File size: 1,283 Bytes
4f86dc1 d7586e1 4f86dc1 e240cd8 db6d653 e20bf51 4f86dc1 7261a4a 910059d 7261a4a 73bb982 7261a4a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 |
---
pipeline_tag: text-classification
inference: true
widget:
- text: "Sem Mark in živim v Ljubljani. Sem doktorski študent na Mednarodni podiplomski šoli Jožefa Stefana."
language:
- sl
license: mit
---
# Hate Speech Classifier for Social Media Content in Slovenian Language
A monolingual model for hate speech classification of social media content in Slovenian language. The model was trained on 50,000 Twitter comments and tested on an independent test set of 10,000 Twitter comments. It is based on multilingual CroSloEngual BERT pre-trained language model.
## Please cite:
Kralj Novak, P., Scantamburlo, T., Pelicon, A., Cinelli, M., Mozetič, I., & Zollo, F. (2022, July). __Handling disagreement in hate speech modelling__. In International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (pp. 681-695). Cham: Springer International Publishing.
https://link.springer.com/chapter/10.1007/978-3-031-08974-9_54
## Tokenizer
During training the text was preprocessed using the original CroSloEngual BERT tokenizer. We suggest the same tokenizer is used for inference.
## Model output
The model classifies each input into one of four distinct classes:
* 0 - acceptable
* 1 - inappropriate
* 2 - offensive
* 3 - violent |