biobert-v1.1-finetuned-medmcqa

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.9408
• Accuracy: {'accuracy': 0.6190476190476191}
• F1-score: {'f1': 0.6383219954648526}

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-06
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1-score
No log	1.0	229	1.1779	{'accuracy': 0.5714285714285714}	{'f1': 0.5936070334566574}
No log	2.0	458	0.9840	{'accuracy': 0.6666666666666666}	{'f1': 0.6800653594771241}
1.1746	3.0	687	0.9408	{'accuracy': 0.6190476190476191}	{'f1': 0.6383219954648526}

Framework versions

• Transformers 4.44.2
• Pytorch 2.5.0+cu121
• Datasets 3.1.0
• Tokenizers 0.19.1