xml-roberta-large-finetuned-ner-finetuned-ner-biobert
This model is a fine-tuned version of raulgdp/xml-roberta-large-finetuned-ner on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0856
- Precision: 0.9484
- Recall: 0.9716
- F1: 0.9598
- Accuracy: 0.9803
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: 32
- eval_batch_size: 32
- 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 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 306 | 0.0922 | 0.9395 | 0.9549 | 0.9471 | 0.9755 |
0.2344 | 2.0 | 612 | 0.0871 | 0.9392 | 0.9675 | 0.9531 | 0.9779 |
0.2344 | 3.0 | 918 | 0.0795 | 0.9466 | 0.9721 | 0.9592 | 0.9805 |
0.0653 | 4.0 | 1224 | 0.0836 | 0.9477 | 0.9703 | 0.9589 | 0.9801 |
0.0456 | 5.0 | 1530 | 0.0856 | 0.9484 | 0.9716 | 0.9598 | 0.9803 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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