Model: PavanKumarAmbadapudi/DiabeticRetinopathy_Hybrid-ViT
Author: PavanKumarAmbadapudi
Library: pytorch
Tags: pytorch, classification, diabetic-retinopathy, hybrid vit, efficientnet, deep-learning, medical-ai, region:us
Card metadata: library_name: pytorch
tags: classification, diabetic-retinopathy, hybrid vit, efficientnet, deep-learning, medical-ai
model_name: Hybrid_ViT
model_description: A Hybrid Vision Transformer (ViT) with EfficientNetB0 as the backbone, trained to classify Diabetic Retinopathy severity into 5 categories.
dataset: name: APTOS 2019 Blindness Detection
url: https://www.kaggle.com/competitions/aptos2019-blindness-detection
description: A dataset containing retinal fundus images for classifying Diabetic Retinopathy severity.
metrics: accuracy: 85.4
loss: 0.23
validation_accuracy: 84.5
validation_loss: 0.25
training: epochs: 5
batch_size: 32
optimizer: Adam
learning_rate: 0.0001
scheduler: type: StepLR
step_size: 10
gamma: 0.5
loss_function: CrossEntropyLoss
k_folds: 5
device: CUDA
model_architecture: backbone: EfficientNetB0
transformer: Vision Transformer (ViT)
num_classes: 5
input_size: 224x224
framework: PyTorch
author: Pavan Kumar Ambadapudi>
repository: https://huggingface.co/PavanKumarAmbadapudi/DiabeticRetinopathy_Hybrid-ViT
Likes: 0 | All-time downloads: 0
Created: 2025-03-26 14:16:23