readme: ---
  language:
  - hu
  tags:
  - text-classification
  license: apache-2.0
  metrics:
  - accuracy
  widget:
  - text: Jó reggelt! majd küldöm az élményhozókat :).
  ---
  
  # Hungarian Sentence-level Sentiment Analysis with Finetuned huBERT Model
  
  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).
  
    - Pretrained model used: huBERT
    - 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:
  
  ```
  @inproceedings {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}
  }
  
  ```