readme: ---
  language: nl
  tags:
  - token-classification
  - sequence-tagger-model
  ---
  
  # Goal
  This model can be used to add emoji to an input text.
  
  To accomplish this, we framed the problem as a token-classification problem, predicting the emoji that should follow a certain word/token as an entity.
  
  The accompanying demo, which includes all the pre- and postprocessing needed can be found [here](https://huggingface.co/spaces/ml6team/emoji_predictor).
  
  For the moment, this only works for Dutch texts.
  
  
  
  # Dataset
  For this model, we scraped about 1000 unique tweets per emoji we support:
  ['😨', '😥', '😍', '😠', '🤯', '😄', '🍾', '🚗', '☕', '💰']
  
  Which could look like this:
  ```
  Wow 😍😍, what a cool car 🚗🚗!
  Omg, I hate mondays 😠... I need a drink 🍾
  ```
  
  After some processing, we can reposition this in a more known NER format:
  
  
  | Word | Label |
  |-------|-----|
  | Wow   | B-😍|
  | ,     | O   |
  | what  | O   |
  | a     | O   |
  | cool  | O   |
  | car   | O   |
  | !     | B-🚗|
  
  Which can then be leveraged for training a token classification model.
  
  Unfortunately, Terms of Service prohibit us from sharing the original dataset.
  
  
  
  # Training
  
  The model was trained for 4 epochs.
  