SOTAVerified

A Simple Log-based Loss Function for Ordinal Text Classification

2022-10-01COLING 2022Code Available1· sign in to hype

François Castagnos, Martin Mihelich, Charles Dognin

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

The cross-entropy loss function is widely used and generally considered the default loss function for text classification. When it comes to ordinal text classification where there is an ordinal relationship between labels, the cross-entropy is not optimal as it does not incorporate the ordinal character into its feedback. In this paper, we propose a new simple loss function called ordinal log-loss (OLL). We show that this loss function outperforms state-of-the-art previously introduced losses on four benchmark text classification datasets.

Tasks

Reproductions