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sentiment-hts2-xlm-roberta-hungarian
NYTK/sentiment-hts2-xlm-roberta-hungarian
sentiment-hts2-xlm-roberta-hungarian is a text classification model from NYTK. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
For further models, scripts and details, see our repository or our demo site.
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Aug 22, 2024
- SHA
- a74e7646
Try a prompt
Model card
From the Hugging Face model README
Hungarian Sentence-level Sentiment Analysis Model with XLM-RoBERTa
For further models, scripts and details, see our repository or our demo site.
- Pretrained model used: XLM-RoBERTa base
- Finetuned on Hungarian Twitter Sentiment (HTS) Corpus
- Labels: 0 (negative), 1 (positive)
Limitations
- max_seq_length = 128
Results
| Model | HTS2 | HTS5 |
|---|---|---|
| huBERT | 85.56 | 68.99 |
| XLM-RoBERTa | 85.56 | 66.50 |
Citation
If you use this model, please cite the following paper:
@article {laki-yang-sentiment,
author = {Laki, László János and Yang, Zijian Győző},
title = {Sentiment Analysis with Neural Models for Hungarian},
journal = {Acta Polytechnica Hungarica},
year = {2023},
publisher = {Obuda University},
volume = {20},
number = {5},
doi = {10.12700/APH.20.5.2023.5.8},
pages= {109--128},
url = {https://acta.uni-obuda.hu/Laki_Yang_134.pdf}
}
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Languages
- hu
- Created
- Mar 2, 2022
- Updated
- Aug 22, 2024