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library_name: transformers
language:
- ko
base_model: lang-brain-test
tags:
- text-classification
- korean_NLP
- KoELECTRA
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ynal_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. -->
# ynal_model
This model is a fine-tuned version of [lang-brain-test](https://huggingface.co/lang-brain-test) on the klue-ynat dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4987
- Accuracy: 0.8634
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4044 | 1.0 | 714 | 0.4436 | 0.8477 |
| 0.309 | 2.0 | 1428 | 0.3955 | 0.8568 |
| 0.2365 | 3.0 | 2142 | 0.4349 | 0.8543 |
| 0.1822 | 4.0 | 2856 | 0.4599 | 0.8610 |
| 0.1181 | 5.0 | 3570 | 0.4987 | 0.8634 |
### Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
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