---
license: mit
base_model: dbmdz/distilbert-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/distilbert-base-turkish-cased](https://huggingface.co/dbmdz/distilbert-base-turkish-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1938
- Accuracy: 0.9592

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9211        | 0.07  | 100  | 1.8456          | 0.3225   |
| 1.6177        | 0.14  | 200  | 1.2261          | 0.5982   |
| 0.8794        | 0.21  | 300  | 0.4865          | 0.8638   |
| 0.428         | 0.27  | 400  | 0.3350          | 0.8991   |
| 0.3189        | 0.34  | 500  | 0.2934          | 0.9128   |
| 0.2869        | 0.41  | 600  | 0.2728          | 0.9219   |
| 0.2776        | 0.48  | 700  | 0.2529          | 0.9267   |
| 0.2334        | 0.55  | 800  | 0.2609          | 0.9303   |
| 0.2314        | 0.62  | 900  | 0.2157          | 0.9369   |
| 0.2381        | 0.69  | 1000 | 0.1924          | 0.9431   |
| 0.2574        | 0.75  | 1100 | 0.2476          | 0.9260   |
| 0.2068        | 0.82  | 1200 | 0.1919          | 0.9429   |
| 0.241         | 0.89  | 1300 | 0.1865          | 0.9417   |
| 0.1894        | 0.96  | 1400 | 0.2022          | 0.9453   |
| 0.1791        | 1.03  | 1500 | 0.2078          | 0.9448   |
| 0.1131        | 1.1   | 1600 | 0.1995          | 0.9493   |
| 0.1082        | 1.17  | 1700 | 0.2074          | 0.9498   |
| 0.1088        | 1.23  | 1800 | 0.2139          | 0.9467   |
| 0.1123        | 1.3   | 1900 | 0.2086          | 0.9481   |
| 0.1083        | 1.37  | 2000 | 0.1964          | 0.9498   |
| 0.1318        | 1.44  | 2100 | 0.1872          | 0.9503   |
| 0.1016        | 1.51  | 2200 | 0.2005          | 0.9486   |
| 0.1415        | 1.58  | 2300 | 0.1918          | 0.9507   |
| 0.1292        | 1.64  | 2400 | 0.1848          | 0.9520   |
| 0.0939        | 1.71  | 2500 | 0.1870          | 0.9539   |
| 0.1301        | 1.78  | 2600 | 0.1950          | 0.9525   |
| 0.1415        | 1.85  | 2700 | 0.1955          | 0.9501   |
| 0.1474        | 1.92  | 2800 | 0.1797          | 0.9556   |
| 0.1169        | 1.99  | 2900 | 0.1767          | 0.9577   |
| 0.0562        | 2.06  | 3000 | 0.1847          | 0.9563   |
| 0.0653        | 2.12  | 3100 | 0.1839          | 0.9584   |
| 0.0431        | 2.19  | 3200 | 0.1853          | 0.9565   |
| 0.0289        | 2.26  | 3300 | 0.1922          | 0.9572   |
| 0.0507        | 2.33  | 3400 | 0.1989          | 0.9582   |
| 0.0475        | 2.4   | 3500 | 0.2009          | 0.9573   |
| 0.0434        | 2.47  | 3600 | 0.1959          | 0.9580   |
| 0.0479        | 2.54  | 3700 | 0.1942          | 0.9585   |
| 0.0421        | 2.6   | 3800 | 0.1986          | 0.9578   |
| 0.0496        | 2.67  | 3900 | 0.1947          | 0.9577   |
| 0.0452        | 2.74  | 4000 | 0.1938          | 0.9594   |
| 0.0329        | 2.81  | 4100 | 0.1936          | 0.9594   |
| 0.0568        | 2.88  | 4200 | 0.1934          | 0.9584   |
| 0.0441        | 2.95  | 4300 | 0.1938          | 0.9592   |


### Framework versions

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