Instructions to use chandiwanablessing/plant-disease-mega-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chandiwanablessing/plant-disease-mega-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="chandiwanablessing/plant-disease-mega-model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("chandiwanablessing/plant-disease-mega-model") model = AutoModelForImageClassification.from_pretrained("chandiwanablessing/plant-disease-mega-model") - Notebooks
- Google Colab
- Kaggle
plant-disease-mega-model
This model is a fine-tuned version of HurudzaAI/plantdiseasedetection1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0131
- Accuracy: 0.9980
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3052 | 1.0 | 859 | 0.0351 | 0.9882 |
| 0.0165 | 2.0 | 1718 | 0.0392 | 0.9908 |
| 0.0072 | 3.0 | 2577 | 0.0418 | 0.9889 |
| 0.0041 | 4.0 | 3436 | 0.0248 | 0.9915 |
| 0.0044 | 5.0 | 4295 | 0.0154 | 0.9974 |
| 0.0000 | 6.0 | 5154 | 0.0126 | 0.9974 |
| 0.0000 | 7.0 | 6013 | 0.0126 | 0.9980 |
| 0.0000 | 8.0 | 6872 | 0.0129 | 0.9980 |
| 0.0000 | 9.0 | 7731 | 0.0130 | 0.9980 |
| 0.0000 | 10.0 | 8590 | 0.0131 | 0.9980 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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Model tree for chandiwanablessing/plant-disease-mega-model
Base model
WinKawaks/vit-tiny-patch16-224 Finetuned
HurudzaAI/plantdiseasedetection1