Beit Base Patch16 224 Pt22k Ft22k Finetuned FER2013
An image classification model based on the BEiT architecture, fine-tuned on the FER2013 dataset for facial expression recognition
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Release Time : 1/7/2023
Model Overview
This model is a vision Transformer based on the BEiT architecture, specifically fine-tuned for facial expression recognition tasks, capable of identifying 7 basic facial expressions
Model Features
Efficient Vision Transformer
Utilizes the BEiT architecture combined with image tokenization technology for efficient image feature extraction
Facial Expression Recognition
Specially fine-tuned on the FER2013 dataset, optimizing performance for facial expression classification
Transfer Learning Capability
Based on large-scale pre-trained models, demonstrating excellent transfer learning capabilities on small-scale datasets
Model Capabilities
Image Classification
Facial Expression Recognition
Sentiment Analysis
Use Cases
Human-Computer Interaction
Emotion Recognition System
Used to detect user facial expressions for analyzing emotional states
Achieved 68.79% accuracy on the FER2013 test set
Psychological Research
Emotional Response Analysis
Used for recording and analyzing subjects' emotional responses in psychological experiments
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