Vit-base-patch16-224-in21k-wwwwii Open-source Image Classification Model - Free Support for Accurate Image Classification

Vit Base Patch16 224 In21k Wwwwii

Developed by Zynovia

This model is a fine-tuned version of Google's ViT model on an unknown dataset, primarily used for image classification tasks.

Image Classification

Transformers

Open Source License:Apache-2.0 #Vision Transformer Fine-tuning #Medium-scale Image Classification #Transfer Learning Optimization

Downloads 22

Release Time : 9/3/2022

Model Overview

This is an image classification model based on the Vision Transformer (ViT) architecture, fine-tuned on the google/vit-base-patch16-224-in21k foundation.

Model Features

Based on ViT Architecture

Utilizes the Vision Transformer architecture, suitable for processing image data

Fine-tuned Version

Fine-tuned on Google's pre-trained model

Medium Scale

Based on ViT-base architecture with moderate parameter size

Model Capabilities

Image Classification

Feature Extraction

Use Cases

Computer Vision

General Image Classification

Can be used to classify common objects and scenes

Validation accuracy 58.45%, Top-3 accuracy 78.45%

Train Loss	Train Accuracy	Train Top - 3 - accuracy	Validation Loss	Validation Accuracy	Validation Top - 3 - accuracy	Epoch
3.4972	0.1475	0.3067	3.0825	0.3240	0.5178	0
2.7352	0.4129	0.6613	2.4838	0.4543	0.6930	1
2.0429	0.6153	0.8315	1.9934	0.5690	0.7550	2
1.4246	0.7672	0.9166	1.6714	0.5876	0.8016	3
0.8976	0.8813	0.9721	1.6144	0.5845	0.7845	4

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Vit Base Patch16 224 In21k Wwwwii

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 Zynovia/vit-base-patch16-224-in21k-wwwwii

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

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