XML-roberta-conll2002-ner-2025-32-10
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: 0.0763
- Precision: 0.8665
- Recall: 0.8782
- F1: 0.8723
- Accuracy: 0.9817
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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0777 | 1.0 | 1041 | 0.0972 | 0.8325 | 0.8596 | 0.8459 | 0.9776 |
| 0.0628 | 2.0 | 2082 | 0.0850 | 0.8429 | 0.8569 | 0.8499 | 0.9790 |
| 0.0528 | 3.0 | 3123 | 0.0735 | 0.8653 | 0.8789 | 0.8721 | 0.9818 |
| 0.0483 | 4.0 | 4164 | 0.0737 | 0.8663 | 0.8772 | 0.8717 | 0.9817 |
| 0.0397 | 5.0 | 5205 | 0.0777 | 0.8692 | 0.8777 | 0.8734 | 0.9819 |
| 0.0391 | 6.0 | 6246 | 0.0763 | 0.8665 | 0.8782 | 0.8723 | 0.9817 |
Framework versions
- PEFT 0.18.0
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 2.14.7
- Tokenizers 0.22.1
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FacebookAI/xlm-roberta-large