README.md

metadata

library_name: transformers
license: apache-2.0
base_model: timm/mobilenetv3_small_100.lamb_in1k
tags:
  - image-classification
  - vision
  - timm
  - generated_from_trainer
datasets:
  - AI-Lab-Makerere/beans
metrics:
  - accuracy
pipeline_tag: image-classification
model-index:
  - name: beans-image-classifier
    results:
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: AI-Lab-Makerere/beans
          type: AI-Lab-Makerere/beans
        metrics:
          - type: accuracy
            value: 0.9549
            name: Validation Accuracy
          - type: accuracy
            value: 0.8984
            name: Test Accuracy

Bean Leaf Disease Classifier

Fine-tuned MobileNetV3-Small on AI-Lab-Makerere/beans.

Given a photo of a bean leaf, the model predicts one of:

• angular_leaf_spot
• bean_rust
• healthy

Metrics

Split	Accuracy	Loss
Validation (best checkpoint)	95.49%	0.235
Test	89.84%	0.303

Training ran for 5 epochs on Apple Silicon (MPS). The best checkpoint was restored before export.

Usage

from transformers import pipeline

clf = pipeline("image-classification", model="omaralshareef/beans-image-classifier")
print(clf("leaf.jpg"))

Training hyperparameters

• learning rate: 5e-5
• train batch size: 16
• eval batch size: 16
• epochs: 5
• optimizer: AdamW
• seed: 42

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5874	1.0	65	0.4124	0.8346
0.4042	2.0	130	0.2352	0.9549
0.2805	3.0	195	0.1679	0.9549
0.2367	4.0	260	0.1370	0.9549
0.1933	5.0	325	0.1394	0.9398