---
license: mit
tags:
- generated_from_trainer
model-index:
- name: med_masked_pubmed_articles_biogpt_large
  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. -->

# med_masked_pubmed_articles_biogpt_large

This model is a fine-tuned version of [microsoft/BioGPT-Large-PubMedQA](https://huggingface.co/microsoft/BioGPT-Large-PubMedQA) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2545
- Rouge2 Precision: 0.7011
- Rouge2 Recall: 0.6931
- Rouge2 Fmeasure: 0.6959

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 3.0566        | 1.0   | 7914  | 3.0375          | 0.7013           | 0.6931        | 0.6959          |
| 2.911         | 2.0   | 15828 | 3.0228          | 0.7013           | 0.6931        | 0.6959          |
| 2.7386        | 3.0   | 23742 | 3.0594          | 0.7011           | 0.6931        | 0.6959          |
| 2.5718        | 4.0   | 31656 | 3.1371          | 0.7011           | 0.6931        | 0.6959          |
| 2.4573        | 5.0   | 39570 | 3.2545          | 0.7011           | 0.6931        | 0.6959          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2