|
--- |
|
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](https://www.kaggle.com/code/wesleyacheng/twitter-emotion-multilabel-classification-w-bert/notebook#Create-Custom-Dataset). |
|
|
|
Hello, I'm Wesley, nice to meet you! 👋 |
|
|
|
Since adding **Joy** and **Sadnesss** with **Anger** in my [Twitter Emotion MultiClass Classifier Notebook](https://www.kaggle.com/code/wesleyacheng/twitter-emotion-classification-with-bert), 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](https://huggingface.co/distilbert-base-uncased) with the [SemEval Twitter Dataset](https://huggingface.co/datasets/sem_eval_2018_task_1) in PyTorch and HuggingFace. |
