CIFAR10_outputs Open-Source Vision Model - Fine-tuned on CIFAR-10, Free Deployment for Precise Image Recognition

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Cifar10 Outputs

Developed by jimypbr

A vision Transformer model fine-tuned on the CIFAR-10 dataset based on google/vit-base-patch16-224-in21k

Image Classification

Transformers

Open Source License:Apache-2.0 #High-precision image classification #ViT fine-tuned model #Specialized for CIFAR10

Downloads 15

Release Time : 6/29/2022

Model Overview

This model is an image classification model based on the Vision Transformer architecture, specifically optimized for the CIFAR-10 dataset, capable of accurately recognizing 10 common object categories.

Model Features

High accuracy

Achieves 99.14% accuracy on the CIFAR-10 test set

Based on ViT architecture

Utilizes the Vision Transformer architecture with powerful image feature extraction capabilities

Lightweight fine-tuning

Fine-tuned based on a pre-trained model, ensuring high training efficiency

Model Capabilities

Image classification

Object recognition

Use Cases

Computer vision

CIFAR-10 image classification

Classifies 10 object categories in the CIFAR-10 dataset

99.14% test accuracy

Property	Details
Model Type	Fine - tuned model based on google/vit - base - patch16 - 224 - in21k for image classification
Training Data	cifar10
Metrics	Accuracy
Results	On the cifar10 dataset, accuracy is 0.991421568627451

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Cifar10 Outputs

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