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---
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
should probably proofread and complete it, then remove this comment. -->
# 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: 0.1869
- Irap: 0.8724
## 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 | Irap |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 235 | 0.1567 | 0.8739 |
| No log | 2.0 | 470 | 0.1518 | 0.8749 |
| 0.029 | 3.0 | 705 | 0.1718 | 0.8742 |
| 0.029 | 4.0 | 940 | 0.1803 | 0.8707 |
| 0.0165 | 5.0 | 1175 | 0.1808 | 0.8731 |
| 0.0165 | 6.0 | 1410 | 0.1850 | 0.8739 |
| 0.009 | 7.0 | 1645 | 0.1869 | 0.8724 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0
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