---
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: 0.1563
- Lrap: 0.8747

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Lrap   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 235  | 0.1368          | 0.8723 |
| No log        | 2.0   | 470  | 0.1419          | 0.8762 |
| 0.0519        | 3.0   | 705  | 0.1512          | 0.8737 |
| 0.0519        | 4.0   | 940  | 0.1553          | 0.8742 |
| 0.0263        | 5.0   | 1175 | 0.1563          | 0.8747 |


### Framework versions

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