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Vit Base Patch16 224 Finetuned Og Dataset 10e
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Vit Base Patch16 224 Finetuned Og Dataset 10e

Developed by Gokulapriyan
A vision Transformer model fine-tuned on a custom image dataset based on Google's ViT model, achieving an evaluation accuracy of 97.7%
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision image classification#ViT fine-tuned model#Few-shot learning
Downloads 17
Release Time : 2/18/2023

Model Overview

This model is a fine-tuned version of Google's ViT-base-patch16-224 architecture for image classification tasks, suitable for general image recognition tasks

Model Features

High accuracy
Achieves 97.7% classification accuracy on the evaluation set
Efficient inference
Can process 46.82 samples per second, suitable for real-time applications
Transformer-based architecture
Utilizes advanced Vision Transformer architecture with powerful feature extraction capabilities

Model Capabilities

Image classification
Feature extraction
Transfer learning

Use Cases

Computer vision
General image classification
Classify and recognize various types of images
Evaluation accuracy 97.7%
Transfer learning base model
Can be used as a pre-trained model for other vision tasks
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