id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-246317-wz7epr3n	Wang, Wei-Yao	EmotionGIF-Yankee: A Sentiment Classifier with Robust Model Based Ensemble Methods	2020-07-05		.txt	text/plain	3270	229	61	We preprocess original tweet data to pre-trained language model, then fine-tune to multi-label classification model. Our study can be mainly divided into three topics, including multi-label classification, pre-trained models, and ensemble methods. Also, deep learning models are introduced to solve the multi-label classification problem, and have been proved that such models are able to extract high-level features from raw data. Secondly, a strength pre-trained language model can generate deep contextual word representation which means a word token can have several representation in different sentences. (2) Our goal aims to get better performance instead of efficiency, we use RoBERTa-base, BERT-basecased, and BERT-base-uncased to individually train language model and fine-tune to multi-label classification model. Since RoBERTa and BERT use different input formats, and our dataset has pair of sequences text and reply in each tweet, we convert input sentences based on corresponding models.	./cache/cord-246317-wz7epr3n.txt	./txt/cord-246317-wz7epr3n.txt