---
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
datasets:
- turkish_ner
metrics:
- f1
- precision
- recall
- accuracy
model-index:
- name: turkish-ner-mBERT-03
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: turkish_ner
      type: turkish_ner
      config: default
      split: train
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.9498768124722323
    - name: Precision
      type: precision
      value: 0.9514138921477406
    - name: Recall
      type: recall
      value: 0.9483446913181983
    - name: Accuracy
      type: accuracy
      value: 0.9899531423087632
---

<!-- 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. -->

# turkish-ner-mBERT-03

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the turkish_ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0340
- F1: 0.9499
- Precision: 0.9514
- Recall: 0.9483
- Accuracy: 0.9900

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
| 0.3699        | 1.0   | 625  | 0.2191          | 0.6830 | 0.6971    | 0.6693 | 0.9216   |
| 0.2451        | 2.0   | 1250 | 0.1407          | 0.8042 | 0.8068    | 0.8017 | 0.9527   |
| 0.1818        | 3.0   | 1875 | 0.0799          | 0.8785 | 0.8828    | 0.8742 | 0.9733   |
| 0.0964        | 4.0   | 2500 | 0.0489          | 0.9295 | 0.9252    | 0.9339 | 0.9852   |
| 0.0635        | 5.0   | 3125 | 0.0340          | 0.9499 | 0.9514    | 0.9483 | 0.9900   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0