---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: umit_42000news
  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. -->

# umit_42000news
Dataset:

https://www.kaggle.com/datasets/furkanozbay/turkish-news-dataset

https://www.kaggle.com/datasets/oktayozturk010/42000-news-text-in-13-classes

This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on provided dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9423
- Accuracy: 0.6937

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8754        | 1.0   | 1584 | 0.9817          | 0.6752   |
| 0.7769        | 2.0   | 3168 | 0.9106          | 0.6903   |
| 0.527         | 3.0   | 4752 | 0.9423          | 0.6937   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2