results
This model is a fine-tuned version of klue/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6312
- Accuracy: 0.862
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: 5e-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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5964 | 1.0 | 1250 | 0.9559 | 0.572 |
| 0.4268 | 2.0 | 2500 | 0.6885 | 0.837 |
| 0.2636 | 3.0 | 3750 | 0.7075 | 0.849 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1
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Base model
klue/roberta-base