poltextlab / HunEmBERT8

huggingface.co
Total runs: 33
24-hour runs: 0
7-day runs: 0
30-day runs: 7
Model's Last Updated: August 24 2026
text-classification

Introduction of HunEmBERT8

Model Details of HunEmBERT8

Model description

Cased fine-tuned BERT model for Hungarian, trained on (manuallay anniated) parliamentary pre-agenda speeches scraped from parlament.hu .

Intended uses & limitations

The model can be used as any other (cased) BERT model. It has been tested recognizing emotions at the sentence level in (parliamentary) pre-agenda speeches, where:

  • 'Label_0': Neutral
  • 'Label_1': Fear
  • 'Label_2': Sadness
  • 'Label_3': Anger
  • 'Label_4': Disgust
  • 'Label_5': Success
  • 'Label_6': Joy
  • 'Label_7': Trust
Training

Fine-tuned version of the original huBERT model ( SZTAKI-HLT/hubert-base-cc ), trained on HunEmPoli corpus.

Category Count Ratio Sentiment Count Ratio
Neutral 351 1.85% Neutral 351 1.85%
Fear 162 0.85% Negative 11180 58.84%
Sadness 4258 22.41%
Anger 643 3.38%
Disgust 6117 32.19%
Success 6602 34.74% Positive 7471 39.32%
Joy 441 2.32%
Trust 428 2.25%
Sum 19002
Eval results
Class Precision Recall F-Score
Fear 0.625 0.625 0.625
Sadness 0.8535 0.6291 0.7243
Anger 0.7857 0.3437 0.4782
Disgust 0.7154 0.8790 0.7888
Success 0.8579 0.8683 0.8631
Joy 0.549 0.6363 0.5894
Trust 0.4705 0.5581 0.5106
Macro AVG 0.7134 0.6281 0.6497
Weighted AVG 0.791 0.7791 0.7743
Usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("poltextlab/HunEmBERT8")
model = AutoModelForSequenceClassification.from_pretrained("poltextlab/HunEmBERT8")
BibTeX entry and citation info

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

Bibtex:

@ARTICLE{10149341,
  author={{"U}veges, Istv{\'a}n and Ring, Orsolya},
  journal={IEEE Access}, 
  title={HunEmBERT: a fine-tuned BERT-model for classifying sentiment and emotion in political communication}, 
  year={2023},
  volume={11},
  number={},
  pages={60267-60278},
  doi={10.1109/ACCESS.2023.3285536}
}

Runs of poltextlab HunEmBERT8 on huggingface.co

33
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
7
30-day runs

More Information About HunEmBERT8 huggingface.co Model

More HunEmBERT8 license Visit here:

https://choosealicense.com/licenses/apache-2.0

HunEmBERT8 huggingface.co

HunEmBERT8 huggingface.co is an AI model on huggingface.co that provides HunEmBERT8's model effect (), which can be used instantly with this poltextlab HunEmBERT8 model. huggingface.co supports a free trial of the HunEmBERT8 model, and also provides paid use of the HunEmBERT8. Support call HunEmBERT8 model through api, including Node.js, Python, http.

poltextlab HunEmBERT8 online free

HunEmBERT8 huggingface.co is an online trial and call api platform, which integrates HunEmBERT8's modeling effects, including api services, and provides a free online trial of HunEmBERT8, you can try HunEmBERT8 online for free by clicking the link below.

poltextlab HunEmBERT8 online free url in huggingface.co:

https://huggingface.co/poltextlab/HunEmBERT8

HunEmBERT8 install

HunEmBERT8 is an open source model from GitHub that offers a free installation service, and any user can find HunEmBERT8 on GitHub to install. At the same time, huggingface.co provides the effect of HunEmBERT8 install, users can directly use HunEmBERT8 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

HunEmBERT8 install url in huggingface.co:

https://huggingface.co/poltextlab/HunEmBERT8

Url of HunEmBERT8

Provider of HunEmBERT8 huggingface.co

poltextlab
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Total runs: 33
Run Growth: 6
Growth Rate: 18.18%
Updated:September 05 2026