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---
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
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