results
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7003
- Accuracy: 0.5660
- F1: 0.5571
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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 477 | 2.8092 | 0.2442 | 0.1739 |
| 2.961 | 2.0 | 954 | 2.4814 | 0.3187 | 0.2486 |
| 2.6582 | 3.0 | 1431 | 2.2660 | 0.3889 | 0.3370 |
| 2.3599 | 4.0 | 1908 | 2.0642 | 0.4277 | 0.3836 |
| 2.0474 | 5.0 | 2385 | 1.9820 | 0.4476 | 0.4212 |
| 1.7898 | 6.0 | 2862 | 1.9047 | 0.4738 | 0.4416 |
| 1.598 | 7.0 | 3339 | 1.7972 | 0.4937 | 0.4680 |
| 1.4538 | 8.0 | 3816 | 1.7815 | 0.5063 | 0.4805 |
| 1.2541 | 9.0 | 4293 | 1.7712 | 0.5199 | 0.4941 |
| 1.1149 | 10.0 | 4770 | 1.7398 | 0.5189 | 0.4950 |
| 0.9883 | 11.0 | 5247 | 1.7048 | 0.5304 | 0.5185 |
| 0.9024 | 12.0 | 5724 | 1.7161 | 0.5503 | 0.5390 |
| 0.7866 | 13.0 | 6201 | 1.6983 | 0.5535 | 0.5414 |
| 0.721 | 14.0 | 6678 | 1.7003 | 0.5660 | 0.5571 |
| 0.6566 | 15.0 | 7155 | 1.6980 | 0.5556 | 0.5492 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
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