| library_name: transformers | |
| language: | |
| - ko | |
| license: apache-2.0 | |
| base_model: monologg/koelectra-base-v3-discriminator | |
| tags: | |
| - text-classification | |
| - KoELECTRA | |
| - 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: 0.4069 | |
| - Accuracy: 0.8629 | |
| - Precision: 0.8508 | |
| - Recall: 0.8771 | |
| - F1: 0.8632 | |
| ## 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: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | |
| | 0.4032 | 1.0 | 714 | 0.4710 | 0.8320 | 0.8100 | 0.8718 | 0.8367 | | |
| | 0.2901 | 2.0 | 1428 | 0.3964 | 0.8584 | 0.8525 | 0.8683 | 0.8589 | | |
| | 0.2206 | 3.0 | 2142 | 0.4069 | 0.8629 | 0.8508 | 0.8771 | 0.8632 | | |
| ### Framework versions | |
| - Transformers 5.0.0 | |
| - Pytorch 2.10.0+cu128 | |
| - Datasets 4.0.0 | |
| - Tokenizers 0.22.2 | |