Bo-Han Fang


2021

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ntust-nlp-1 at ROCLING-2021 Shared Task: Educational Texts Dimensional Sentiment Analysis using Pretrained Language Models
Yi-Wei Wang | Wei-Zhe Chang | Bo-Han Fang | Yi-Chia Chen | Wei-Kai Huang | Kuan-Yu Chen
Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021)

This technical report aims at the ROCLING 2021 Shared Task: Dimensional Sentiment Analysis for Educational Texts. In order to predict the affective states of Chinese educational texts, we present a practical framework by employing pre-trained language models, such as BERT and MacBERT. Several valuable observations and analyses can be drawn from a series of experiments. From the results, we find that MacBERT-based methods can deliver better results than BERT-based methods on the verification set. Therefore, we average the prediction results of several models obtained using different settings as the final output.