
# Hungarian Sentence-level Sentiment Analysis Model with XLM-RoBERTa

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: 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:

```
@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}
}

```
{"language": ["hu"], "license": "mit", "tags": ["text-classification"], "metrics": ["accuracy"], "widget": [{"text": "J\u00f3 reggelt! majd k\u00fcld\u00f6m az \u00e9lm\u00e9nyhoz\u00f3kat :)."}]}
transformers pytorch roberta text-classification hu license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #hu #license-mit #autotrain_compatible #endpoints_compatible #region-us 

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: huBERT, HTS2: 85.56, HTS5: 68.99
Model: XLM-RoBERTa, HTS2: 85.56, HTS5: 66.50


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



TAGS
#transformers #pytorch #roberta #text-classification #hu #license-mit #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #roberta #text-classification #hu #license-mit #autotrain_compatible #endpoints_compatible #region-us 
