Please read the topic category description to understand what this is all about


Description
Emoticons are often used as a proxy for emotional content in social media posts or instant messaging chats. As a result, emojis are often used as a label to train text classifiers. The goal of this project is to create a Transformer-based implementation of DeepEmoji 6, a research project from MIT that studied this task with LSTMs.

Model(s)
Any BERT-like model would be a good candidate for fine-tuning on an emoji dataset and you can get inspiration from models like these:

cardiffnlp/twitter-roberta-base-emoji


Datasets

tweet_eval 7


Challenges
To get better performance, you may want to perform domain adaptation by fine-tuning the language model on in-domain data. We recommend trying this approach only after building a baseline classifier.

Desired project outcomes

Create a Streamlit or Gradio app on  Spaces that can predict the top 5 emojis associated with a piece of text
Don’t forget to push all your models and datasets to the Hub so others can build on them!


Additional resources


https://huggingface.co/spaces/ml6team/emoji_predictor 6 (a Space for inspiration)


Discord channel
To chat and organise with other people interested in this project, head over to our Discord and:

Follow the instructions on the #join-course channel
Join the learning-from-emojis channel

Just make sure you comment here to indicate that you’ll be contributing to this project