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---
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 |
|