reptile-classifier-ko
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: 0.8473
- Accuracy: 0.8571
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: 8
- eval_batch_size: 8
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 4 | 1.4946 | 0.4286 |
| No log | 2.0 | 8 | 1.3567 | 0.4286 |
| 1.5809 | 3.0 | 12 | 1.2038 | 0.5714 |
| 1.5809 | 4.0 | 16 | 1.0654 | 0.7143 |
| 1.0943 | 5.0 | 20 | 0.9427 | 0.7143 |
| 1.0943 | 6.0 | 24 | 0.8473 | 0.8571 |
| 1.0943 | 7.0 | 28 | 0.7914 | 0.8571 |
| 0.6992 | 8.0 | 32 | 0.7475 | 0.8571 |
| 0.6992 | 9.0 | 36 | 0.7274 | 0.8571 |
| 0.5718 | 10.0 | 40 | 0.7207 | 0.8571 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.8.0
- Datasets 4.0.0
- Tokenizers 0.21.4
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beomi/kcbert-base