pubmedbert-fulltext
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4548
- Accuracy: 0.9498
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 791 | 0.2502 | 0.9342 |
| 0.1717 | 2.0 | 1582 | 0.2889 | 0.9449 |
| 0.0792 | 3.0 | 2373 | 0.2844 | 0.9424 |
| 0.0565 | 4.0 | 3164 | 0.3055 | 0.9377 |
| 0.0565 | 5.0 | 3955 | 0.3059 | 0.9458 |
| 0.0405 | 6.0 | 4746 | 0.3693 | 0.9451 |
| 0.0274 | 7.0 | 5537 | 0.3295 | 0.9438 |
| 0.0263 | 8.0 | 6328 | 0.4278 | 0.9337 |
| 0.0181 | 9.0 | 7119 | 0.3807 | 0.9465 |
| 0.0181 | 10.0 | 7910 | 0.4318 | 0.9442 |
| 0.0173 | 11.0 | 8701 | 0.3995 | 0.9487 |
| 0.011 | 12.0 | 9492 | 0.4487 | 0.9466 |
| 0.0077 | 13.0 | 10283 | 0.4247 | 0.9482 |
| 0.0075 | 14.0 | 11074 | 0.5082 | 0.9433 |
| 0.0075 | 15.0 | 11865 | 0.4722 | 0.9458 |
| 0.0071 | 16.0 | 12656 | 0.4134 | 0.9507 |
| 0.0034 | 17.0 | 13447 | 0.4252 | 0.9496 |
| 0.0033 | 18.0 | 14238 | 0.4436 | 0.9500 |
| 0.0023 | 19.0 | 15029 | 0.4481 | 0.9505 |
| 0.0023 | 20.0 | 15820 | 0.4548 | 0.9498 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2