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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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- f1 |
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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: 0.4149 |
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- Accuracy: 0.8581 |
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- Precision: 0.8490 |
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- Recall: 0.8719 |
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- F1: 0.8598 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.404 | 1.0 | 714 | 0.4718 | 0.8402 | 0.8232 | 0.8672 | 0.8411 | |
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| 0.2999 | 2.0 | 1428 | 0.4038 | 0.8553 | 0.8474 | 0.8713 | 0.8576 | |
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| 0.2288 | 3.0 | 2142 | 0.4149 | 0.8581 | 0.8490 | 0.8719 | 0.8598 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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