no code implementations • 4 Sep 2017 • Pedro Saleiro, Luís Sarmento, Eduarda Mendes Rodrigues, Carlos Soares, Eugénio Oliveira
Using a single GPU, we were able to scale up vocabulary size from 2048 words embedded and 500K training examples to 32768 words over 10M training examples while keeping a stable validation loss and approximately linear trend on training time per epoch.
2 code implementations • SEMEVAL 2017 • Pedro Saleiro, Eduarda Mendes Rodrigues, Carlos Soares, Eugénio Oliveira
This paper presents the approach developed at the Faculty of Engineering of University of Porto, to participate in SemEval 2017, Task 5: Fine-grained Sentiment Analysis on Financial Microblogs and News.