Deep Learning Brasil at ABSAPT 2022: Portuguese Transformer Ensemble Approaches
Aspect-based Sentiment Analysis (ABSA) is a task whose objective is to classify the individual sentiment polarity of all entities, called aspects, in a sentence. The task is composed of two subtasks: Aspect Term Extraction (ATE), identify all aspect terms in a sentence; and Sentiment Orientation Extraction (SOE), given a sentence and its aspect terms, the task is to determine the sentiment polarity of each aspect term (positive, negative or neutral). This article presents we present our participation in Aspect-Based Sentiment Analysis in Portuguese (ABSAPT) 2022 at IberLEF 2022. We submitted the best performing systems, achieving new state-of-the-art results on both subtasks.
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Methods
Adafactor •
Adam •
Attention Dropout •
BERT •
BPE •
DeBERTa •
Dense Connections •
Disentangled Attention Mechanism •
Dropout •
GELU •
GLU •
Inverse Square Root Schedule •
Layer Normalization •
Linear Layer •
Linear Warmup With Linear Decay •
Multi-Head Attention •
Residual Connection •
RoBERTa •
Scaled Dot-Product Attention •
SentencePiece •
Softmax •
T5 •
Weight Decay •
WordPiece
