Edit model card

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

Preprocessing

You must apply removing stopwords, stemming, or lemmatization process for Turkish.

Results

  • Accuracy: %96.310
  • F1-score: %96.316

Citation

BibTeX: Peer review process

APA: Peer review process

Downloads last month
9
Safetensors
Model size
11.9M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train anilguven/albert_tr_turkish_news

Collection including anilguven/albert_tr_turkish_news