Mostefa-Terbeche/diabetic-retinopathy-aptos-efficientnet

Diabetic Retinopathy Classification Model

Model Description

This model is trained for diabetic retinopathy classification using the efficientnet architecture on the aptos dataset.

Model Details

• Architecture: efficientnet
• Dataset: aptos
• Training Date: b3_20250720-012032
• Task: 5-class diabetic retinopathy grading (0-4)

Performance

• Test Accuracy: 0.7704918032786885
• Test Quadratic Kappa: 0.8974660347551343
• Validation Kappa: 0.8974660347551343

Usage

import torch
from huggingface_hub import hf_hub_download

# Download model
model_path = hf_hub_download(
    repo_id="your-username/diabetic-retinopathy-aptos-efficientnet",
    filename="model_best.pt"
)

# Load model
model = torch.load(model_path, map_location='cpu')

Classes

• 0: No DR (No diabetic retinopathy)
• 1: Mild DR (Mild non-proliferative diabetic retinopathy)
• 2: Moderate DR (Moderate non-proliferative diabetic retinopathy)
• 3: Severe DR (Severe non-proliferative diabetic retinopathy)
• 4: Proliferative DR (Proliferative diabetic retinopathy)

Citation

If you use this model, please cite your research paper/thesis.