metadata
license: apache-2.0
datasets:
- sem_eval_2018_task_1
language:
- en
metrics:
- accuracy
- f1
pipeline_tag: text-classification
widget:
- text: We should lock the door and scream that curse word we know.
example_title: Anger Tweet
- text: >-
You know what else barely touches the ground? Stray dogs, toenail
clippings, road kill, hippies, dung beetles...
example_title: Disgust Tweet
- text: >-
I sure am glad you told me earthquakes are a myth, Joy; otherwise, I’d be
terrified right now.
example_title: Fear Tweet
- text: >-
All right, everyone, fresh start. We are gonna have a good day, which will
turn into a good week, which will turn into a good year, which turns into
a good life!
example_title: Joy Tweet
- text: Crying helps me slow down and obsess over the weight of life's problems.
example_title: Sadness Tweet
First posted on my Kaggle.
Hello, I'm Wesley, nice to meet you! 👋
Since adding Joy and Sadnesss with Anger in my Twitter Emotion MultiClass Classifier Notebook, I wanted to complete the Inside Out group with Fear and Disgust!
Here I made a Twitter Emotion MultiLabel Classifier by doing transfer learning on BERT with the SemEval Twitter Dataset in PyTorch and HuggingFace.