Original)
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- ### tk en (Turkmen to English)
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- | Metric | Fine-tuned | Original |
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- |--------|-----------|----------|
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- | BLEU | 26.07 | 26.48 |
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- | chrF | 52.97 | 52.91 |
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- | TER | 68.39 | 69.70 |
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- #### tk → en (Turkmen to English)
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- | Metric | Fine-tuned | Original |
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- |--------|-----------|----------|
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- | BLEU | 26.07 | 26.48 |
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- | chrF | 52.97 | 52.91 |
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- | TER | 68.39 | 69.70 |
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  *Scores computed with sacre BLEU 2.5, chrF, TER on the official `test` split.
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  A separate spreadsheet with **human adequacy/fluency ratings** is available in the article.*
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  - Gender/ politeness nuances not guaranteed.
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  - CC-BY-NC licence forbids commercial use; respect Meta’s original terms.
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  ## Citation
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  ```bibtex
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  @misc{durdyyev2025turkmenNLLBLoRA,
 
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  ## TL;DR & Quick results
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+ Try it on [Space demo](https://huggingface.co/spaces/XSkills/nllb-turkmen-english) Article with full technical journey is available [Medium](https://medium.com/@meinnps/fine-tuning-nllb-200-with-lora-on-a-650-sentence-turkmen-english-corpus-082f68bdec71).
 
 
 
 
 
 
 
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  ### Model Comparison (Fine-tuned vs Original)
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+ #### English to Turkmen
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+ | Metric | Fine-tuned | Original | Difference |
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+ |---------------------------|-----------:|---------:|-----------:|
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+ | **BLEU** | 8.24 | 8.12 | +0.12 |
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+ | **chrF** | 39.55 | 39.46 | +0.09 |
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+ | **TER (lower is better)** | 87.20 | 87.30 | -0.10 |
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+ #### Turkmen to English
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+ | Metric | Fine-tuned | Original | Difference |
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+ |---------------------------|-----------:|---------:|-----------:|
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+ | **BLEU** | 25.88 | 26.48 | -0.60 |
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+ | **chrF** | 52.71 | 52.91 | -0.20 |
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+ | **TER (lower is better)** | 67.70 | 69.70 | -2.00 |
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  *Scores computed with sacre BLEU 2.5, chrF, TER on the official `test` split.
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  A separate spreadsheet with **human adequacy/fluency ratings** is available in the article.*
 
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  - Gender/ politeness nuances not guaranteed.
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  - CC-BY-NC licence forbids commercial use; respect Meta’s original terms.
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+ ## How to Contribute
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+ We welcome contributions to improve Turkmen-English translation capabilities! Here's how you can help:
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+ ### Data Contributions
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+ - **Read Dataset Contribution**: You can find the instructions for contributing to the dataset at [Dataset Readme](https://huggingface.co/datasets/XSkills/turkmen_english_s500/blob/main/README.md)
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+
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+ ### Code Contributions
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+ - **Hyperparameter experiments**: Try different LoRA configurations and document your results
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+ - **Evaluation**: Help with human evaluation of translation quality and fluency
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+ - **Bug fixes**: Report issues or submit fixes for the model implementation
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+ ### Use Cases & Documentation
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+ - **Example applications**: Share how you're using the model for research or projects
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+ - **Domain-specific guides**: Create guides for using the model in specific domains
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+ - **Translation examples**: Share interesting or challenging translation examples
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+
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+ ### Getting Started
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+ 1. Fork the repository
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+ 2. Make your changes
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+ 3. Submit a pull request with clear documentation of your contribution
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+ 4. For data contributions, contact the maintainer directly
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+ All contributors will be acknowledged in the model documentation. Contact [[email protected]](mailto:[email protected]) with any questions or to discuss potential contributions.
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+ ---
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+ *Note: This model is licensed under CC-BY-NC-4.0, so all contributions must be compatible with non-commercial use only.*
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  ## Citation
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  ```bibtex
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  @misc{durdyyev2025turkmenNLLBLoRA,