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OntoMedQA

This model is a fine-tuned version of bert-base-uncased on the medmcqa dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2874
  • Accuracy: 0.4118

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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 187 1.2418 0.2941
No log 2.0 374 1.1449 0.4706
0.8219 3.0 561 1.2874 0.4118

Framework versions

  • Transformers 4.21.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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Dataset used to train sahillihas/OntoMedQA