---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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: 0.1723
- Lrap: 0.8749

## 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 | Lrap   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 235  | 0.1389          | 0.8722 |
| No log        | 2.0   | 470  | 0.1446          | 0.8749 |
| 0.049         | 3.0   | 705  | 0.1561          | 0.8744 |
| 0.049         | 4.0   | 940  | 0.1683          | 0.8629 |
| 0.025         | 5.0   | 1175 | 0.1658          | 0.8739 |
| 0.025         | 6.0   | 1410 | 0.1723          | 0.8750 |
| 0.0146        | 7.0   | 1645 | 0.1723          | 0.8749 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0