roberta-large-bne-capitel-ner-finetuned-ner
This model is a fine-tuned version of PlanTL-GOB-ES/roberta-large-bne-capitel-ner on the biobert_json dataset. It achieves the following results on the evaluation set:
- Loss: 0.0918
- Precision: 0.9574
- Recall: 0.9659
- F1: 0.9616
- 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: 8
- eval_batch_size: 8
- 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 |
---|---|---|---|---|---|---|---|
0.1292 | 1.0 | 1224 | 0.0942 | 0.9455 | 0.9528 | 0.9491 | 0.9737 |
0.0813 | 2.0 | 2448 | 0.0960 | 0.9443 | 0.9696 | 0.9568 | 0.9780 |
0.0509 | 3.0 | 3672 | 0.0819 | 0.9559 | 0.9686 | 0.9622 | 0.9814 |
0.0314 | 4.0 | 4896 | 0.0853 | 0.9557 | 0.9694 | 0.9625 | 0.9811 |
0.0196 | 5.0 | 6120 | 0.0918 | 0.9574 | 0.9659 | 0.9616 | 0.9810 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
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Base model
PlanTL-GOB-ES/roberta-large-bne-capitel-nerEvaluation results
- Precision on biobert_jsonvalidation set self-reported0.957
- Recall on biobert_jsonvalidation set self-reported0.966
- F1 on biobert_jsonvalidation set self-reported0.962
- Accuracy on biobert_jsonvalidation set self-reported0.981