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biobert-v1.1-finetuned-medmcqa-2024-11-30-T11-04-13 – AI Model by maxg73872 | AlphaNeural AI
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biobert-v1.1-finetuned-medmcqa-2024-11-30-T11-04-13
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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-2024-11-30-T11-04-13
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: 0.9072
Accuracy: 0.5847
F1: 0.5855
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
0.7477
0.9997
1428
0.9334
0.5573
0.5583
0.5585
1.9996
2856
0.9072
0.5847
0.5855
0.4556
2.9996
4284
1.0348
0.5754
0.5767
Framework versions
Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
