A2H0H0R1/plant-disease
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How to use A2H0H0R1/mobilenet_v2_1.0_224-plant-disease with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="A2H0H0R1/mobilenet_v2_1.0_224-plant-disease")
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("A2H0H0R1/mobilenet_v2_1.0_224-plant-disease")
model = AutoModelForImageClassification.from_pretrained("A2H0H0R1/mobilenet_v2_1.0_224-plant-disease", device_map="auto")This model is a fine-tuned version of google/mobilenet_v2_1.0_224 on the imagefolder dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0369 | 1.0 | 158 | 0.9116 | 0.8417 |
| 0.4523 | 2.0 | 316 | 0.4556 | 0.9038 |
| 0.3848 | 3.0 | 474 | 0.3579 | 0.9330 |
Base model
google/mobilenet_v2_1.0_224