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biobert-v1.1-finetuned-medmcqa-100-2024-11-30-T09-48-50 – AI Model by maxg73872 | AlphaNeural AI
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biobert-v1.1-finetuned-medmcqa-100-2024-11-30-T09-48-50
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transformers
safetensors
bert
multiple-choice
generated_from_trainer
dmis-lab/biobert-v1.1
finetune
endpoints_compatible
us
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biobert-v1.1-finetuned-medmcqa-100-2024-11-30-T09-48-50
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: 1.3905
Accuracy: 0.39
F1: 0.3970
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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
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: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
No log
0.96
3
1.3834
0.36
0.3619
No log
1.92
6
1.3872
0.36
0.3609
No log
2.88
9
1.3905
0.39
0.3970
Framework versions
Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
