metadata
library_name: transformers
pipeline_tag: image-classification
base_model: google/vit-base-patch16-224
datasets:
- AI-Lab-Makerere/beans
metrics:
- accuracy
tags:
- vision
- image-classification
beans-vit
google/vit-base-patch16-224 fine-tuned on AI-Lab-Makerere/beans
(bean-leaf disease classification) for Lab 1 of Przetwarzanie Danych w Chmurze.
Classes: angular_leaf_spot, bean_rust, healthy
Results (test split)
- Accuracy: 0.9688
- Macro F1: 0.9691
| class | precision | recall | f1-score | support |
|---|---|---|---|---|
| angular_leaf_spot | 1 | 0.9302 | 0.9639 | 43 |
| bean_rust | 0.9149 | 1 | 0.9556 | 43 |
| healthy | 1 | 0.9762 | 0.988 | 42 |
Training
Epochs: 3, learning rate: 5e-05, batch size: 32, fp16 on a Colab T4. Experiments tracked with MLflow.
Usage
from transformers import pipeline
clf = pipeline("image-classification", model="lustachowicz/beans-vit")
clf("leaf.jpg", top_k=3)