gene_finetuned
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the biocreative_gene_mention dataset. It achieves the following results on the evaluation set:
- Loss: 0.1217
- Precision: 0.8389
- Recall: 0.8738
- F1: 0.8560
- Accuracy: 0.9582
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 157 | 0.1379 | 0.7838 | 0.8403 | 0.8111 | 0.9487 |
| No log | 2.0 | 314 | 0.1188 | 0.8394 | 0.8642 | 0.8516 | 0.9570 |
| No log | 3.0 | 471 | 0.1217 | 0.8389 | 0.8738 | 0.8560 | 0.9582 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2
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Evaluation results
- Precision on biocreative_gene_mentionvalidation set self-reported0.839
- Recall on biocreative_gene_mentionvalidation set self-reported0.874
- F1 on biocreative_gene_mentionvalidation set self-reported0.856
- Accuracy on biocreative_gene_mentionvalidation set self-reported0.958