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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-turkish-cased-finetuned-ner

This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1591
- Precision: 0.9068
- Recall: 0.9245
- F1: 0.9156
- Accuracy: 0.9622

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2222        | 1.0   | 1250 | 0.1655          | 0.8835    | 0.9037 | 0.8935 | 0.9533   |
| 0.1227        | 2.0   | 2500 | 0.1618          | 0.8954    | 0.9199 | 0.9075 | 0.9590   |
| 0.0783        | 3.0   | 3750 | 0.1591          | 0.9068    | 0.9245 | 0.9156 | 0.9622   |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0