IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations
Jorge Balazs, Edison Marrese-Taylor, Yutaka Matsuo · 2018
In this paper we describe our system designed for the WASSA 2018 Implicit Emotion Shared Task (IEST), which obtained 2 nd place out of 30 teams with a test macro F1 score of 0.710.The system is composed of a single pre-trained ELMo layer for encoding words, a Bidirectional Long-Short Memory Network BiLSTM for enriching word representations with context, a max-pooling operation for creating sentence representations from them, and a Dense Layer for projecting the sentence representations into label space.Our official submission was obtained by ensembling 6 of these models initialized with different random seeds.The code for replicating this paper is available at https://github.com/ jabalazs/implicit_emotion.