---
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_10_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. -->

# irem_5e-05_4_10_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: 0.8459
- Precision: 0.2556
- Recall: 0.2403
- F1: 0.2477
- Accuracy: 0.8883

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2701        | 1.0   | 672  | 0.1902          | 0.125     | 0.0926 | 0.1064 | 0.9460   |
| 0.2016        | 2.0   | 1344 | 0.1750          | 0.1173    | 0.1759 | 0.1407 | 0.9453   |
| 0.1195        | 3.0   | 2016 | 0.2107          | 0.1880    | 0.2315 | 0.2075 | 0.9476   |
| 0.0776        | 4.0   | 2688 | 0.2238          | 0.1397    | 0.1759 | 0.1557 | 0.9473   |
| 0.0314        | 5.0   | 3360 | 0.2438          | 0.2057    | 0.2685 | 0.2329 | 0.9506   |
| 0.022         | 6.0   | 4032 | 0.3185          | 0.2231    | 0.25   | 0.2358 | 0.9498   |
| 0.0165        | 7.0   | 4704 | 0.3448          | 0.2177    | 0.25   | 0.2328 | 0.9494   |
| 0.0078        | 8.0   | 5376 | 0.3405          | 0.2308    | 0.2778 | 0.2521 | 0.9501   |
| 0.0035        | 9.0   | 6048 | 0.3445          | 0.2121    | 0.2593 | 0.2333 | 0.9484   |
| 0.0035        | 10.0  | 6720 | 0.3680          | 0.2273    | 0.2778 | 0.25   | 0.9489   |


### Framework versions

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