---
library_name: transformers
license: mit
base_model: gpt2
tags:
- generated_from_trainer
datasets:
- medqa_corpus_en
model-index:
- name: gpt2-medqa
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# gpt2-medqa

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the medqa_corpus_en dataset.
It achieves the following results on the evaluation set:
- Loss: 5.7186

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 469  | 6.3476          |
| 7.4059        | 2.0   | 938  | 5.8686          |
| 6.1689        | 3.0   | 1407 | 5.7186          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0