metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clinical-bigbird-medqa-usmle-nocontext
results: []
clinical-bigbird-medqa-usmle-nocontext
This model is a fine-tuned version of yikuan8/Clinical-BigBird on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3863
- Accuracy: 0.2482
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- 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 | 159 | 1.3860 | 0.2584 |
| No log | 2.0 | 318 | 1.3859 | 0.2820 |
| No log | 3.0 | 477 | 1.3863 | 0.2522 |
| 1.3891 | 4.0 | 636 | 1.3863 | 0.2498 |
| 1.3891 | 5.0 | 795 | 1.3863 | 0.2404 |
| 1.3891 | 6.0 | 954 | 1.3863 | 0.2498 |
| 1.3882 | 7.0 | 1113 | 1.3863 | 0.2506 |
| 1.3882 | 8.0 | 1272 | 1.3863 | 0.2467 |
| 1.3882 | 9.0 | 1431 | 1.3863 | 0.2490 |
| 1.3876 | 10.0 | 1590 | 1.3863 | 0.2482 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2