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

# best_model_categorize

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: 0.0431
- Precision: 0.6642
- Recall: 0.7093
- F1: 0.6860
- Accuracy: 0.9857

## 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: 8
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 309  | 0.2587          | 0.1656    | 0.2316 | 0.1931 | 0.9131   |
| 0.3346        | 2.0   | 618  | 0.1543          | 0.3189    | 0.4404 | 0.3700 | 0.9524   |
| 0.3346        | 3.0   | 927  | 0.0821          | 0.4876    | 0.5654 | 0.5236 | 0.9732   |
| 0.1746        | 4.0   | 1236 | 0.0551          | 0.6009    | 0.6621 | 0.6300 | 0.9816   |
| 0.083         | 5.0   | 1545 | 0.0431          | 0.6642    | 0.7093 | 0.6860 | 0.9857   |


### Framework versions

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