Finetuning Sentiment Model 3000 Samples
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Finetuning Sentiment Model 3000 Samples
Developed by mayank15122000
A sentiment analysis model fine-tuned based on distilbert-base-uncased, achieving 87.67% accuracy on the evaluation set
Downloads 111
Release Time : 4/6/2025
Model Overview
This model is a fine-tuned DistilBERT variant for sentiment analysis tasks, suitable for text sentiment classification
Model Features
Efficient and Lightweight
Based on DistilBERT architecture, reducing model size while maintaining performance
High Accuracy
Achieves 87.67% accuracy and 88.03% F1 score on the evaluation set
Fast Training
Only requires 2 training epochs to achieve good performance
Model Capabilities
Text sentiment classification
English text analysis
Use Cases
Social Media Analysis
Comment Sentiment Analysis
Analyze the sentiment tendency of user comments
87.67% accuracy
Customer Feedback Analysis
Customer Satisfaction Evaluation
Automatically classify the sentiment tendency of customer feedback
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