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Beit Base Patch16 224 Pt22k Ft22k Finetuned FER2013CKPlus 7e 05 Finetuned SFEW 7e 05

Developed by lixiqi
A vision Transformer model based on the BEiT architecture, fine-tuned on FER2013CKPlus and SFEW datasets for facial expression recognition tasks.
Downloads 17
Release Time : 1/29/2023

Model Overview

This model is an image classification model based on the BEiT architecture, specifically fine-tuned for facial expression recognition tasks. Trained on FER2013CKPlus and SFEW datasets, it can recognize various facial expressions.

Model Features

Based on BEiT architecture
Utilizes the BEiT (BERT pre-trained image Transformer) architecture, combining the advantages of vision Transformers.
Facial expression recognition
Specifically optimized and fine-tuned for facial expression recognition tasks.
Two-stage fine-tuning
First fine-tuned on the FER2013CKPlus dataset, then further fine-tuned on the SFEW dataset.

Model Capabilities

Image classification
Facial expression recognition
Emotion analysis

Use Cases

Affective computing
Facial expression analysis
Analyze facial expressions in images to identify basic emotional states.
Achieved 49.6% accuracy on the evaluation set.
Human-computer interaction
Emotion-aware systems
Used to build interactive systems that can understand user emotional states.
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