---
license: mit
datasets:
- uoft-cs/cifar10
language:
- en
metrics:
- accuracy
base_model:
- jaeunglee/resnet18-cifar10-unlearning
tags:
- machine_unlearning
---

# Evaluation Report

## Testing Data
**Dataset**: CIFAR-10 Test Set  
**Metrics**: Forget class accuracy(loss), Retain class accuracy(loss)

---

## Training Details

### Training Procedure
- **Base Model**: ResNet18  
- **Dataset**: CIFAR-10  
- **Excluded Class**: Varies by model  
- **Loss Function**: Negative Log-Likelihood Loss  
- **Optimizer**: SGD with:
  - Learning rate: 0.01  
  - Momentum: 0.9  
  - Weight decay: 5e-4  
  - Nesterov: True   
- **Training Epochs**: 20  
- **Batch Size**: 256  
- **Hardware**: Single GPU (NVIDIA GeForce RTX 3090)

### Selective Synapse Dampening Specifics
- **Lambda**: 1.0  
- **Alpha**: 10.0    

### Algorithm
The **SSD (Selective Synapse Dampening)** algorithm was used for inexact unlearning. This method selectively reduces the impact of a specific class on the model while preserving the performance on the remaining classes. 

Each resulting model (`cifar10_resnet18_SSD_X.pth`) corresponds to a scenario where a single class (`X`) has been unlearned. SSD efficiently removes class-specific knowledge while maintaining robustness and generalizability.

For more details on the SSD algorithm, refer to the [GitHub repository](https://github.com/if-loops/selective-synaptic-dampening).

---



## Results

| Model                         | Forget Class | Forget class acc(loss) | Retain class acc(loss) |
|--------------------------------|--------------|-------------------------|-------------------------|
| cifar10_resnet18_SSD_0.pth     | Airplane     | 0.0 (8.102)             | 83.38 (0.527)          |
| cifar10_resnet18_SSD_1.pth     | Automobile   | 0.0 (6.550)             | 94.62 (0.189)          |
| cifar10_resnet18_SSD_2.pth     | Bird         | 0.0 (9.854)             | 90.06 (0.328)          |
| cifar10_resnet18_SSD_3.pth     | Cat          | 0.0 (8.428)             | 90.00 (0.317)          |
| cifar10_resnet18_SSD_4.pth     | Deer         | 0.0 (5.885)             | 95.26 (0.161)          |
| cifar10_resnet18_SSD_5.pth     | Dog          | 0.0 (6.917)             | 12.53 (2.799)          |
| cifar10_resnet18_SSD_6.pth     | Frog         | 0.0 (5.532)             | 95.29 (0.156)          |
| cifar10_resnet18_SSD_7.pth     | Horse        | 0.0 (7.328)             | 17.71 (3.478)          |
| cifar10_resnet18_SSD_8.pth     | Ship         | 0.0 (3.783)             | 95.41 (0.158)          |
| cifar10_resnet18_SSD_9.pth     | Truck        | 0.0 (5.864)             | 94.29 (0.198)          |