---
license: unknown
datasets:
- anilguven/turkish_product_reviews_sentiment
language:
- tr
metrics:
- accuracy
- f1
- precision
- recall
tags:
- turkish
- product
- review
- distilbert
- bert
---
### Model Info

This model was developed/finetuned for product review task for Turkish Language. Model was finetuned via hepsiburada.com product review dataset. 
- LABEL_0: negative review
- LABEL_1: positive review

### Model Sources

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

- **Dataset:** https://huggingface.co/datasets/anilguven/turkish_product_reviews_sentiment
- **Demo-Coding [optional]:** https://github.com/anil1055/Turkish_Product_Review_Analysis_with_Language_Models
- **Finetuned from model [optional]:** https://huggingface.co/dbmdz/distilbert-base-turkish-cased
- 

#### Preprocessing 

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

### Results

- auprc = 0.9720155023202002
- auroc = 0.9743030995629336
- eval_loss = 0.3418520176025824
- fn = 206
- fp = 226
- mcc = 0.8420573290530216
- tn = 2474
- tp = 2565
- Accuracy: %92.10