--- 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: 0.2393 - Lrap: 0.8715 ## 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: 16 - eval_batch_size: 16 - 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 | Lrap | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.0202 | 1.0 | 938 | 0.2017 | 0.8627 | | 0.0157 | 2.0 | 1876 | 0.2041 | 0.8702 | | 0.0112 | 3.0 | 2814 | 0.2157 | 0.8713 | | 0.0055 | 4.0 | 3752 | 0.2221 | 0.8730 | | 0.0039 | 5.0 | 4690 | 0.2327 | 0.8715 | | 0.0035 | 6.0 | 5628 | 0.2384 | 0.8722 | | 0.0024 | 7.0 | 6566 | 0.2393 | 0.8715 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.5.1+cu124 - Datasets 3.3.0 - Tokenizers 0.21.0