finetuned
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the ncbi_disease dataset. It achieves the following results on the evaluation set:
- Loss: 0.0568
- Precision: 0.8246
- Recall: 0.8725
- F1: 0.8479
- Accuracy: 0.9839
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 | 170 | 0.0582 | 0.7621 | 0.8506 | 0.8040 | 0.9816 |
No log | 2.0 | 340 | 0.0588 | 0.8074 | 0.8535 | 0.8298 | 0.9828 |
0.0712 | 3.0 | 510 | 0.0568 | 0.8246 | 0.8725 | 0.8479 | 0.9839 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2
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Dataset used to train Randomui/finetuned
Evaluation results
- Precision on ncbi_diseasevalidation set self-reported0.825
- Recall on ncbi_diseasevalidation set self-reported0.873
- F1 on ncbi_diseasevalidation set self-reported0.848
- Accuracy on ncbi_diseasevalidation set self-reported0.984