xlm-roberta-large-finetuned-conll03-english-finetuned-ner
This model is a fine-tuned version of FacebookAI/xlm-roberta-large-finetuned-conll03-english on the biobert_json dataset. It achieves the following results on the evaluation set:
- Loss: 0.0876
- Precision: 0.9477
- Recall: 0.9725
- F1: 0.9599
- Accuracy: 0.9810
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.255 | 1.0 | 612 | 0.0956 | 0.9305 | 0.9638 | 0.9468 | 0.9749 |
0.0997 | 2.0 | 1224 | 0.0871 | 0.9397 | 0.9740 | 0.9565 | 0.9795 |
0.0711 | 3.0 | 1836 | 0.0848 | 0.9474 | 0.9718 | 0.9595 | 0.9806 |
0.0552 | 4.0 | 2448 | 0.0860 | 0.9464 | 0.9744 | 0.9602 | 0.9808 |
0.0354 | 5.0 | 3060 | 0.0876 | 0.9477 | 0.9725 | 0.9599 | 0.9810 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Evaluation results
- Precision on biobert_jsonvalidation set self-reported0.948
- Recall on biobert_jsonvalidation set self-reported0.972
- F1 on biobert_jsonvalidation set self-reported0.960
- Accuracy on biobert_jsonvalidation set self-reported0.981