BioBERT_BioNLP13CG_NER_new
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1721
- Precision: 0.8444
- Recall: 0.8396
- F1: 0.8420
- Accuracy: 0.9571
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 191 | 0.2112 | 0.8333 | 0.8134 | 0.8232 | 0.9507 |
| No log | 2.0 | 382 | 0.1744 | 0.8304 | 0.8400 | 0.8352 | 0.9557 |
| 0.3204 | 3.0 | 573 | 0.1721 | 0.8444 | 0.8396 | 0.8420 | 0.9571 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Inference Providers
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Model tree for judithrosell/BioBERT_BioNLP13CG_NER_new
Base model
dmis-lab/biobert-v1.1