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Beit Finetuned
This model is a fine-tuned BEiT base version on the CIFAR-10 dataset, focusing on image classification tasks, achieving 99.18% accuracy on the evaluation set.
Downloads 24
Release Time : 5/18/2022
Model Overview
A fine-tuned model based on the BEiT architecture for high-precision image classification tasks, specifically optimized for performance on the CIFAR-10 dataset.
Model Features
High Accuracy
Achieves 99.18% classification accuracy on the CIFAR-10 test set
Efficient Fine-tuning
Requires only 3 training epochs to achieve excellent performance
Transfer Learning Capability
Based on the BEiT pre-trained model with excellent feature extraction capabilities
Model Capabilities
Image classification
Transfer learning
Computer vision tasks
Use Cases
Image Recognition
CIFAR-10 Image Classification
Accurate classification of 10 categories of objects in the CIFAR-10 dataset
99.18% accuracy
Education & Research
Computer Vision Teaching
Used as a benchmark model for image classification tasks in teaching demonstrations
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