---
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: 0.1216
- Accuracy: 0.9767

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0625        | 0.12  | 200  | 0.3592          | 0.8799   |
| 0.2277        | 0.25  | 400  | 0.1771          | 0.9473   |
| 0.202         | 0.37  | 600  | 0.1594          | 0.9602   |
| 0.1711        | 0.5   | 800  | 0.1588          | 0.9612   |
| 0.1532        | 0.62  | 1000 | 0.1764          | 0.9525   |
| 0.1508        | 0.75  | 1200 | 0.1482          | 0.9627   |
| 0.1441        | 0.87  | 1400 | 0.1102          | 0.9719   |
| 0.1128        | 0.99  | 1600 | 0.1284          | 0.9686   |
| 0.07          | 1.12  | 1800 | 0.1321          | 0.9686   |
| 0.0812        | 1.24  | 2000 | 0.1365          | 0.9706   |
| 0.0858        | 1.37  | 2200 | 0.1046          | 0.9719   |
| 0.0636        | 1.49  | 2400 | 0.1263          | 0.9709   |
| 0.0861        | 1.62  | 2600 | 0.1081          | 0.9742   |
| 0.0623        | 1.74  | 2800 | 0.1148          | 0.9748   |
| 0.082         | 1.86  | 3000 | 0.0877          | 0.9778   |
| 0.0456        | 1.99  | 3200 | 0.1167          | 0.9751   |
| 0.0277        | 2.11  | 3400 | 0.1147          | 0.9759   |
| 0.0205        | 2.24  | 3600 | 0.1247          | 0.9753   |
| 0.0167        | 2.36  | 3800 | 0.1188          | 0.9776   |
| 0.0185        | 2.49  | 4000 | 0.1362          | 0.9762   |
| 0.0156        | 2.61  | 4200 | 0.1254          | 0.9762   |
| 0.0273        | 2.73  | 4400 | 0.1230          | 0.9768   |
| 0.019         | 2.86  | 4600 | 0.1245          | 0.9764   |
| 0.0102        | 2.98  | 4800 | 0.1216          | 0.9767   |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1