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The Re-Label Method For Data-Centric Machine Learning

Guo, Tong
arXiv (All) · Papers
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computation-and-languagemachine-learning
In industry deep learning application, our manually labeled data has a certain number of noisy data. To solve this problem and achieve more than 90 score in dev dataset, we present a simple method to find the noisy data and re-label the noisy data by human, given the model predictions as references
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