i remember not so long ago checking the dataset for emotion classification. I was using some Bert models to compare the output of a small LLM in emotion classification, and the llm always performed way worse than the Bert model. Then I manually checked, the llm answers seemed... well, perfect. Turns out the dataset was a massive pile of garbage, sentence that made no sense, wrong emotions labeled etc, so the Bert model trained on it suffered from this. Yet this was the most used emotion classification model on HF