--- library_name: transformers license: apache-2.0 base_model: monologg/koelectra-base-v3-discriminator tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: ynat-model results: [] --- # ynat-model This model is a fine-tuned version of [monologg/koelectra-base-v3-discriminator](https://huggingface.co/monologg/koelectra-base-v3-discriminator) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4651 - Accuracy: 0.8459 - Precision: 0.8354 - Recall: 0.8655 - F1: 0.8492 ## 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-06 - 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 0.7213 | 1.0 | 714 | 0.8798 | 0.7424 | 0.7565 | 0.8240 | 0.7756 | | 0.4888 | 2.0 | 1428 | 0.5669 | 0.8254 | 0.8110 | 0.8604 | 0.8321 | | 0.4147 | 3.0 | 2142 | 0.5082 | 0.8376 | 0.8263 | 0.8659 | 0.8433 | | 0.4093 | 4.0 | 2856 | 0.4712 | 0.8444 | 0.8299 | 0.8656 | 0.8464 | | 0.3667 | 5.0 | 3570 | 0.4651 | 0.8459 | 0.8354 | 0.8655 | 0.8492 | ### Framework versions - Transformers 4.54.1 - Pytorch 2.6.0+cu124 - Datasets 4.0.0 - Tokenizers 0.21.4