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We undertake the model ESRM mentioned in Section Exercise Semantic Representation Module stacked with a binary classifier head to tell apart the duplicate pairs.<br><br><br><br> The query exercise and candidate exercise are processed talked about in Section Data Pre-processing and concatenated as the enter of ESRM model. The coaching labels are in the form mentioned in Section Data Pre-processing. We plan to collect a substantial amount of coaching information and use it both to tremendous-tune pretrained language fashions and [https://repo.amhost.net/brittseaborn60/aquasculpt-metabolism-booster1983/-/issues/10 AquaSculpt weight loss support] to prepare transformer fashions from scratch. We adopt transformer because the backbone encoder which is shared by means of the three steps. In different exercises of different datasets, the variety of LSTM layers varies from one to three layers. 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By summing the outputs of the sequential neural network at consecutive timestamps, will probably be transformed to a many-to-one sequential neural network and is educated to output the number of repetitions.<br> | ||
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