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@@ -74,4 +74,24 @@ The following hyperparameters were used during training:
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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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- 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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- # Paper Details
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- If you want to know about the full implementation detials, please read the full paper here
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https://www.researchgate.net/publication/375011546_Question_Answering_on_Biomedical_Research_Papers_using_Transfer_Learning_on_BERT-Base_Models
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## Citation Plain Text
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S. Pudasaini and S. Shakya, "Question Answering on Biomedical Research Papers using Transfer Learning on BERT-Base Models," 2023 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Kirtipur, Nepal, 2023, pp. 496-501, doi: 10.1109/I-SMAC58438.2023.10290240.
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## Citation Bibtex
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@INPROCEEDINGS{10290240,
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author={Pudasaini, Shushanta and Shakya, Subarna},
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booktitle={2023 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)},
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title={Question Answering on Biomedical Research Papers using Transfer Learning on BERT-Base Models},
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year={2023},
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volume={},
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number={},
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pages={496-501},
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doi={10.1109/I-SMAC58438.2023.10290240}}
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