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---
license: unknown
datasets:
- anilguven/turkish_spam_email
language:
- tr
metrics:
- accuracy
- f1
- recall
- precision
tags:
- turkish
- spam
- ham
- email
- albert
- 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/loodos/albert-base-turkish-uncased
#### 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: %93.55
- Accuracy: %93.10
## 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.* |