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BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6748
- Accuracy: 0.72
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: 1e-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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 57 | 0.8396 | 0.58 |
No log | 2.0 | 114 | 0.8608 | 0.58 |
No log | 3.0 | 171 | 0.7642 | 0.68 |
No log | 4.0 | 228 | 0.8196 | 0.64 |
No log | 5.0 | 285 | 0.6477 | 0.72 |
No log | 6.0 | 342 | 0.6861 | 0.72 |
No log | 7.0 | 399 | 0.6735 | 0.74 |
No log | 8.0 | 456 | 0.6516 | 0.72 |
0.6526 | 9.0 | 513 | 0.6707 | 0.72 |
0.6526 | 10.0 | 570 | 0.6748 | 0.72 |
Framework versions
- Transformers 4.10.2
- Pytorch 1.9.0+cu102
- Datasets 1.12.0
- Tokenizers 0.10.3
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Evaluation results
- Accuracyself-reported0.720