--- 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_result results: [] --- # bert_model_result 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: 0.1646 - Lrap: 0.8742 ## 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 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 | Lrap | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 1.0 | 235 | 0.1287 | 0.8744 | | No log | 2.0 | 470 | 0.1332 | 0.8779 | | 0.0658 | 3.0 | 705 | 0.1450 | 0.8776 | | 0.0658 | 4.0 | 940 | 0.1533 | 0.8740 | | 0.0319 | 5.0 | 1175 | 0.1569 | 0.8757 | | 0.0319 | 6.0 | 1410 | 0.1632 | 0.8715 | | 0.018 | 7.0 | 1645 | 0.1646 | 0.8742 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Datasets 3.3.0 - Tokenizers 0.21.0