S

Sentimental Analysis

Developed by Dmyadav2001
A sentiment analysis system implemented using the lightweight DistilBERT model, supporting positive/negative/neutral three-class classification
Downloads 100
Release Time : 11/10/2023

Model Overview

This model is a sentiment analysis tool fine-tuned based on the DistilBERT architecture, specifically designed for text sentiment classification tasks, capable of identifying emotional tendencies in text

Model Features

Lightweight and Efficient
Adopts DistilBERT architecture, reducing size by 40% while maintaining 95% of BERT's performance
Multi-sentiment Classification
Supports positive/negative/neutral three-class classification, adapting to more complex sentiment analysis scenarios
Transfer Learning
Fine-tuned based on pre-trained models, achieving good results even on small-scale datasets

Model Capabilities

Text sentiment classification
Short text analysis
Comment emotion detection

Use Cases

Social Media Analysis
User Comment Sentiment Monitoring
Analyze the sentiment tendencies of user comments on social media platforms
Can automatically identify negative comments for early warning
Customer Service
Customer Service Dialogue Analysis
Evaluate emotional changes in customer conversations
Helps identify dissatisfied customers for priority handling
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