biobert-v1.1-finetuned-medmcqa-2024-11-25-T17-21-20 – AI Model by maxg73872 | AlphaNeural AI

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

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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