| --- |
| 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](https://huggingface.co/timm/mobilenetv3_small_100.lamb_in1k) on [AI-Lab-Makerere/beans](https://huggingface.co/datasets/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 |
|
|
| ```python |
| 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 | |
|
|
