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Youtube Xlm Roberta Base Sentiment Multilingual

Developed by AmaanP314
Fine-tuned YouTube comment sentiment analysis model based on cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual, with an accuracy of 80.17%
Downloads 91
Release Time : 2/23/2025

Model Overview

A fine-tuned model specifically designed for YouTube comment sentiment analysis, capable of identifying positive, neutral, and negative sentiments, suitable for video recommendation systems and content analysis scenarios

Model Features

Domain Adaptation Optimization
Specifically optimized for the slang and structural characteristics of YouTube comments
Multilingual Support
Based on XLM-RoBERTa architecture, supports multilingual sentiment analysis
High Accuracy
Achieves 80.17% accuracy on YouTube comment test sets

Model Capabilities

Text Sentiment Classification
Multilingual Text Processing
Short Text Analysis

Use Cases

Content Recommendation
Video Recommendation System
Optimize video recommendation algorithms based on comment sentiment
Enhance user viewing experience
Content Analysis
Audience Feedback Dashboard
Automatically analyze sentiment tendencies in video comments
Help creators understand audience reactions
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