| --- |
| base_model: |
| - sentence-transformers/paraphrase-multilingual-mpnet-base-v2 |
| language: |
| - multilingual |
| - ar |
| - bg |
| - ca |
| - cs |
| - da |
| - de |
| - el |
| - en |
| - es |
| - et |
| - fa |
| - fi |
| - fr |
| - gl |
| - gu |
| - he |
| - hi |
| - hr |
| - hu |
| - hy |
| - id |
| - it |
| - ja |
| - ka |
| - ko |
| - ku |
| - lt |
| - lv |
| - mk |
| - mn |
| - mr |
| - ms |
| - my |
| - nb |
| - nl |
| - pl |
| - pt |
| - ro |
| - sk |
| - sl |
| - sq |
| - sr |
| - sv |
| - th |
| - tr |
| - uk |
| - ur |
| - vi |
| license: apache-2.0 |
| library_name: sentence-transformers |
| tags: |
| - sentence-transformers |
| - feature-extraction |
| - sentence-similarity |
| - transformers |
| language_bcp47: |
| - fr-ca |
| - pt-br |
| - zh-cn |
| - zh-tw |
| pipeline_tag: sentence-similarity |
| datasets: |
| - victormuryn/wsd-training-dataset |
| --- |
| # use-natural-pt |
| This model is a fine-tuned version of [paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2), trained on the Ukrainian text corpus [UberText 2.0](https://lang.org.ua/en/ubertext/) on the raw corpus with pool targets, with no data augmentation applied. It is part of the [Ukrainian Sentence Embeddings](https://huggingface.co/collections/victormuryn/ukrainian-sentence-embeddings-use) collection, which explores the effect of different training strategies on sentence embedding quality for Ukrainian. |
|
|
| ## Model Description |
| The model was fine-tuned using a contrastive objective on UberText 2.0. |
|
|
| ## Collection Overview |
| | Model | Description | |
| | ----------------------- | ----------------------------------------------------- | |
| | use-natural-no-pt | Raw UberText 2.0, no augmentation, no pool targets | |
| | **use-natural-pt** | Raw UberText 2.0, no augmentation, pool targets | |
| | use-generated-no-pt | Generated augmentation, no pool targets | |
| | use-generated-pt | Generated augmentation, pool targets | |
| | use-translation-no-pt | Back-translation augmentation, no pool targets | |
| | use-translation-pt | Back-translation augmentation, pool targets | |
| | use-mask-no-pt | Masking augmentation, no pool targets | |
| | use-mask-pt | Masking augmentation, pool targets | |
| | use-dropout-no-pt | Dropout augmentation, no pool targets | |
| | use-dropout-pt | Dropout augmentation, pool targets | |
| | use-token-shuffle-no-pt | Token-shuffling augmentation, no pool targets | |
| | use-token-shuffle-pt | Token-shuffling augmentation, pool targets | |
| | use-combined-no-pt | Combined augmentation strategies, no pool targets | |
| | use-combined-pt | Combined augmentation strategies, pool targets | |
| | use-stochastic-no-pt | Markov-based stochastic augmentation, no pool targets | |
| | use-stochastic-pt | Markov-based stochastic augmentation, pool targets | |
|
|
| ## Usage |
| ```python |
| from sentence_transformers import SentenceTransformer |
| model = SentenceTransformer("victormuryn/use-natural-pt") |
| sentences = [ |
| "Проводжає сина мати захищати рідний край", |
| "Хоч би малесеньку хатину він мріяв мати над Дніпром", |
| ] |
| embeddings = model.encode(sentences) |
| print(embeddings.shape) |
| ``` |
|
|
| ## Training Details |
| - **Base model:** paraphrase-multilingual-mpnet-base-v2 |
| - **Training corpus:** UberText 2.0 |
| - **Augmentation:** None |
| - **Pool targets:** Yes |
|
|
| ## Citation |
| To be added |
|
|
| ## License |
| Apache 2.0 |
|
|
