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README.md
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This is one of the 3 further pre-trained models from the SpaceTransformers family presented in [SpaceTransformers: Language Modeling for Space Systems](https://ieeexplore.ieee.org/document/9548078). The original Git repo is [strath-ace/smart-nlp](https://github.com/strath-ace/smart-nlp).
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The further pre-training corpus includes publications abstracts, books, and Wikipedia pages related to space systems. Corpus size is 14.3 GB. SpaceSciBERT was further pre-trained on this domain-specific corpus from [SciBERT-SciVocab (uncased)](https://huggingface.co/allenai/scibert_scivocab_uncased). In our paper, it is then fine-tuned for a Concept Recognition task.
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@ARTICLE{
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9548078,
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author={Berquand, Audrey and Darm, Paul and Riccardi, Annalisa},
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number={},
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pages={133111-133122},
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doi={10.1109/ACCESS.2021.3115659}
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}
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### SpaceSciBERT
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This is one of the 3 further pre-trained models from the SpaceTransformers family presented in [SpaceTransformers: Language Modeling for Space Systems](https://ieeexplore.ieee.org/document/9548078). The original Git repo is [strath-ace/smart-nlp](https://github.com/strath-ace/smart-nlp).
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The further pre-training corpus includes publications abstracts, books, and Wikipedia pages related to space systems. Corpus size is 14.3 GB. SpaceSciBERT was further pre-trained on this domain-specific corpus from [SciBERT-SciVocab (uncased)](https://huggingface.co/allenai/scibert_scivocab_uncased). In our paper, it is then fine-tuned for a Concept Recognition task.
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### BibTeX entry and citation info
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```
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@ARTICLE{
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9548078,
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author={Berquand, Audrey and Darm, Paul and Riccardi, Annalisa},
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number={},
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pages={133111-133122},
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doi={10.1109/ACCESS.2021.3115659}
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}
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```
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