---
base_model: dbmdz/bert-base-turkish-uncased
language:
- tr
library_name: transformers
---
* We use the trt turkish news data which inside news context and categories belongs to one of the news. 

* Using bert base turkish uncased model, aimed to label the categories to the news.

* We have 11 separate categories as below;

  ('bilim_teknoloji',

   'dunya', 'egitim',

  'ekonomi',

  'guncel',

  'gundem',

   'kultur_sanat',

  'saglik',

  'spor',

   'turkiye',

   'yasam')

* We got the validation skor and follow the metric accuracy. The model gave us successfully result. 

### Training results

| Epoch | Train Loss | Validation Loss | accuracy | val_accuracy |
|:-----:|:----------:|:---------------:|:--------:|:------------:|
|   0   | 0.739859   |   0.507217      | 0.766797 |  0.828693    |
|   1   | 0.413323   |   0.474160      | 0.865625 |  0.843466    |