biobert-v1.1-finetuned-medmcqa-2024-11-25-T16-48-24 – AI Model by maxg73872 | AlphaNeural AI

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biobert-v1.1-finetuned-medmcqa-2024-11-25-T16-48-24

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dmis-lab/biobert-v1.1

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biobert-v1.1-finetuned-medmcqa-2024-11-25-T16-48-24

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: 0.7763
Accuracy: 0.8095
F1: 0.8138

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
1.3838	0.9739	14	1.0207	0.6905	0.6764
1.086	1.9478	28	0.9525	0.6190	0.6189
0.6655	2.9913	43	0.7763	0.8095	0.8138
0.5349	3.9652	57	0.8631	0.7381	0.7368
0.3138	4.8696	70	0.8401	0.7857	0.7854

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3