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Distilbert Base Uncased Finetuned Emotion
A lightweight sentiment analysis model based on DistilBERT, fine-tuned on an unknown dataset with an accuracy of 93.45%
Downloads 18
Release Time : 3/2/2022
Model Overview
This model is a fine-tuned version of DistilBERT, specifically designed for sentiment analysis tasks. It retains the main performance of BERT through knowledge distillation while reducing model size and computational requirements.
Model Features
Efficient and Lightweight
Significantly reduces model size while maintaining high accuracy through knowledge distillation technology
Excellent Performance
Achieves 93.45% accuracy and an F1 score of 0.9348 on the evaluation set
Fast Inference
Inference speed is approximately 60% faster compared to the original BERT model
Model Capabilities
Text Classification
Sentiment Analysis
Natural Language Understanding
Use Cases
Social Media Analysis
User Comment Sentiment Analysis
Analyze the sentiment tendencies of social media comments
Can accurately identify over 93% of sentiment categories
Customer Service
Customer Feedback Classification
Automatically classify the sentiment tendencies of customer feedback
Helps quickly identify dissatisfied customers
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