| --- |
| license: mit |
| datasets: |
| - anilguven/turkish_news_dataset |
| language: |
| - tr |
| metrics: |
| - accuracy |
| - f1 |
| tags: |
| - electra |
| - news |
| - classification |
| - text |
| --- |
| |
| ### 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/dbmdz/electra-base-turkish-cased-discriminator |
| |
| ### Preprocessing |
| You must apply removing stopwords, stemming, or lemmatization process for Turkish. |
| |
| ### Results |
| - Accuracy: %97.619 |
| - F1-score: %97.617 |
| |
| ### Citation |
| BibTeX: |
| Peer review process |
