---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- medmcqa
metrics:
- accuracy
model-index:
- name: OntoMedQA
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# OntoMedQA

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/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