Sagemaker Distilbert Emotion
S
Sagemaker Distilbert Emotion
Developed by jpabbuehl
A text sentiment classification model based on DistilBERT, fine-tuned on the emotion dataset with an accuracy of 92.9%
Downloads 21
Release Time : 3/2/2022
Model Overview
This model is a fine-tuned version of DistilBERT, specifically designed for text sentiment classification tasks, capable of recognizing six basic emotions.
Model Features
High Accuracy
Achieves 92.9% classification accuracy on the emotion dataset
Lightweight
Based on the DistilBERT architecture, more lightweight and efficient than the full BERT model
Fast Inference
Optimized model suitable for production environment deployment
Model Capabilities
Text Classification
Sentiment Analysis
Use Cases
Social Media Analysis
User Comment Sentiment Analysis
Analyze user emotions in social media comments
Accurately identifies six basic emotions including anger, joy, sadness, etc.
Customer Service
Customer Feedback Classification
Automatically classify emotional tendencies in customer feedback
Helps quickly identify dissatisfied customers
Featured Recommended AI Models