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

# didem_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: 0.6822
- Precision: 0.2508
- Recall: 0.2827
- F1: 0.2658
- Accuracy: 0.8869

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2745        | 1.0   | 669  | 0.2574          | 0.1028    | 0.0769 | 0.088  | 0.9295   |
| 0.2494        | 2.0   | 1338 | 0.2560          | 0.0814    | 0.0979 | 0.0889 | 0.9241   |
| 0.1455        | 3.0   | 2007 | 0.2870          | 0.1070    | 0.1608 | 0.1285 | 0.9271   |
| 0.0938        | 4.0   | 2676 | 0.2964          | 0.1040    | 0.1469 | 0.1217 | 0.9214   |
| 0.0677        | 5.0   | 3345 | 0.3666          | 0.1152    | 0.1329 | 0.1234 | 0.9314   |
| 0.0258        | 6.0   | 4014 | 0.3647          | 0.1222    | 0.1538 | 0.1362 | 0.9276   |
| 0.0273        | 7.0   | 4683 | 0.4239          | 0.1727    | 0.1678 | 0.1702 | 0.9315   |
| 0.0176        | 8.0   | 5352 | 0.4458          | 0.1321    | 0.1469 | 0.1391 | 0.9300   |
| 0.0051        | 9.0   | 6021 | 0.4836          | 0.1622    | 0.1678 | 0.1649 | 0.9292   |
| 0.0032        | 10.0  | 6690 | 0.4995          | 0.1529    | 0.1678 | 0.16   | 0.9295   |


### Framework versions

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