Diabetic Retinopathy Classification Model

Model Description

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

Model Details

  • Architecture: vit
  • Dataset: aptos
  • Training Date: b_16_20250716-210242
  • Task: 5-class diabetic retinopathy grading (0-4)

Performance

  • Test Accuracy: 0.76775956284153
  • Test Quadratic Kappa: 0.8858538019772866
  • Validation Kappa: 0.8858538019772866

Usage

import torch
from huggingface_hub import hf_hub_download

# Download model
model_path = hf_hub_download(
    repo_id="your-username/diabetic-retinopathy-aptos-vit",
    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.

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Evaluation results