pubmedbert-abstract
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4618
- Accuracy: 0.9501
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 | 0.2340 | 0.9386 |
| 0.1776 | 2.0 | 1582 | 0.2716 | 0.9419 |
| 0.0855 | 3.0 | 2373 | 0.2730 | 0.9431 |
| 0.0627 | 4.0 | 3164 | 0.3323 | 0.9382 |
| 0.0627 | 5.0 | 3955 | 0.3308 | 0.9451 |
| 0.0463 | 6.0 | 4746 | 0.3986 | 0.9412 |
| 0.0308 | 7.0 | 5537 | 0.4211 | 0.9419 |
| 0.0312 | 8.0 | 6328 | 0.3616 | 0.9437 |
| 0.0221 | 9.0 | 7119 | 0.4310 | 0.9396 |
| 0.0221 | 10.0 | 7910 | 0.4222 | 0.9438 |
| 0.0181 | 11.0 | 8701 | 0.4185 | 0.9445 |
| 0.0141 | 12.0 | 9492 | 0.4678 | 0.9456 |
| 0.0133 | 13.0 | 10283 | 0.4027 | 0.9503 |
| 0.0082 | 14.0 | 11074 | 0.4504 | 0.9473 |
| 0.0082 | 15.0 | 11865 | 0.4760 | 0.9505 |
| 0.0052 | 16.0 | 12656 | 0.4573 | 0.9449 |
| 0.0042 | 17.0 | 13447 | 0.4356 | 0.9522 |
| 0.0037 | 18.0 | 14238 | 0.4577 | 0.9487 |
| 0.0024 | 19.0 | 15029 | 0.4642 | 0.9493 |
| 0.0024 | 20.0 | 15820 | 0.4618 | 0.9501 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2