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Sentiment and Emotion Analysis using Roberta Model

The main objective of this project is to analyze the sentiment and emotion of users based on the text they provide. This project utilizes a pre-trained model called Roberta, which has been trained on a vast collection of Twitter responses from users.

Project Overview

I have built an application using Streamlit, a Python library for creating interactive web applications. The application allows users to input text and obtain sentiment analysis results in real-time.

Model Description

The Roberta model is a state-of-the-art language model that excels in understanding and analyzing textual data. It has been fine-tuned on Twitter data, making it particularly effective in capturing the nuances and sentiment expressed in short user responses.

Features

  • Sentiment Analysis: The application provides sentiment analysis, classifying text into positive, negative, or neutral sentiment categories.

Acknowledgments

This project utilizes the Roberta pre-trained model, which is made possible by the contributions of the Hugging Face. I express my gratitude to the creators and contributors of the Roberta model.

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