---
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
  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. -->

# results

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: 0.3687
- Accuracy: 0.9130

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8572        | 0.14  | 200  | 1.4831          | 0.4714   |
| 1.2551        | 0.27  | 400  | 0.9639          | 0.6684   |
| 0.886         | 0.41  | 600  | 0.7681          | 0.7507   |
| 0.7313        | 0.55  | 800  | 0.5526          | 0.8317   |
| 0.5804        | 0.69  | 1000 | 0.5308          | 0.8312   |
| 0.5407        | 0.82  | 1200 | 0.4486          | 0.8595   |
| 0.502         | 0.96  | 1400 | 0.5216          | 0.8516   |
| 0.3737        | 1.1   | 1600 | 0.4527          | 0.8763   |
| 0.3367        | 1.23  | 1800 | 0.4716          | 0.8544   |
| 0.3272        | 1.37  | 2000 | 0.3905          | 0.8862   |
| 0.2988        | 1.51  | 2200 | 0.3661          | 0.8926   |
| 0.298         | 1.64  | 2400 | 0.4301          | 0.8898   |
| 0.2856        | 1.78  | 2600 | 0.3944          | 0.8943   |
| 0.2832        | 1.92  | 2800 | 0.3608          | 0.8979   |
| 0.2483        | 2.06  | 3000 | 0.3757          | 0.8987   |
| 0.1699        | 2.19  | 3200 | 0.3802          | 0.9100   |
| 0.1433        | 2.33  | 3400 | 0.4144          | 0.9114   |
| 0.1826        | 2.47  | 3600 | 0.3533          | 0.9124   |
| 0.159         | 2.6   | 3800 | 0.3708          | 0.9107   |
| 0.1601        | 2.74  | 4000 | 0.3775          | 0.9118   |
| 0.1442        | 2.88  | 4200 | 0.3687          | 0.9130   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1