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Beit Base Patch16 224 Pt22k Ft22k Finetuned FER2013

Developed by lixiqi
An image classification model based on the BEiT architecture, fine-tuned on the FER2013 dataset for facial expression recognition
Downloads 20
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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