Towards Neural Speaker Modeling in Multi-Party Conversation:The Task, Dataset, and Models
Table 2: Model performance (in percentage).
['[BOLD] Model Random guess', '[BOLD] Model Random guess', '[BOLD] Macro  [ITALIC] F1 19.93', '[BOLD] Weighted  [ITALIC] F1 34.19', '[BOLD] Micro  [ITALIC] F1 27.53', '[BOLD] Acc. 27.53', '[BOLD] MRR.']
Performance. Majority-class guess results in high accuracy, showing that the dataset is screwed. Hence, we choose macro F1 as our major metric, which addresses minority classes more than other metrics. We nevertheless present other metrics including accuracy, mean reciprocal ranking (MRR), and micro/weighted F1 as additional evidence.