ethz/food101
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How to use farhanyh/food_model with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="farhanyh/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("farhanyh/food_model")
model = AutoModelForImageClassification.from_pretrained("farhanyh/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 |
|---|---|---|---|---|
| 2.718 | 0.99 | 62 | 2.5596 | 0.842 |
| 1.8555 | 2.0 | 125 | 1.8344 | 0.873 |
| 1.6437 | 2.98 | 186 | 1.6470 | 0.909 |
Base model
google/vit-base-patch16-224-in21k