metadata
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: []
ynat_model
This model is a fine-tuned version of 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