| 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`](https://huggingface.co/datasets/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 | |
| ```python | |
| from transformers import pipeline | |
| clf = pipeline("image-classification", model="lustachowicz/beans-vit") | |
| clf("leaf.jpg", top_k=3) | |
| ``` | |