--- library_name: transformers license: apache-2.0 base_model: beomi/kcbert-base tags: - HHD - 10_class - multi_labels - generated_from_trainer model-index: - name: bert_model_out results: [] --- # bert_model_out This model is a fine-tuned version of [beomi/kcbert-base](https://huggingface.co/beomi/kcbert-base) on the unsmile_data dataset. It achieves the following results on the evaluation set: - Loss: 0.1559 - Irap: 0.8744 ## 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: 2e-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: 7 ### Training results | Training Loss | Epoch | Step | Validation Loss | Irap | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 1.0 | 235 | 0.1296 | 0.8701 | | No log | 2.0 | 470 | 0.1274 | 0.8754 | | 0.0982 | 3.0 | 705 | 0.1324 | 0.8759 | | 0.0982 | 4.0 | 940 | 0.1410 | 0.8762 | | 0.0497 | 5.0 | 1175 | 0.1475 | 0.8770 | | 0.0497 | 6.0 | 1410 | 0.1530 | 0.8731 | | 0.028 | 7.0 | 1645 | 0.1559 | 0.8744 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.5.1+cu124 - Datasets 3.3.0 - Tokenizers 0.21.0