| --- |
| 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 |
| 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. --> |
|
|
| # bert_model |
| |
| 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: 0.1308 |
| - Lrap: 0.8803 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## 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: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Lrap | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | No log | 1.0 | 235 | 0.1478 | 0.8586 | |
| | No log | 2.0 | 470 | 0.1278 | 0.8726 | |
| | 0.1715 | 3.0 | 705 | 0.1246 | 0.8797 | |
| | 0.1715 | 4.0 | 940 | 0.1278 | 0.8800 | |
| | 0.079 | 5.0 | 1175 | 0.1308 | 0.8803 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.47.1 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.3.0 |
| - Tokenizers 0.21.0 |
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|
