metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: biolinkbert-base-medqa-usmle-MPNet-context
results: []
biolinkbert-base-medqa-usmle-MPNet-context
This model is a fine-tuned version of michiyasunaga/BioLinkBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4506
- Accuracy: 0.3936
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 1.3518 | 0.3354 |
| 1.3648 | 2.0 | 636 | 1.3308 | 0.3684 |
| 1.3648 | 3.0 | 954 | 1.3267 | 0.3943 |
| 1.2711 | 4.0 | 1272 | 1.3455 | 0.3865 |
| 1.1769 | 5.0 | 1590 | 1.3739 | 0.3943 |
| 1.1769 | 6.0 | 1908 | 1.3960 | 0.4069 |
| 1.0815 | 7.0 | 2226 | 1.4320 | 0.3959 |
| 1.0092 | 8.0 | 2544 | 1.4506 | 0.3936 |
Framework versions
- Transformers 4.27.2
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2