Sentiment Analysis model based on SlovakBERT
This is a sentiment analysis classifier based on SlovakBERT. The model can distinguish three level of sentiment:
-1
- Negative sentiment0
- Neutral sentiment1
- Positive setiment
The model was fine-tuned using Slovak part of Multilingual Twitter Sentiment Analysis Dataset [Mozetič et al 2016] containing 50k manually annotated Slovak tweets. As such, it is fine-tuned for tweets and it is not advised to use the model for general-purpose sentiment analysis.
Results
The model was evaluated in our paper [Pikuliak et al 2021, Section 4.4]. It achieves F1-score on the original dataset and F1-score on general reviews dataset.
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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