{"title":"YNU_OXZ @ HaSpeeDe 2 and AMI : XLM-RoBERTa with Ordered Neurons LSTM for Classification Task at EVALITA 2020","authors":"Xiaozhi Ou, Hongling Li","doi":"10.4000/BOOKS.AACCADEMIA.6912","DOIUrl":null,"url":null,"abstract":"English. This paper describes the system that team YNU OXZ submitted for EVALITA 2020. We participate in the shared task on Automatic Misogyny Identification (AMI) and Hate Speech Detection (HaSpeeDe 2) at the 7th evaluation campaign EVALITA 2020. For HaSpeeDe 2, we participate in Task A Hate Speech Detection and submitted two-run results for the news headline test and tweets headline test, respectively. Our submitted run is based on the pre-trained multilanguage model XLM-RoBERTa, and input into Convolution Neural Network and K-max Pooling (CNN + K-max Pooling). Then, an Ordered Neurons LSTM (ONLSTM) is added to the previous representation and submitted to a linear decision function. Regarding the AMI shared task for the automatic identification of misogynous content in the Italian language. We participate in subtask A about Misogyny & Aggressive Behaviour Identification. Our system is similar to the one defined for HaSpeeDe and is based on the pre-trained multi-language model XLMRoBERTa, an Ordered Neurons LSTM (ON-LSTM), a Capsule Network, and a final classifier.","PeriodicalId":184564,"journal":{"name":"EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4000/BOOKS.AACCADEMIA.6912","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
English. This paper describes the system that team YNU OXZ submitted for EVALITA 2020. We participate in the shared task on Automatic Misogyny Identification (AMI) and Hate Speech Detection (HaSpeeDe 2) at the 7th evaluation campaign EVALITA 2020. For HaSpeeDe 2, we participate in Task A Hate Speech Detection and submitted two-run results for the news headline test and tweets headline test, respectively. Our submitted run is based on the pre-trained multilanguage model XLM-RoBERTa, and input into Convolution Neural Network and K-max Pooling (CNN + K-max Pooling). Then, an Ordered Neurons LSTM (ONLSTM) is added to the previous representation and submitted to a linear decision function. Regarding the AMI shared task for the automatic identification of misogynous content in the Italian language. We participate in subtask A about Misogyny & Aggressive Behaviour Identification. Our system is similar to the one defined for HaSpeeDe and is based on the pre-trained multi-language model XLMRoBERTa, an Ordered Neurons LSTM (ON-LSTM), a Capsule Network, and a final classifier.