---
license: apache-2.0
base_model: google/vit-base-patch16-224
datasets:
  - meganariley/inat-wildflowers-25
tags:
  - image-classification
  - wildflowers
  - plants
  - inaturalist
  - vit
  - vision
metrics:
  - accuracy
pipeline_tag: image-classification
model-index:
  - name: wildflower-classifier-vit
    results:
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: inat-wildflowers-25
          type: meganariley/inat-wildflowers-25
          split: test
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.979
---

# 🌸 Wildflower Classifier — ViT Base

A **Vision Transformer (ViT)** fine-tuned to identify **25 North American wildflower species** from photographs, achieving **97.9% test accuracy**.

## Model Details

- **Base model**: [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224)
- **Architecture**: ViT-Base (86.6M params, patch size 16, input 224×224)
- **Task**: Multi-class image classification (25 classes)
- **Training data**: [meganariley/inat-wildflowers-25](https://huggingface.co/datasets/meganariley/inat-wildflowers-25) — 10,000 research-grade iNaturalist photos

## Performance

| Split | Accuracy | Loss |
|-------|----------|------|
| Validation | 97.1% | 0.098 |
| **Test** | **97.9%** | **0.082** |

### Per-Class Test Accuracy

| Species | Accuracy | Species | Accuracy |
|---------|----------|---------|----------|
| Blazing Star | 95.0% | Marsh Marigold | 97.5% |
| Blue Flag Iris | 100.0% | Ox-eye Daisy | 95.0% |
| California Poppy | 97.5% | Queen Anne's Lace | 95.0% |
| Canada Goldenrod | 100.0% | Spring Beauty | 100.0% |
| Cardinal Flower | 100.0% | Trout Lily | 100.0% |
| Colorado Columbine | 97.5% | Virginia Bluebells | 97.5% |
| Common Milkweed | 97.5% | White Trillium | 97.5% |
| Common Yarrow | 100.0% | Wild Bergamot | 97.5% |
| Dutchman's Breeches | 100.0% | Wild Columbine | 100.0% |
| Fireweed | 95.0% | Wild Lupine | 100.0% |
| Indian Blanket | 97.5% | Wild Rose | 100.0% |
| Indian Paintbrush | 95.0% | Joe-Pye Weed | 95.0% |
| Jack-in-the-Pulpit | 97.5% | | |

**10 species at 100% accuracy** · All species ≥ 95%

## Training

- **Epochs**: 5
- **Optimizer**: AdamW (lr=5e-5, weight_decay=0.01)
- **Batch size**: 16 × 4 gradient accumulation = effective 64
- **Warmup**: 10% linear
- **Augmentation**: RandomResizedCrop, HorizontalFlip, ColorJitter
- **Hardware**: CPU (8 vCPU / 32GB RAM)
- **Training time**: ~2 hours

### Training Curve

| Epoch | Val Accuracy | Val Loss |
|-------|-------------|----------|
| 1 | 93.5% | 0.255 |
| 2 | 95.2% | 0.146 |
| 3 | 96.3% | 0.114 |
| 4 | 97.0% | 0.104 |
| 5 | 97.1% | 0.098 |

## Usage

```python
from transformers import pipeline

classifier = pipeline("image-classification", model="meganariley/wildflower-classifier-vit")
results = classifier("path/to/wildflower.jpg", top_k=5)
for r in results:
    print(f"{r['label']}: {r['score']:.3f}")
```

## Demo

Try it live: [🌸 Wildflower Identifier Space](https://huggingface.co/spaces/meganariley/wildflower-identifier)

## License

Apache 2.0 (base model license). Training data from iNaturalist under CC BY-NC 4.0.