ResNet-18 Bean Leaf Disease Classifier

This model is a fine-tuned version of microsoft/resnet-18, trained on the AI-Lab-Makerere/beans dataset.

It classifies bean-leaf images into three categories:

• angular_leaf_spot
• bean_rust
• healthy

Test results

The model was evaluated on the official test split containing 128 images.

Per-class results

Confusion matrix

Training configuration

• Base model: Microsoft ResNet-18
• Epochs: 10
• Learning rate: 5e-5
• Training batch size: 8
• Gradient accumulation steps: 2
• Effective batch size: 16
• Weight decay: 0.01
• Random seed: 42
• Best checkpoint selected using validation macro-F1

Example usage

from PIL import Image
from transformers import pipeline

classifier = pipeline(
    "image-classification",
    model="Zharasbek/resnet18-bean-disease-classifier",
)

image = Image.open("bean_leaf.jpg").convert("RGB")
predictions = classifier(image, top_k=3)

print(predictions)

Intended use

This model was created as an educational project demonstrating fine-tuning, evaluation, model publishing, and deployment.

Limitations

The model supports only the three classes present in the Beans dataset. It may produce unreliable predictions for:

• Other crops or plant species
• Diseases absent from the dataset
• Images captured under substantially different conditions
• Images that do not contain bean leaves

The model has not been clinically or agriculturally validated and should not be used as the sole basis for crop-management decisions.

Licenses and attribution

The base model is distributed under the Apache 2.0 license.

The Beans dataset is distributed under the MIT license.