---
license: mit
base_model: dbmdz/distilbert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: distilbert_turk
  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. -->

# distilbert_turk

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: 0.1927
- F1: 0.8338
- Roc Auc: 0.9092
- Accuracy: 0.8047

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.2899        | 1.0   | 1151  | 0.2053          | 0.6418 | 0.7738  | 0.6719   |
| 0.1846        | 2.0   | 2302  | 0.1777          | 0.7480 | 0.8434  | 0.7461   |
| 0.1432        | 3.0   | 3453  | 0.1633          | 0.7879 | 0.8866  | 0.7656   |
| 0.1241        | 4.0   | 4604  | 0.1508          | 0.8256 | 0.9037  | 0.7891   |
| 0.0961        | 5.0   | 5755  | 0.1621          | 0.8203 | 0.9048  | 0.7969   |
| 0.065         | 6.0   | 6906  | 0.1733          | 0.8108 | 0.9092  | 0.7969   |
| 0.0548        | 7.0   | 8057  | 0.1848          | 0.8238 | 0.8993  | 0.7930   |
| 0.0496        | 8.0   | 9208  | 0.1875          | 0.8130 | 0.9055  | 0.7969   |
| 0.0413        | 9.0   | 10359 | 0.1905          | 0.8359 | 0.9096  | 0.8086   |
| 0.038         | 10.0  | 11510 | 0.1927          | 0.8338 | 0.9092  | 0.8047   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0