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# plant_disease_detection(vriksharakshak)

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0880
- Accuracy: 0.9811

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

# use this model
```python
from transformers import pipeline
from PIL import Image
import requests

# Load the image classification pipeline with a specific model
pipe = pipeline("image-classification", "ozair23/swin-tiny-patch4-window7-224-finetuned-plantdisease")

# Load the image from a URL
url = 'https://huggingface.co/nielsr/convnext-tiny-finetuned-eurostat/resolve/main/forest.png'
image = Image.open(requests.get(url, stream=True).raw)

# Classify the image
results = pipe(image)

# Display the results
print("Predictions:")
for result in results:
    print(f"Label: {result['label']}, Score: {result['score']:.4f}")
```
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.1968        | 0.9983 | 145  | 0.0880          | 0.9811   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
pepper__bell___bacterial_spot pepper__bell___healthy potato___early_blight potato___late_blight potato___healthy tomato_bacterial_spot tomato_early_blight tomato_late_blight tomato_leaf_mold tomato_septoria_leaf_spot tomato_spider_mites_two_spotted_spider_mite tomato__target_spot tomato__tomato_yellowleaf__curl_virus tomato__tomato_mosaic_virus tomato_healthy