---
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-ner-turkish-cased
  results: []
---

<!-- 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. -->

# bert-ner-turkish-cased

This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0987
- Precision: 0.9112
- Recall: 0.9364
- F1: 0.9236
- Accuracy: 0.9600

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- 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: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1351        | 1.0   | 1527  | 0.1158          | 0.8592    | 0.9070 | 0.8825 | 0.9517   |
| 0.1088        | 2.0   | 3054  | 0.1045          | 0.8787    | 0.9336 | 0.9053 | 0.9574   |
| 0.1016        | 3.0   | 4581  | 0.0993          | 0.8901    | 0.9280 | 0.9086 | 0.9576   |
| 0.1102        | 4.0   | 6108  | 0.0963          | 0.8991    | 0.9277 | 0.9132 | 0.9587   |
| 0.0877        | 5.0   | 7635  | 0.0953          | 0.9046    | 0.9292 | 0.9167 | 0.9584   |
| 0.0933        | 6.0   | 9162  | 0.0939          | 0.9036    | 0.9321 | 0.9176 | 0.9593   |
| 0.0827        | 7.0   | 10689 | 0.0967          | 0.8986    | 0.9398 | 0.9188 | 0.9605   |
| 0.0933        | 8.0   | 12216 | 0.0949          | 0.9122    | 0.9292 | 0.9206 | 0.9593   |
| 0.084         | 9.0   | 13743 | 0.0987          | 0.9112    | 0.9364 | 0.9236 | 0.9600   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0