Edit model card
  • 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
Downloads last month
8
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for RvKy/bert_FineTuned_MultiClass_news

Finetuned
(10)
this model