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language: |
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- en |
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pipeline_tag: text-classification |
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# Span NLI BERT (base) |
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This is a **BERT-base** model ([`bert-base-uncased`][2]) fine-tuned on the [**ContractNLI**][3] dataset (non-disclosure agreements) with the **Span NLI BERT** model architecture, |
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from [*ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts* (Koreeda and Manning, 2021)][1]. |
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For a hypothesis, the **Span NLI BERT** model predicts NLI labels and identifies evidence for documents as premises. |
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Spans of documents should be pre-annotated; evidence is always full sentences or items in an enumerated list in the document. |
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For details of the architecture and usage of the relevant training/testing scripts, check out the paper and their [Github repo][4]. |
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This model is fine-tuned according to the hyperparameters in `data/conf_base.yml` in their repo, |
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which differs from their hyperparameters that produced the best dev scores as noted in the Appendix of the paper. |
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ArXiv: <https://arxiv.org/abs/2110.01799> |
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[1]: https://aclanthology.org/2021.findings-emnlp.164/ |
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[2]: https://huggingface.co/bert-base-uncased |
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[3]: https://stanfordnlp.github.io/contract-nli/ |
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[4]: https://github.com/stanfordnlp/contract-nli-bert |
