naver_review
This model is a fine-tuned version of beomi/kcbert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0823
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 |
|---|---|---|---|
| 0.0874 | 1.0 | 1172 | 0.0789 |
| 0.0624 | 2.0 | 2344 | 0.0755 |
| 0.0439 | 3.0 | 3516 | 0.0793 |
| 0.0315 | 4.0 | 4688 | 0.0801 |
| 0.0249 | 5.0 | 5860 | 0.0823 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for Kogasa4875/naver_review
Base model
beomi/kcbert-base