biobert-v1.1-finetuned-medmcqa-2024-11-25-T17-21-20

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.2111
• Accuracy: 0.5742
• F1: 0.5753

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: 0.000159
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 128
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.7483	0.9939	142	0.9367	0.5613	0.5628
0.6026	1.9921	284	0.9227	0.5685	0.5693
0.3491	2.9904	426	1.2111	0.5742	0.5753
0.2135	3.9956	569	1.5260	0.5697	0.5704
0.114	4.9869	710	1.9557	0.5666	0.5672

Framework versions

• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3