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biobert-v1.1-finetuned-medmcqa-20pct-2024-12-03-T13-24-56 – AI Model by maxg73872 | AlphaNeural AI
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biobert-v1.1-finetuned-medmcqa-20pct-2024-12-03-T13-24-56
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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-20pct-2024-12-03-T13-24-56
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: 0.9330
Accuracy: 0.5671
F1: 0.5680
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
0.7195
0.9995
1142
0.9801
0.5381
0.5402
0.5306
1.9999
2285
0.9330
0.5671
0.5680
0.3505
2.9986
3426
1.0417
0.5618
0.5628
Framework versions
Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
