readme: ---
  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) ...
  