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README.md
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datasets:
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- adsabs/WIESP2022-NER
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- jxhzxn/contributions-ner-cs
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language:
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- en
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tags:
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PCSciBERT_cased was initiated with the cased variant of SciBERT (https://huggingface.co/allenai/scibert_scivocab_cased) and pre-trained on texts from 1,560,661 research articles of the physics and computer science domain in arXiv.
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The tokenizer for PCSciBERT_cased uses the same vocabulary from allenai/scibert_scivocab_cased.
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---
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datasets:
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- adsabs/WIESP2022-NER
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language:
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- en
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tags:
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---
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PCSciBERT_cased was initiated with the cased variant of SciBERT (https://huggingface.co/allenai/scibert_scivocab_cased) and pre-trained on texts from 1,560,661 research articles of the physics and computer science domain in arXiv.
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The tokenizer for PCSciBERT_cased uses the same vocabulary from allenai/scibert_scivocab_cased.
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The model was also evaluated on its downstream performance in named entity recognition using the adsabs/WIESP2022-NER and CS-NER (https://github.com/jd-coderepos/contributions-ner-cs/tree/main) dataset. Overall, PCSciBERT_cased achieved higher micro F1 scores for both WIESP and CS-NER datasets.\\
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It improves the performance of SciBERT(cased) on CS-NER test dataset by 0.69% and on WIESP test dataset by 1.49%.
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