---
library_name: transformers
license: mit
base_model: akdeniz27/bert-base-turkish-cased-ner
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-turkish-cased-ner-finetuned-ner
  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-base-turkish-cased-ner-finetuned-ner

This model is a fine-tuned version of [akdeniz27/bert-base-turkish-cased-ner](https://huggingface.co/akdeniz27/bert-base-turkish-cased-ner) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2379
- Precision: 0.9707
- Recall: 0.9708
- F1: 0.9708
- Accuracy: 0.9729

## 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: 1e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1631        | 1.0   | 3334  | 0.1465          | 0.9620    | 0.9627 | 0.9624 | 0.9651   |
| 0.1162        | 2.0   | 6668  | 0.1524          | 0.9659    | 0.9655 | 0.9657 | 0.9683   |
| 0.0938        | 3.0   | 10002 | 0.1452          | 0.9686    | 0.9691 | 0.9688 | 0.9712   |
| 0.048         | 4.0   | 13336 | 0.1734          | 0.9698    | 0.9697 | 0.9698 | 0.9719   |
| 0.0359        | 5.0   | 16670 | 0.1810          | 0.9701    | 0.9703 | 0.9702 | 0.9723   |
| 0.0274        | 6.0   | 20004 | 0.1941          | 0.9713    | 0.9713 | 0.9713 | 0.9734   |
| 0.0187        | 7.0   | 23338 | 0.2185          | 0.9700    | 0.9700 | 0.9700 | 0.9722   |
| 0.0229        | 8.0   | 26672 | 0.2265          | 0.9706    | 0.9707 | 0.9707 | 0.9728   |
| 0.015         | 9.0   | 30006 | 0.2325          | 0.9706    | 0.9705 | 0.9706 | 0.9729   |
| 0.009         | 10.0  | 33340 | 0.2379          | 0.9707    | 0.9708 | 0.9708 | 0.9729   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1