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--- |
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license: mit |
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tags: |
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- feature-extraction |
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library_name: generic |
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datasets: |
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- ubertext2.0 |
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widget: |
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- text: "доброго вечора ми з україни" |
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--- |
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**skipgram.uk.300.bin** is pre-trained word vectors for the Ukrainian language, trained with fastText on (yet unreleased) UberText2.0 dataset, collected and processed by the [lang-uk](https://lang.org.ua/en/). This model was trained using skipgram in dimension 300, with character n-grams range of 2-5, and 15 negative samples. |
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Our model increases Accuracy by 6.3% compared to the [Facebook Ukrainian word vectors](https://fasttext.cc/docs/en/crawl-vectors.html) on the word analogy task. The dataset for Ukrainian word analogy is available [here](https://github.com/lang-uk/vecs/). |
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Extrinsic evaluations were performed on two sequence labeling tasks: NER and POS tagging. [NER-UK dataset](https://github.com/lang-uk/ner-uk) was released by the [lang-uk](https://lang.org.ua/), and [Ukrainian (UD) corpus](https://github.com/brown-uk/corpus) was developed by a [non-profit organization Institute for Ukrainian](https://mova.institute/). |
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Results: |
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1) spaCy NER F-score: **0.818** |
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2) POS Flair Accuracy: **0.824** |
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3) POS spaCy Accuracy: **0.911** |
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Usage |
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``` |
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import fasttext.util |
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ft = fasttext.load_model('skipgram.uk.300.bin') |
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ft.get_word_vector('привіт') |
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``` |
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### BibTeX entry and citation info |
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```bibtex |
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@inproceedings{romanyshyn-etal-2023-learning, |
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title = "Learning Word Embeddings for {U}krainian: A Comparative Study of Fast{T}ext Hyperparameters", |
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author = "Romanyshyn, Nataliia and |
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Chaplynskyi, Dmytro and |
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Zakharov, Kyrylo", |
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booktitle = "Proceedings of the Second Ukrainian Natural Language Processing Workshop", |
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month = may, |
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year = "2023", |
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address = "Dubrovnik, Croatia", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2023.unlp-1.3", |
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pages = "20--31", |
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} |
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``` |
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Copyright: [Dmytro Chaplynskyi](https://twitter.com/dchaplinsky), [lang-uk](https://lang.org.ua) project, [Nataliia Romanyshyn](https://github.com/romanyshyn-natalia), [Ukrainian Catholic University](https://ucu.edu.ua/en/), 2022 |
