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---
language:
- sk
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- sts
license: cc
datasets:
- glue
metrics:
- spearmanr
widget:
- source_sentence: "Izrael uskutočnil letecké údery v blízkosti Damasku."
sentences:
- "Izrael uskutočnil vzdušný útok na Sýriu."
- "Pes leží na gauči a má hlavu na bielom vankúši."
---
# Sentence similarity model based on SlovakBERT
This is a sentence similarity model based on [SlovakBERT](https://huggingface.co/gerulata/slovakbert). The model was fine-tuned using [STSbenchmark](https://ixa2.si.ehu.eus/stswiki/index.php/STSbenchmark) [Cer et al 2017] translated to Slovak using [M2M100](https://huggingface.co/facebook/m2m100_1.2B). The model can be used as an universal sentence encoder for Slovak sentences.
## Results
The model was evaluated in [our paper](https://arxiv.org/abs/2109.15254) [Pikuliak et al 2021, Section 4.3]. It achieves \\(0.791\\) Spearman correlation on STSbenchmark test set.
## Usage
Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
```
pip install -U sentence-transformers
```
Then you can use the model like this:
```python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]
model = SentenceTransformer('kinit/slovakbert-sts-stsb')
embeddings = model.encode(sentences)
print(embeddings)
```
## Cite
```
@inproceedings{pikuliak-etal-2022-slovakbert,
title = "{S}lovak{BERT}: {S}lovak Masked Language Model",
author = "Pikuliak, Mat{\'u}{\v{s}} and
Grivalsk{\'y}, {\v{S}}tefan and
Kon{\^o}pka, Martin and
Bl{\v{s}}t{\'a}k, Miroslav and
Tamajka, Martin and
Bachrat{\'y}, Viktor and
Simko, Marian and
Bal{\'a}{\v{z}}ik, Pavol and
Trnka, Michal and
Uhl{\'a}rik, Filip",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2022",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.findings-emnlp.530",
pages = "7156--7168",
abstract = "We introduce a new Slovak masked language model called \textit{SlovakBERT}. This is to our best knowledge the first paper discussing Slovak transformers-based language models. We evaluate our model on several NLP tasks and achieve state-of-the-art results. This evaluation is likewise the first attempt to establish a benchmark for Slovak language models. We publish the masked language model, as well as the fine-tuned models for part-of-speech tagging, sentiment analysis and semantic textual similarity.",
}
```
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