Open-source model vit-base-patch16-224-in21k-finetuned-cifar10 - Free deployment for image classification

Vit Base Patch16 224 In21k Finetuned Cifar10

Developed by aaraki

A pre-trained model based on Google's Vision Transformer (ViT) architecture, fine-tuned on the CIFAR-10 dataset for image classification tasks.

Image Classification

Transformers

Open Source License:Apache-2.0 #High-precision image classification #ViT architecture #CIFAR10 fine-tuning

Downloads 16.69k

Release Time : 3/30/2022

Model Overview

This model is a fine-tuned version of Google's ViT-base-patch16-224-in21k pre-trained model on the CIFAR-10 dataset, specifically designed for 10-class image classification tasks.

Model Features

High accuracy

Achieved 97.88% accuracy on the CIFAR-10 test set

Transformer-based architecture

Utilizes the Vision Transformer architecture with self-attention mechanisms for processing image data

Transfer learning

Fine-tuned from an ImageNet-21k pre-trained model to leverage pre-existing knowledge

Model Capabilities

Image classification

10-class object recognition

Use Cases

Computer vision

CIFAR-10 image classification

Classifies 10 common object categories in the CIFAR-10 dataset

97.88% accuracy

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4291	1.0	390	0.2564	0.9788

Property	Details
Model Type	vit-base-patch16-224-in21k-finetuned-cifar10
Training Data	cifar10
Metrics	accuracy

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Vit Base Patch16 224 In21k Finetuned Cifar10

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