Vit-base-brain-mri Open-source Image Classification Model - Accurately Recognize Brain MRI Image Categories

Vit Base Brain Mri

Developed by andrei-teodor

An image classification model fine-tuned on the BrainMRI dataset based on Google's ViT base model

Downloads 42

Release Time : 8/25/2024

Model Overview

This model is a variant based on the Vision Transformer (ViT) architecture, specifically fine-tuned for brain MRI image classification tasks.

Based on ViT Architecture

Utilizes the Vision Transformer architecture, leveraging self-attention mechanisms to process image data

Specialized for Brain MRI

Specifically fine-tuned for brain MRI image classification tasks

Moderate Accuracy

Achieves an accuracy of 0.599 on the evaluation set

Brain MRI Image Classification

Medical Image Analysis

Medical Imaging

Brain Disease Classification

Classifies brain MRI images to identify potential disease types

Achieves an accuracy of 0.599 on the test set

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	72	0.9986	0.6098
1.098	2.0	144	0.8445	0.7003
0.7895	3.0	216	0.7318	0.7526
0.7895	4.0	288	0.6842	0.7474
0.6629	5.0	360	0.6328	0.7857
0.5966	6.0	432	0.5957	0.8101
0.5546	7.0	504	0.5646	0.8118
0.5546	8.0	576	0.5647	0.8049
0.5113	9.0	648	0.5340	0.8275
0.4882	10.0	720	0.5190	0.8328
0.4882	11.0	792	0.5197	0.8328
0.4789	12.0	864	0.5002	0.8258
0.4582	13.0	936	0.4957	0.8310
0.4426	14.0	1008	0.4821	0.8310
0.4426	15.0	1080	0.4706	0.8467
0.4328	16.0	1152	0.4821	0.8153
0.432	17.0	1224	0.4992	0.8275
0.432	18.0	1296	0.4799	0.8345
0.4196	19.0	1368	0.4838	0.8310
0.4287	20.0	1440	0.4598	0.8659

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