ynat_model
This model is a fine-tuned version of lang-brain-4 on the klue-ynat dataset. It achieves the following results on the evaluation set:
- Loss: 0.4988
- Accuracy: 0.8596
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: 64
- eval_batch_size: 64
- 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 | Accuracy |
|---|---|---|---|---|
| 0.4145 | 1.0 | 714 | 0.4453 | 0.8477 |
| 0.312 | 2.0 | 1428 | 0.3891 | 0.8565 |
| 0.2412 | 3.0 | 2142 | 0.4332 | 0.8541 |
| 0.1854 | 4.0 | 2856 | 0.4530 | 0.8596 |
| 0.1177 | 5.0 | 3570 | 0.4988 | 0.8596 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
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