NIT-Agartala-NLP-Team at SemEval-2020 Task 8:Building Multimodal Classifiers to tackle Internet Humor
Table 4: Test Set Results (macro-F1 and potential ranks) on all subtasks. Official submission in bold.
['Model', 'Subtask A F1 (%)', 'Subtask A Rank', 'Subtask B F1(%)', 'Subtask B Rank', 'Subtask C F1(%)', 'Subtask C Rank']
On the test Datastet, the task organizers rank each system based on averaged Macro F1. For subtasks B ad C where there are 4 separate categories within the task an average score over the four categories was provided. Ranks were provided for only the top submission of each team. Initially, we submit three different systems for task evaluation — the Logistic Regression model, the BiLSTM + Attention model, the BERT model. However, we saw that the certain models performed better on certain subtasks.