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Beit Base Patch16 224 Pt22k Ft22k Finetuned FER2013 6e 05

Developed by lixiqi
Facial expression recognition model fine-tuned on the FER2013 dataset based on Microsoft's BEiT model
Downloads 18
Release Time : 1/9/2023

Model Overview

This model is a facial expression classifier based on the BEiT vision Transformer architecture, specifically fine-tuned for facial expression recognition tasks, achieving an accuracy of 68.63% on the FER2013 dataset.

Model Features

Based on BEiT Architecture
Utilizes advanced vision Transformer architecture with powerful image feature extraction capabilities
Optimized for Facial Expression Recognition
Specifically fine-tuned on the FER2013 facial expression dataset, suitable for sentiment analysis applications
Medium-sized Model
Based on the BEiT-base architecture, achieving a good balance between computational efficiency and performance

Model Capabilities

Facial Expression Classification
Emotional State Recognition
Static Image Analysis

Use Cases

Affective Computing
Facial Expression Analysis System
Used to analyze user facial expressions to infer emotional states
Achieved 68.63% accuracy on the FER2013 test set
Human-Computer Interaction
Intelligent Customer Service Emotion Detection
Real-time detection of user facial expression changes to adjust service strategies
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