UL_base_classification Open-source Image Classification Model - Free to Use, with an Accuracy of 89.21% on the Validation Set

UL Base Classification

Developed by sharmajai901

This model is a fine-tuned image classification model based on Google's ViT-base-patch16-224 on an image folder dataset, achieving 89.21% accuracy on the validation set.

Image Classification

Transformers

Open Source License:Apache-2.0 #High-precision image classification #ViT fine-tuned model #Transfer learning

Downloads 2,432

Release Time : 6/11/2024

Model Overview

An image classification model based on the Vision Transformer architecture, suitable for general image classification tasks.

Model Features

High accuracy

Achieves 89.21% classification accuracy on the validation set.

ViT-based architecture

Utilizes the Vision Transformer base architecture with powerful image feature extraction capabilities.

Lightweight fine-tuning

Lightweight fine-tuning on the base model to adapt to specific classification tasks.

Model Capabilities

Image classification

Visual feature extraction

Use Cases

General image classification

Object recognition

Identify the main object categories in images.

89.21% accuracy on the validation set.

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8296	0.9756	20	0.5683	0.8230
0.4462	2.0	41	0.3949	0.8603
0.3588	2.9756	61	0.3633	0.8575
0.3196	4.0	82	0.3247	0.8852
0.2921	4.9756	102	0.3374	0.8728
0.2688	6.0	123	0.3125	0.8921
0.2366	6.8293	140	0.3137	0.8866

Property	Details
Model Type	Fine - tuned version of google/vit - base - patch16 - 224
Training Data	imagefolder
Metrics	accuracy

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UL Base Classification

Model Overview

Model Features

Model Capabilities

Use Cases

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