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---
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: med_masked_pubmed_articles_biogpt_large
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# med_masked_pubmed_articles_biogpt_large
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This model is a fine-tuned version of [microsoft/BioGPT-Large-PubMedQA](https://huggingface.co/microsoft/BioGPT-Large-PubMedQA) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.2545
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- Rouge2 Precision: 0.7011
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- Rouge2 Recall: 0.6931
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- Rouge2 Fmeasure: 0.6959
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
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| 3.0566 | 1.0 | 7914 | 3.0375 | 0.7013 | 0.6931 | 0.6959 |
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| 2.911 | 2.0 | 15828 | 3.0228 | 0.7013 | 0.6931 | 0.6959 |
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| 2.7386 | 3.0 | 23742 | 3.0594 | 0.7011 | 0.6931 | 0.6959 |
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| 2.5718 | 4.0 | 31656 | 3.1371 | 0.7011 | 0.6931 | 0.6959 |
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| 2.4573 | 5.0 | 39570 | 3.2545 | 0.7011 | 0.6931 | 0.6959 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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