kvkk-ner-bert-turkish
This model is a fine-tuned version of dbmdz/bert-base-turkish-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0802
- Precision: 0.9152
- Recall: 0.9203
- F1: 0.9177
- Accuracy: 0.9759
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1429 | 1.0 | 3246 | 0.0861 | 0.8965 | 0.9167 | 0.9065 | 0.9732 |
| 0.0970 | 2.0 | 6492 | 0.0958 | 0.9100 | 0.9095 | 0.9097 | 0.9730 |
| 0.0716 | 3.0 | 9738 | 0.1025 | 0.9059 | 0.9100 | 0.9079 | 0.9724 |
Framework versions
- Transformers 5.5.4
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2