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

Developed by Celal11
This is an image classification model based on the BEiT architecture, fine-tuned on the FER2013 and CK+ datasets for facial expression recognition tasks.
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision facial expression recognition#Fine-tuning transfer learning#Image classification
Downloads 19
Release Time : 1/9/2023

Model Overview

This model is a vision Transformer based on the BEiT architecture, specifically optimized for facial expression recognition tasks. After fine-tuning on the FER2013 and CK+ datasets, it achieved 100% accuracy on the evaluation set.

Model Features

High accuracy
After fine-tuning on the FER2013 and CK+ datasets, the evaluation accuracy reached 100%
Based on BEiT architecture
Uses the BEiT-base (patch16-224) architecture, combining the advantages of vision Transformers
Optimized training
Employs linear learning rate scheduling and warm-up strategies for stable and efficient training

Model Capabilities

Facial expression recognition
Image classification
Emotion analysis

Use Cases

Human-computer interaction
Emotion recognition system
Used to identify users' facial expressions to analyze their emotional states
High-accuracy emotion classification
Psychological research
Facial expression analysis
Used for automatic facial expression recognition in psychological experiments
Provides objective expression classification data
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