vit-base-patch16-224-in21k-bantai_vitv1 Open-source Image Classification Model

Vit Base Patch16 224 In21k Bantai Vitv1

Developed by AykeeSalazar

This model is an image classification model based on the Google Vision Transformer (ViT) architecture, achieving an accuracy of 86.36% after fine-tuning on the image_folder dataset.

Image Classification

Transformers

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

Downloads 17

Release Time : 4/2/2022

Model Overview

This is an image classification model based on the ViT architecture, suitable for general image recognition tasks. The model performs excellently on standard image classification tasks, achieving an accuracy of 86.36%.

Model Features

High Accuracy

Achieves a classification accuracy of 86.36% on the evaluation set.

ViT-based Architecture

Utilizes the Vision Transformer architecture, leveraging self-attention mechanisms for image processing.

Transfer Learning

Fine-tuned based on the pre-trained google/vit-base-patch16-224-in21k model.

Model Capabilities

Image classification

Visual feature extraction

Use Cases

Computer Vision

General Image Classification

Classifies various types of images.

Achieves 86.36% accuracy on the test set.

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5997	1.0	115	0.5401	0.7886
0.4696	2.0	230	0.4410	0.8482
0.4019	3.0	345	0.3961	0.8636

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Vit Base Patch16 224 In21k Bantai Vitv1

Model Overview

Model Features

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