---
library_name: transformers
language:
- ko
base_model: brina-4
tags:
- text-classification
- korean_NLP
- KoELECTRA
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ynat_model
  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. -->

# ynat_model

This model is a fine-tuned version of [brina-4](https://huggingface.co/brina-4) on the klue-ynat dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5193
- Accuracy: 0.8567

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4049        | 1.0   | 714  | 0.4515          | 0.8425   |
| 0.3132        | 2.0   | 1428 | 0.4136          | 0.8497   |
| 0.2289        | 3.0   | 2142 | 0.4638          | 0.8452   |
| 0.1833        | 4.0   | 2856 | 0.4686          | 0.8598   |
| 0.1155        | 5.0   | 3570 | 0.5193          | 0.8567   |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0