---
license: cc
tags:
  - onnx
  - image-classification
  - cifar10
  - dropout
  - aidge
pipeline_tag: image-classification
datasets:
  - cifar10
metrics:
  - type: accuracy
    value: 69.96%
model-index:
  - name: Custom ResNet-18 with Integrated Dropout
    results:
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: CIFAR-10
          type: cifar10
        metrics:
          - type: accuracy
            value: 69.96%
---

# MarwaNet (ONNX)

This is a **custom convolutional neural network (CNN)** trained on the **CIFAR-10** dataset, developed to test the integration of a **custom Dropout operator** for the **Aidge** platform.

## Details

- **Architecture**: Custom Convolutional Neural Network (CNN) with a Dropout layer
- **Trained on**: CIFAR-10 (60,000 32x32 color images, 10 classes)
- **Data Normalization**: `mean = [0.4914, 0.4822, 0.4465]` ; `std = [0.2023, 0.1994, 0.2010]`
- **Dropout Probability**: 0.3
- **ONNX opset version**: 15
- **Conversion tool**: PyTorch → ONNX