2022
EMNLP
EMNLP 2022
Yet at the FinNLP-2022 ERAI Task: Modified models for evaluating the Rationales of Amateur Investors
Abstract
AbstractThe financial reports usually reveal the recent development of the company and often cause the volatility in the company’s share price. The opinions causing higher maximal potential profit and lower maximal loss can help the amateur investors choose rational strategies. FinNLP-2022 ERAI task aims to quantify the opinions’ potentials of leading higher maximal potential profit and lower maximal loss. In this paper, different strategies were applied to solve the ERAI tasks. Valinna ‘RoBERTa-wwm’ showed excellent performance and helped us rank second in ‘MPP’ label prediction task. After integrating some tricks, the modified ‘RoBERTa-wwm’ outperformed all other models in ‘ML’ ranking task.
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Core Methods > Classification
Machine Learning > Core Methods > Regression
Machine Learning > Application Areas > Domain Adaptation
Natural Language Processing > Applications > Text Classification
Natural Language Processing > Applications > Sentiment Analysis
Deep Learning > Models > Transformers
Deep Learning > Techniques > Fine-Tuning
Deep Learning > Learning Types > Classification