| | --- |
| | tags: |
| | - autotrain |
| | - vision |
| | - image-classification |
| | datasets: |
| | - juliensimon/autotrain-data-food101 |
| | widget: |
| | - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg |
| | example_title: Tiger |
| | - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg |
| | example_title: Teapot |
| | - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg |
| | example_title: Palace |
| | co2_eq_emissions: |
| | emissions: 179.11544810549532 |
| | --- |
| | |
| | # Usage |
| |
|
| | ``` |
| | from transformers import pipeline |
| | p = pipeline("image-classification", model="juliensimon/autotrain-food101-1471154053") |
| | result = p("my_image.jpg") |
| | ``` |
| |
|
| | # Model Trained Using AutoTrain |
| |
|
| | - Problem type: Multi-class Classification |
| | - Model ID: 1471154053 |
| | - CO2 Emissions (in grams): 179.1154 |
| |
|
| | ## Validation Metrics |
| |
|
| | - Loss: 0.301 |
| | - Accuracy: 0.915 |
| | - Macro F1: 0.915 |
| | - Micro F1: 0.915 |
| | - Weighted F1: 0.915 |
| | - Macro Precision: 0.917 |
| | - Micro Precision: 0.915 |
| | - Weighted Precision: 0.917 |
| | - Macro Recall: 0.915 |
| | - Micro Recall: 0.915 |
| | - Weighted Recall: 0.915 |
