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language: en tags: - emotion-classification datasets: - go-emotions - bdotloh/empathetic-dialogues-contexts # Model Description Yet another Transformer model fine-tuned for approximating another non-linear mapping between X and Y? That's right! This is your good ol' emotion classifier - given an input text, the model outputs a probability distribution over a set of pre-selected emotion words. In this case, it is 32, which is the number of emotion classes in the [Empathetic Dialogues](https://huggingface.co/datasets/bdotloh/empathetic-dialogues-contexts) dataset. This model is built "on top of" a [distilbert-base-uncased model fine-tuned on the go-emotions dataset](https://huggingface.co/bhadresh-savani/bert-base-go-emotion). Y'all should really check out that model, it even contains a jupyter notebook file that illustrates how the model was trained (bhadresh-savani if you see this, thank you!). ## Training data ## Training procedure ### Preprocessing ## Evaluation results ### Limitations and bias Well where should we begin... EmpatheticDialogues: 1) Unable to ascertain the degree of cultural specificity for the context that a respondent described when given an emotion label (i.e., p(description | emotion, *culture*)) 2) ...