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
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.
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:
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.