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  • Continue pre-training RoBERTa-base using discharge summaries from MIMIC-III datasets.

  • Details can be found in the following paper

Xiang Dai and Ilias Chalkidis and Sune Darkner and Desmond Elliott. 2022. Revisiting Transformer-based Models for Long Document Classification. (https://arxiv.org/abs/2204.06683)

  • Important hyper-parameters
Max sequence 128
Batch size 128
Learning rate 5e-5
Training epochs 15
Training time 40 GPU-hours
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