Hungarian Sentence-level Sentiment Analysis Model with XLM-RoBERTa

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• Pretrained model used: XLM-RoBERTa base
• Finetuned on Hungarian Twitter Sentiment (HTS) Corpus
• Labels: 0 (very negative), 1 (negative), 2 (neutral), 3 (positive), 4 (very positive)

Limitations

• max_seq_length = 128

Results

Citation

If you use this model, please cite the following paper:

@inproceedings {laki-yang-sentiment,
    title = {Improving Performance of Sentence-level Sentiment Analysis with Data Augmentation Methods},
    booktitle = {Proceedings of 12th IEEE International Conference on Cognitive Infocommunications (CogInfoCom 2021)},
    year = {2021},
    publisher = {IEEE},
    address = {Online},
    author = {Laki, László and Yang, Zijian Győző}
    pages = {417--422}
}