README.md

---
license: unknown
datasets:
- anilguven/turkish_spam_email
language:
- tr
metrics:
- accuracy
- f1
- recall
- precision
tags:
- turkish
- spam
- email
- ham
- bert
---
### Model Info

This model was developed/finetuned for spam detection task for Turkish Language. This model was finetuned via spam/ham email dataset. 
- LABEL_0: ham/normal mail
- LABEL_1: spam mail

### Model Sources

<!-- Provide the basic links for the model. -->

- **Dataset:** https://huggingface.co/datasets/anilguven/turkish_spam_email
- **Paper:** https://dergipark.org.tr/tr/pub/ejosat/issue/75736/1234079
- **Demo-Coding [optional]:** https://github.com/anil1055/Turkish_spam_email_detection_with_language_models
- **Finetuned from model [optional]:** https://huggingface.co/dbmdz/electra-base-turkish-caseddiscriminator

#### Preprocessing 

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

# Model Load safetensors

<!-- Provide a quick summary of what the model is/does. -->

Detailed https://huggingface.co/docs/diffusers/using-diffusers/using_safetensors

### Results

- F1-score: %94.00
- Accuracy: %94.08

## Citation

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

*@article{article_1234079, title={Türkçe E-postalarda Spam Tespiti için Makine Öğrenme Yöntemlerinin ve Dil Modellerinin Analizi}, journal={Avrupa Bilim ve Teknoloji Dergisi}, pages={1–6}, year={2023}, DOI={10.31590/ejosat.1234079}, author={GÜVEN, Zekeriya Anıl}, keywords={Siber Güvenlik, Spam Tespiti, Dil Modeli, Makine Öğrenmesi, Doğal Dil İşleme, Metin Sınıflandırma, Cyber Security, Spam Detection, Language Model, Machine Learning, Natural Language Processing, Text Classification}, number={47}, publisher={Osman SAĞDIÇ} }*


**APA:**

*GÜVEN, Z. A. (2023). Türkçe E-postalarda Spam Tespiti için Makine Öğrenme Yöntemlerinin ve Dil Modellerinin Analizi. Avrupa Bilim ve Teknoloji Dergisi, (47), 1-6.*