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+### BERT (double)
+Model and tokenizer files for BERT (double) model from [When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset](https://arxiv.org/abs/2104.08671).
+
+### Training Data
+BERT (double) is pretrained using the same English Wikipedia corpus that the base BERT model (uncased, 110M parameters), [bert-base-uncased](https://huggingface.co/bert-base-uncased), was pretrained on. For more information on the pretraining corpus, refer to the [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/abs/1810.04805) paper.
+
+### Training Objective
+This model is initialized with the base BERT model (uncased, 110M parameters), [bert-base-uncased](https://huggingface.co/bert-base-uncased), and trained for an additional 1M steps on the MLM and NSP objective. 
+
+This facilitates a direct comparison to our BERT-based models for the legal domain, which are also pretrained for 2M total steps.
+- Legal-BERT: zlucia/legalbert (https://huggingface.co/zlucia/legalbert)
+- Custom Legal-BERT: zlucia/custom-legalbert (https://huggingface.co/zlucia/custom-legalbert)
+
+### Usage
+Please see the [casehold repository](https://github.com/reglab/casehold) for scripts that support computing pretrain loss and finetuning on BERT (double) for classification and multiple choice tasks described in the paper: Overruling, Terms of Service, CaseHOLD.
+
+### Citation
+	@inproceedings{zhengguha2021,
+		title={When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset},
+		author={Lucia Zheng and Neel Guha and Brandon R. Anderson and Peter Henderson and Daniel E. Ho},
+		year={2021},
+		eprint={2104.08671},
+		archivePrefix={arXiv},
+		primaryClass={cs.CL},
+		booktitle={Proceedings of the 18th International Conference on Artificial Intelligence and Law},
+		publisher={Association for Computing Machinery},
+		note={(in press)}
+	}
+
+Lucia Zheng, Neel Guha, Brandon R. Anderson, Peter Henderson, and Daniel E. Ho. 2021. When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset. In *Proceedings of the 18th International Conference on Artificial Intelligence and Law (ICAIL '21)*, June 21-25, 2021, São Paulo, Brazil. ACM Inc., New York, NY, (in press). arXiv: [2104.08671 \[cs.CL\]](https://arxiv.org/abs/2104.08671).