metadata
language:
- ckb
tags:
- kurdish
- sentiment-analysis
- offensive-language-detection
- multi-task-learning
- kubert
KurdSense — Multi-Task Kurdish Sentiment & Offensive Language Detector
KurdSense is the first multi-task NLP model for Kurdish Sorani, simultaneously predicting sentiment (Negative/Neutral/Positive) and offensiveness (Safe/Offensive) from a single Kurdish tweet.
Model Details
- Base model: KuBERT (asosoft/KuBERT-Central-Kurdish-BERT-Model)
- Architecture: Shared KuBERT encoder + two classification heads
- Language: Kurdish Sorani (ckb)
- Dataset: STSD — 24,668 annotated Kurdish tweets (Wady, Badawi & Kurt, 2024)
Results
| Task | Macro F1 | Accuracy |
|---|---|---|
| Sentiment (3-class) | 0.5100 | 55.9% |
| Offensiveness (binary) | 0.6326 | 87.1% |
How to Use
Load the model weights using the custom KurdSenseMultiTask architecture and BertTokenizer with unk_token="[UNK]".
Citation
Wady, S. H., Badawi, S., & Kurt, F. (2024). A Kurdish Sorani Twitter dataset for language modelling. Data in Brief, 57, 110967.