ethz/food101
Viewer • Updated • 101k • 63.2k • 142
How to use MHRDYN7/my_awesome_food_model with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="MHRDYN7/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("MHRDYN7/my_awesome_food_model")
model = AutoModelForImageClassification.from_pretrained("MHRDYN7/my_awesome_food_model", device_map="auto")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 |
|---|---|---|---|---|
| 2.7036 | 0.99 | 62 | 2.4963 | 0.839 |
| 1.808 | 2.0 | 125 | 1.7523 | 0.875 |
| 1.5765 | 2.98 | 186 | 1.6130 | 0.889 |
Base model
google/vit-base-patch16-224-in21k