ethz/food101
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How to use arieg/my_awesome_food_model with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="arieg/my_awesome_food_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("arieg/my_awesome_food_model")
model = AutoModelForImageClassification.from_pretrained("arieg/my_awesome_food_model")This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the food101 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 |
|---|---|---|---|---|
| 0.918 | 0.96 | 12 | 0.8973 | 0.97 |
| 0.8361 | 2.0 | 25 | 0.7851 | 0.995 |
| 0.7704 | 2.88 | 36 | 0.7792 | 0.99 |
Base model
google/vit-base-patch16-224-in21k