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--- |
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library_name: transformers |
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language: |
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- ko |
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license: apache-2.0 |
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base_model: monologg/koelectra-base-v3-discriminator |
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tags: |
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- text-classification |
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- koELECTRA |
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- Korean-NLP |
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- topic-classification |
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- news-classification |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: ynat-model |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ynat-model |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4124 |
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- Accuracy: 0.8575 |
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- Precision: 0.8501 |
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- Recall: 0.8709 |
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- F1score: 0.8599 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:-------:| |
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| 0.3949 | 1.0 | 714 | 0.4448 | 0.8479 | 0.8285 | 0.8755 | 0.8496 | |
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| 0.2925 | 2.0 | 1428 | 0.4128 | 0.8520 | 0.8443 | 0.8668 | 0.8536 | |
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| 0.2328 | 3.0 | 2142 | 0.4124 | 0.8575 | 0.8501 | 0.8709 | 0.8599 | |
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### Framework versions |
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- Transformers 4.54.1 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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