xml-roberta-large-nuevo-16
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1318
- Precision: 0.8923
- Recall: 0.8973
- F1: 0.8948
- Accuracy: 0.9820
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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0787 | 1.0 | 1041 | 0.0877 | 0.8424 | 0.8579 | 0.8501 | 0.9769 |
| 0.0479 | 2.0 | 2082 | 0.0853 | 0.8625 | 0.8878 | 0.8750 | 0.9794 |
| 0.031 | 3.0 | 3123 | 0.0997 | 0.8778 | 0.8810 | 0.8794 | 0.9800 |
| 0.0223 | 4.0 | 4164 | 0.1133 | 0.8747 | 0.8833 | 0.8790 | 0.9805 |
| 0.0114 | 5.0 | 5205 | 0.1286 | 0.8877 | 0.8921 | 0.8899 | 0.9807 |
| 0.0091 | 6.0 | 6246 | 0.1318 | 0.8923 | 0.8973 | 0.8948 | 0.9820 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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FacebookAI/xlm-roberta-large