metadata
license: mit
datasets:
- anilguven/turkish_news_dataset
language:
- tr
metrics:
- accuracy
- f1
tags:
- news
- classification
- turkish
- xlm-roberta
Information
This model was developed/finetuned for news classification task for the Turkish Language. This model was finetuned via news dataset. This dataset contains 7 classes: economy, magazine, sport, politics, technology, health, and events.
- LABEL_0: economy
- LABEL_1: magazine
- LABEL_2: health
- LABEL_3: politics
- LABEL_4: sports
- LABEL_5: technology
- LABEL_6: events
Model Sources
- Dataset: https://huggingface.co/datasets/anilguven/turkish_news_dataset
- Paper: peer review (Springer)
- Finetuned from model:: https://huggingface.co/Overfit-GM/xlm-roberta-large-turkish-offensive
Preprocessing
You must apply removing stopwords, stemming, or lemmatization process for Turkish.
Results
- Accuracy: %95.595
- F1-score: %95.586
Citation
BibTeX: Peer review process