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