Hq Fer2013notestaugm
H
Hq Fer2013notestaugm
Developed by Piro17
A fine-tuned image classification model based on ViT architecture, excelling on the FER2013 dataset
Downloads 17
Release Time : 2/19/2023
Model Overview
This model is a fine-tuned version of the google/vit-base-patch16-224-in21k pre-trained model for image classification tasks, primarily used for facial expression recognition
Model Features
High Accuracy
Achieves 69.98% accuracy on the FER2013 dataset
Based on ViT Architecture
Utilizes Vision Transformer architecture with powerful image feature extraction capabilities
Fine-tuned
Performance gradually improved through 10 training epochs
Model Capabilities
Image Classification
Facial Expression Recognition
Emotion Analysis
Use Cases
Affective Computing
Facial Expression Recognition
Recognizes facial expressions of individuals in images
Achieves 69.98% accuracy on the FER2013 dataset
Human-Computer Interaction
Emotional Feedback System
Used to detect user emotional states
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