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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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