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Sentiment Analysis with Fine-Tuned BERT

This project demonstrates multi-class sentiment analysis using a fine-tuned BERT model trained on Twitter sentiment data.


Comments / Suggestions are appreciated!

Model Output Examples

Class Labels

{0: 'sadness', 2: 'love', 4: 'fear', 3: 'anger', 5: 'surprise', 1: 'joy'}

Screenshots

Below are some sample screenshots showing the model in action:

Example 1
Example 2

This model was fine-tuned using HuggingFace's transformers library and a BERT base uncased model. The pipeline predicts one of the six emotion categories (sadness, love, fear, anger, surprise, joy) for a given input sentence.