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---
library_name: transformers
language:
- ko
license: apache-2.0
base_model: monologg/koelectra-base-v3-discriminator
tags:
- text-classification
- 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: 0.4071
- Accuracy: 0.8612
- Precision: 0.8523
- Recall: 0.8748
- F1: 0.8630
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4097 | 1.0 | 714 | 0.4866 | 0.8362 | 0.8105 | 0.8674 | 0.8335 |
| 0.2884 | 2.0 | 1428 | 0.4015 | 0.8564 | 0.8476 | 0.8744 | 0.8593 |
| 0.2299 | 3.0 | 2142 | 0.4071 | 0.8612 | 0.8523 | 0.8748 | 0.8630 |
### Framework versions
- Transformers 4.54.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2
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