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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 dataset.

This model is built "on top of" a distilbert-base-uncased model fine-tuned on the go-emotions dataset. 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


Evaluation results

Limitations and bias

Well where should we begin...


  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. ...
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Text Classification
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Dataset used to train bdotloh/just-another-emotion-classifier