---
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: 5e-05_64_10_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. -->

# 5e-05_64_10_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: 0.5204
- Precision: 0.4302
- Recall: 0.4619
- F1: 0.4455
- Accuracy: 0.8994

## 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: 64
- eval_batch_size: 64
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 62   | 0.4949          | 0.4191    | 0.5473 | 0.4747 | 0.8857   |
| 0.0228        | 2.0   | 124  | 0.4641          | 0.4825    | 0.5206 | 0.5008 | 0.9054   |
| 0.0228        | 3.0   | 186  | 0.5234          | 0.4415    | 0.5328 | 0.4829 | 0.8997   |
| 0.0188        | 4.0   | 248  | 0.5468          | 0.5196    | 0.5006 | 0.5099 | 0.9059   |
| 0.0144        | 5.0   | 310  | 0.5661          | 0.4424    | 0.5339 | 0.4839 | 0.8961   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0