Tom Rietzke
2023
Mr-Fosdick at SemEval-2023 Task 5: Comparing Dataset Expansion Techniques for Non-Transformer and Transformer Models: Improving Model Performance through Data Augmentation
Christian Falkenberg | Erik Schönwälder | Tom Rietzke | Chris-Andris Görner | Robert Walther | Julius Gonsior | Anja Reusch
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Christian Falkenberg | Erik Schönwälder | Tom Rietzke | Chris-Andris Görner | Robert Walther | Julius Gonsior | Anja Reusch
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
In supervised learning, a significant amount of data is essential. To achieve this, we generated and evaluated datasets based on a provided dataset using transformer and non-transformer models. By utilizing these generated datasets during the training of new models, we attain a higher balanced accuracy during validation compared to using only the original dataset.