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--- |
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language: |
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- hu |
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tags: |
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- text-classification |
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license: apache-2.0 |
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metrics: |
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- accuracy |
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widget: |
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- text: Jó reggelt! majd küldöm az élményhozókat :). |
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--- |
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# Hungarian Sentence-level Sentiment Analysis with Finetuned huBERT Model |
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For further models, scripts and details, see [our repository](https://github.com/nytud/sentiment-analysis) or [our demo site](https://juniper.nytud.hu/demo/nlp). |
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- Pretrained model used: huBERT |
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- Finetuned on Hungarian Twitter Sentiment (HTS) Corpus |
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- Labels: 0 (negative), 1 (positive) |
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## Limitations |
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- max_seq_length = 128 |
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## Results |
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| Model | HTS2 | HTS5 | |
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| ------------- | ------------- | ------------- | |
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| huBERT | **85.56** | 68.99 | |
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| XLM-RoBERTa| 85.56 | 66.50 | |
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## Citation |
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If you use this model, please cite the following paper: |
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``` |
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@inproceedings {yang-sentiment, |
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title = {Improving Performance of Sentence-level Sentiment Analysis with Data Augmentation Methods}, |
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booktitle = {Proceedings of 12th IEEE International Conference on Cognitive Infocommunications (CogInfoCom 2021)}, |
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year = {2021}, |
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publisher = {IEEE}, |
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address = {Online}, |
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author = {Laki, László and Yang, Zijian Győző} |
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pages = {417--422} |
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} |
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``` |
