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.

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