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Cardiff University at SemEval-2020 Task 6: fine-tuning BERT for domain-specific definition classification
- Source :
- International Workshop on Semantic Evaluation (SemEval 2020), SemEval@COLING
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Abstract
- We describe the system submitted to SemEval-2020 Task 6, Subtask 1. The aim of this subtask is to predict whether a given sentence contains a definition or not. Unsurprisingly, we found that strong results can be achieved by fine-tuning a pre-trained BERT language model. In this paper,we analyze the performance of this strategy. Among others, we show that results can be improved by using a two-step fine-tuning process, in which the BERT model is first fine-tuned on the full training set, and then further specialized towards a target domain.
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- International Workshop on Semantic Evaluation (SemEval 2020), SemEval@COLING
- Accession number :
- edsair.doi.dedup.....7a8dbe850aa3c8691cc98b7f7198f0d3