Discover the latest strategies and comparative insights into optimizing meme sentiment analysis through multimodal classifiers.
Authors: Muzhaffar Hazman, University of Galway, Ireland; Susan McKeever, Technological University Dublin, Ireland; Josephine Griffith, University of Galway, Ireland. Table of Links Abstract and Introduction Related Works Methodology Results Limitations and Future Works Conclusion, Acknowledgments, and References A Hyperparameters and Settings B Metric: Weighted F1-Score C Architectural Details D Performance Benchmarking E Contingency Table: Baseline vs.
To prevent the models from converging into a model that predicts only the most prevalent class in the training set, we balance the classes in these fractional datasets by applying weights inverse of the class distribution during sampling without replacement. For unimodal intermediate training, we used two unimodal datasets: Crowdflower for unimodal images, and DynaSent for unimodal text.
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