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cifar-10-lenet5
aijadugar/cifar-10-lenet5
cifar-10-lenet5 is a image classification model from aijadugar. Use it when you need a label for an image. It is set up for pytorch. The card lists the license as mit.
A PyTorch implementation of the classic LeNet-5 architecture trained on the CIFAR-10 dataset.
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At a glance
- Task
- Image Classification
- Library
- pytorch
- License
- mit
- Access
- Public
- Created
- Jul 16, 2026
- Updated
- Jul 16, 2026
- SHA
- 1dfde532
Datasets
Model card
From the Hugging Face model README
LeNet-5 on CIFAR-10
A PyTorch implementation of the classic LeNet-5 architecture trained on the CIFAR-10 dataset.
Model Details
- Architecture: LeNet-5
- Framework: PyTorch
- Dataset: CIFAR-10
- Input Size: 3 × 32 × 32
- Classes: 10
CIFAR-10 Classes
| Label | Class |
|---|---|
| 0 | airplane |
| 1 | automobile |
| 2 | bird |
| 3 | cat |
| 4 | deer |
| 5 | dog |
| 6 | frog |
| 7 | horse |
| 8 | ship |
| 9 | truck |
Training
- Optimizer: Adam
- Learning Rate: 1e-3
- Loss Function: CrossEntropyLoss
- Epochs: 20
- Batch Size: 64
Performance
| Metric | Value |
|---|---|
| Test Accuracy | 58.32% |
Model Files
lenet5_cifar10.pth— Trained model weights
Load Model
import torch
model = LeNet5()
model.load_state_dict(torch.load("lenet5_cifar10.pth"))
model.eval()
Inference
with torch.no_grad():
outputs = model(images)
_, predicted = torch.max(outputs, 1)
Author
Ankit Bari
- GitHub: https://github.com/aijadugar
- Hugging Face: https://huggingface.co/aijadugar
- Task
- Image Classification
- Library
- pytorch
- License
- mit
- Languages
- en
- Created
- Jul 16, 2026
- Updated
- Jul 16, 2026