ethz/food101
Viewer • Updated • 101k • 27.9k • 136
How to use faldeus0092/image_classification with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="faldeus0092/image_classification")
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("faldeus0092/image_classification")
model = AutoModelForImageClassification.from_pretrained("faldeus0092/image_classification")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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.6551 | 0.99 | 62 | 2.5197 | 0.838 |
| 1.8088 | 2.0 | 125 | 1.7662 | 0.893 |
| 1.5857 | 2.98 | 186 | 1.6207 | 0.885 |
Base model
google/vit-base-patch16-224-in21k