---
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: 0.1455
- Accuracy: 0.9716

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6937        | 0.14  | 200  | 0.5659          | 0.8653   |
| 0.3263        | 0.27  | 400  | 0.2603          | 0.9248   |
| 0.2423        | 0.41  | 600  | 0.2538          | 0.9323   |
| 0.2036        | 0.55  | 800  | 0.2016          | 0.9495   |
| 0.1961        | 0.69  | 1000 | 0.1868          | 0.9519   |
| 0.1837        | 0.82  | 1200 | 0.1819          | 0.9537   |
| 0.2017        | 0.96  | 1400 | 0.1481          | 0.9626   |
| 0.1337        | 1.1   | 1600 | 0.1735          | 0.9597   |
| 0.097         | 1.23  | 1800 | 0.1684          | 0.9616   |
| 0.1059        | 1.37  | 2000 | 0.1545          | 0.9614   |
| 0.0968        | 1.51  | 2200 | 0.1436          | 0.9657   |
| 0.1147        | 1.64  | 2400 | 0.1401          | 0.9638   |
| 0.082         | 1.78  | 2600 | 0.1389          | 0.9673   |
| 0.078         | 1.92  | 2800 | 0.1233          | 0.9719   |
| 0.0668        | 2.06  | 3000 | 0.1373          | 0.9690   |
| 0.0279        | 2.19  | 3200 | 0.1512          | 0.9702   |
| 0.0331        | 2.33  | 3400 | 0.1353          | 0.9738   |
| 0.0276        | 2.47  | 3600 | 0.1404          | 0.9733   |
| 0.0339        | 2.6   | 3800 | 0.1527          | 0.9719   |
| 0.031         | 2.74  | 4000 | 0.1483          | 0.9710   |
| 0.0224        | 2.88  | 4200 | 0.1455          | 0.9716   |


### Framework versions

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