---
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: irem_5e-05_4_5_detect
  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. -->

# irem_5e-05_4_5_detect

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: 0.5701
- Precision: 0.6177
- Recall: 0.4781
- F1: 0.5390
- Accuracy: 0.9124

## 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: 4
- eval_batch_size: 4
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.173         | 1.0   | 669  | 0.1389          | 0.2328    | 0.2278 | 0.2303 | 0.9490   |
| 0.0999        | 2.0   | 1338 | 0.1502          | 0.3805    | 0.3629 | 0.3715 | 0.9529   |
| 0.0629        | 3.0   | 2007 | 0.1825          | 0.3611    | 0.3291 | 0.3444 | 0.9508   |
| 0.035         | 4.0   | 2676 | 0.2136          | 0.3857    | 0.3629 | 0.3739 | 0.9526   |
| 0.0117        | 5.0   | 3345 | 0.2472          | 0.3816    | 0.3671 | 0.3742 | 0.9523   |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0