File size: 1,139 Bytes
3bfc4cb
 
1b8cace
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4bd4dbc
 
8fb7d50
f2b04c3
4bd4dbc
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
---
license: apache-2.0
datasets:
- tweet_eval
language:
- en
metrics:
- accuracy
- f1
pipeline_tag: text-classification
widget:
  - text: Yay!
    example_title: Joy Example
  - text: There is no meaning in life.
    example_title: Sadness Example
  - text: I hate you!
    example_title: Anger Example
---

First posted in my [Kaggle](https://www.kaggle.com/code/wesleyacheng/twitter-emotion-classification-with-bert).

Hello, I'm **Wesley**, nice to meet you! 👋

While I was making my **[Angry Birds Classifier](https://www.kaggle.com/code/wesleyacheng/angry-birds-classifier)** to classify if tweets are angry or not, I thought why don't we add **2** more emotions! **Joy and Sadness** into the mix!

Here I created a **Multiclass Text Classifier** that classifies tweets as either having **JOY, SADNESS, or ANGER**.

I used the [Twitter Emotion Dataset](https://huggingface.co/datasets/tweet_eval/viewer/emotion/train) and [BERT](https://huggingface.co/distilbert-base-uncased) to do [Transfer Learning](https://en.wikipedia.org/wiki/Transfer_learning) with [PyTorch](https://pytorch.org) and [HuggingFace](https://huggingface.co).