NER-finetuning-XML-RoBERTa-BIOBERT
This model is a fine-tuned version of raulgdp/xml-roberta-large-finetuned-ner on the biobert_json dataset. It achieves the following results on the evaluation set:
- Loss: 0.0946
- Precision: 0.9498
- Recall: 0.9714
- F1: 0.9605
- Accuracy: 0.9814
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.1306 | 1.0 | 1224 | 0.1013 | 0.9299 | 0.9609 | 0.9451 | 0.9735 |
0.0996 | 2.0 | 2448 | 0.0932 | 0.9383 | 0.9656 | 0.9517 | 0.9777 |
0.0608 | 3.0 | 3672 | 0.0865 | 0.9493 | 0.9720 | 0.9605 | 0.9813 |
0.0445 | 4.0 | 4896 | 0.0927 | 0.9531 | 0.9729 | 0.9629 | 0.9819 |
0.0327 | 5.0 | 6120 | 0.0946 | 0.9498 | 0.9714 | 0.9605 | 0.9814 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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raulgdp/xml-roberta-large-finetuned-ner
Evaluation results
- Precision on biobert_jsonvalidation set self-reported0.950
- Recall on biobert_jsonvalidation set self-reported0.971
- F1 on biobert_jsonvalidation set self-reported0.960
- Accuracy on biobert_jsonvalidation set self-reported0.981