deit-base-mri Open-source Image Classification Model - Fine-tuned on mriDataSet, with a classification accuracy of 99.01%

Deit Base Mri

Developed by raedinkhaled

An image classification model fine-tuned on the mriDataSet dataset based on facebook/deit-base-distilled-patch16-224, achieving an accuracy of 99.01%

Image Classification

Transformers

Open Source License:Apache-2.0 #Medical Image Classification #High-precision ViT #MRI Analysis

Downloads 15

Release Time : 7/1/2022

Model Overview

This model is an image classification model based on the Vision Transformer architecture, specifically fine-tuned for MRI image classification tasks

Model Features

High Accuracy

Achieves 99.01% accuracy on MRI image classification tasks

Based on Vision Transformer

Utilizes advanced Transformer architecture for image processing

Efficient Fine-tuning

Requires only 2 training epochs to achieve high performance

Model Capabilities

Medical Image Classification

MRI Image Analysis

Image Feature Extraction

Use Cases

Medical Imaging Analysis

MRI Image Classification

Classifying and diagnosing MRI scan images

99.01% accuracy

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0107	0.8	500	0.0782	0.9887
0.0065	1.6	1000	0.0657	0.9901

Property	Details
Model Type	Fine - tuned version of facebook/deit-base-distilled-patch16-224 for image classification
Training Data	mriDataSet (type: imagefolder)
Metrics	Accuracy (value: 0.9900709219858156 on mriDataSet)

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Deit Base Mri

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