biolinkbert-base-medqa-usmle-nocontext
This model is a fine-tuned version of michiyasunaga/BioLinkBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5149
- Accuracy: 0.3943
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: 64
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 0.98 | 39 | 1.3339 | 0.3590 |
No log | 1.98 | 78 | 1.3685 | 0.3794 |
No log | 2.98 | 117 | 1.4162 | 0.3912 |
No log | 3.98 | 156 | 1.4484 | 0.3888 |
No log | 4.98 | 195 | 1.4869 | 0.3983 |
No log | 5.98 | 234 | 1.5149 | 0.3943 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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