Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)
Task Training huge unsupervised deep neural networks yields to strong progress in the field of Natural Language Processing (NLP). Using these extensively pre-trained networks for particular NLP applications is the current state-of-the-art approach. In this project, we approach the task of ranking possible clarifying questions for a given query. We fine-tuned a pre-trained BERT model to rank the possible clarifying questions in a classification manner. The achieved model scores a top-5 accuracy of 0.4565 on the provided benchmark dataset. Installation […]
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