---
library_name: transformers
license: apache-2.0
base_model: beomi/kcbert-base
tags:
- reptile
- korean
- text-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: reptile-classifier-ko
  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. -->

# reptile-classifier-ko

This model is a fine-tuned version of [beomi/kcbert-base](https://huggingface.co/beomi/kcbert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8473
- Accuracy: 0.8571

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 4    | 1.4946          | 0.4286   |
| No log        | 2.0   | 8    | 1.3567          | 0.4286   |
| 1.5809        | 3.0   | 12   | 1.2038          | 0.5714   |
| 1.5809        | 4.0   | 16   | 1.0654          | 0.7143   |
| 1.0943        | 5.0   | 20   | 0.9427          | 0.7143   |
| 1.0943        | 6.0   | 24   | 0.8473          | 0.8571   |
| 1.0943        | 7.0   | 28   | 0.7914          | 0.8571   |
| 0.6992        | 8.0   | 32   | 0.7475          | 0.8571   |
| 0.6992        | 9.0   | 36   | 0.7274          | 0.8571   |
| 0.5718        | 10.0  | 40   | 0.7207          | 0.8571   |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.8.0
- Datasets 4.0.0
- Tokenizers 0.21.4