Robert Walther

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2023

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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)

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.
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