Making an optimisation algorithm 10k times faster ๐ŸŽ

How we made our multilabel classification threshold optimizer converge in minutes instead of days Multilabel classification is a common task in machine learning and Natural Language Processing (NLP). We approach it by training a model that can apply one or more labels to each new example that it sees. Since the model will output a probability for each of the labels, one of the parameters we can tweak to improve its performance (for example measured in micro f1) is the threshold probability at which a label is applied....

April 13, 2022 ยท 6 min