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Beit Base Patch16 224 Pt22k Ft22k Finetuned FER2013 9e 05
A vision Transformer model based on the BEiT architecture, fine-tuned on the FER2013 dataset for facial expression recognition tasks
Downloads 19
Release Time : 1/8/2023
Model Overview
This model is a vision Transformer based on Microsoft's BEiT architecture, specifically fine-tuned for facial expression recognition tasks, achieving 68.4% accuracy on the FER2013 dataset
Model Features
Based on BEiT Architecture
Utilizes the BEiT (Bidirectional Encoder representation for Image Transformers) architecture, combining the advantages of vision Transformers
Facial Expression Recognition
Specifically optimized for facial expression recognition tasks, capable of identifying multiple facial expressions
Efficient Fine-tuning
Fine-tuned with a learning rate of 9e-05 on the pre-trained model, balancing training efficiency and model performance
Model Capabilities
Facial Expression Classification
Image Feature Extraction
Emotion Recognition
Use Cases
Affective Computing
Real-time Expression Analysis
Used for real-time expression recognition in video conferences or social media
Can identify multiple basic expressions with 68.4% accuracy
Human-Computer Interaction
Provides user emotion feedback for smart devices
Psychological Research
Emotional Response Study
Used for automatic facial expression analysis in psychological experiments
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