Achieving_90__In_Data_Centric_Industry_Deep_Learning_Task.pdf (91.35 kB)
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Achieving 90% In Data-Centric Industry Deep Learning Task

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posted on 2022-01-07, 23:32 authored by Tong GuoTong Guo
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 in human labeling. In this paper, we illustrate our idea for a broad set of deep learning tasks, includes classification, sequence tagging, object detection, sequence generation, click-through rate prediction. The experimental results and human evaluation results verify our idea.


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