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SO at SemEval-2020 task 7: DeepPavlov logistic regression with BERT embeddings vs SVR at funniness evaluationстатья
- Автор: Soloveva Anita
- Сборник: Proceedings of the 14th International Workshop on Semantic Evaluation
- Год издания: 2020
- Место издания: ACL
- Аннотация: This paper describes my efforts in evaluating how editing news headlines can make them funnier within the frames of SemEval 2020 Task 7. I participated in both of the sub-tasks: Sub-Task 1 “Regression” and Sub-task 2 “Predict the funnier of the two edited versions of an original headline”. I experimented with a number of different models, but ended up using DeepPavlov logistic regression (LR) with BERT English cased embeddings for the first sub-task and support vector regression model (SVR) for the second. RMSE score obtained for the first task was 0.65099 and accuracy for the second – 0.32915.
- Добавил в систему: Соловьёва Анита Вячеславовна