基于SlovakBERT的情感分析模型

这是一个基于SlovakBERT的情感分析分类器。该模型可以区分三个级别的情感：

• -1 - 负面情感
• 0 - 中性情感
• 1 - 正面情感

该模型是使用SlovakBERT的 SlovakBERT 部分进行微调的[Mozetič et al 2016]，包含50,000个手动标注的斯洛伐克语推文。因此，该模型是针对推文进行微调的，不建议将该模型用于通用情感分析。

结果

该模型在 our paper 的评估中获得以下结果[Pikuliak et al 2021，第4.4节]：在原始数据集上的F1得分为0.67，普通评论数据集上的F1得分为0.58。

引用

@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.",
}