|
|
--- |
|
|
library_name: transformers |
|
|
language: |
|
|
- ko |
|
|
license: apache-2.0 |
|
|
base_model: monologg/koelectra-base-v3-discriminator |
|
|
tags: |
|
|
- text-classification |
|
|
- KoELECTRA |
|
|
- Korean-NLP |
|
|
- topic-classification |
|
|
- news-classification |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
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 [monologg/koelectra-base-v3-discriminator](https://huggingface.co/monologg/koelectra-base-v3-discriminator) on the klue-ynat dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.4885 |
|
|
- Accuracy: 0.8551 |
|
|
- Precision: 0.8449 |
|
|
- Recall: 0.8685 |
|
|
- F1: 0.8560 |
|
|
|
|
|
## 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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 3 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
|
| 0.2251 | 1.0 | 714 | 0.4871 | 0.8523 | 0.8517 | 0.8586 | 0.8534 | |
|
|
| 0.2431 | 2.0 | 1428 | 0.4452 | 0.8531 | 0.8467 | 0.8675 | 0.8556 | |
|
|
| 0.1716 | 3.0 | 2142 | 0.4885 | 0.8551 | 0.8449 | 0.8685 | 0.8560 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.51.3 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.6.0 |
|
|
- Tokenizers 0.21.1 |
|
|
|
