|
--- |
|
license: mit |
|
datasets: |
|
- anilguven/turkish_news_dataset |
|
language: |
|
- tr |
|
metrics: |
|
- accuracy |
|
- f1 |
|
tags: |
|
- news |
|
- classification |
|
- bert |
|
--- |
|
|
|
### 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::** hhttps://huggingface.co/dbmdz/bert-base-turkish-uncased |
|
|
|
### Preprocessing |
|
You must apply removing stopwords, stemming, or lemmatization process for Turkish. |
|
|
|
### Results |
|
- Accuracy: %97.619 |
|
- F1-score: %97.618 |
|
|
|
### Citation |
|
BibTeX: |
|
Peer review process |
