---
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
model-index:
- name: results
  results: []
datasets:
- turkish-nlp-suite/turkish-wikiNER
language:
- tr
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# berturk-ner

This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on 
[turkish-nlp-suite/turkish-wikiNER](https://huggingface.co/datasets/turkish-nlp-suite/turkish-wikiNER) dataset.
It achieves the following results:

Validation Set
- Loss: 0.3693
- Accuracy: 0.9149
- F1: 0.9146
- Precision: 0.9167
- Recall: 0.9149

Test Set
- Accuracy: 0.9241
- F1: 0.8316
- Precision: 0.8341
- Recall: 0.8291

## 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: 0.0002
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Preicision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:----------:|:------:|
| 0.5606        | 1.0   | 141  | 0.3018          | 0.9109   | 0.9107 | 0.9127     | 0.9109 |
| 0.2489        | 2.0   | 282  | 0.3185          | 0.9108   | 0.9089 | 0.9107     | 0.9108 |
| 0.1558        | 3.0   | 423  | 0.3378          | 0.9051   | 0.9028 | 0.9056     | 0.9051 |
| 0.0966        | 4.0   | 564  | 0.3472          | 0.9151   | 0.9149 | 0.9170     | 0.9151 |
| 0.0678        | 5.0   | 705  | 0.3693          | 0.9149   | 0.9146 | 0.9167     | 0.9149 |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1