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---
library_name: transformers
license: apache-2.0
base_model: beomi/kcbert-base
tags:
- HHD
- 10_class
- multi_label
- 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: 0.1558
- Lrap: 0.8820
## 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 | 0.1349 | 0.8754 |
| No log | 2.0 | 470 | 0.1374 | 0.8851 |
| 0.0472 | 3.0 | 705 | 0.1462 | 0.8795 |
| 0.0472 | 4.0 | 940 | 0.1540 | 0.8790 |
| 0.0237 | 5.0 | 1175 | 0.1558 | 0.8820 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0
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