
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1471154050
- CO2 Emissions (in grams): 135.1875

## Validation Metrics

- Loss: 0.391
- Accuracy: 0.890
- Macro F1: 0.890
- Micro F1: 0.890
- Weighted F1: 0.890
- Macro Precision: 0.892
- Micro Precision: 0.890
- Weighted Precision: 0.892
- Macro Recall: 0.890
- Micro Recall: 0.890
- Weighted Recall: 0.890
{"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": 135.18748471833436}}
transformers pytorch safetensors autotrain vision image-classification dataset:juliensimon/autotrain-data-food101 co2_eq_emissions endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #autotrain #vision #image-classification #dataset-juliensimon/autotrain-data-food101 #co2_eq_emissions #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1471154050
- CO2 Emissions (in grams): 135.1875

## Validation Metrics

- Loss: 0.391
- Accuracy: 0.890
- Macro F1: 0.890
- Micro F1: 0.890
- Weighted F1: 0.890
- Macro Precision: 0.892
- Micro Precision: 0.890
- Weighted Precision: 0.892
- Macro Recall: 0.890
- Micro Recall: 0.890
- Weighted Recall: 0.890
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1471154050
- CO2 Emissions (in grams): 135.1875 ## Validation Metrics

- Loss: 0.391
- Accuracy: 0.890
- Macro F1: 0.890
- Micro F1: 0.890
- Weighted F1: 0.890
- Macro Precision: 0.892
- Micro Precision: 0.890
- Weighted Precision: 0.892
- Macro Recall: 0.890
- Micro Recall: 0.890
- Weighted Recall: 0.890
TAGS
#transformers #pytorch #safetensors #autotrain #vision #image-classification #dataset-juliensimon/autotrain-data-food101 #co2_eq_emissions #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1471154050
- CO2 Emissions (in grams): 135.1875 ## Validation Metrics

- Loss: 0.391
- Accuracy: 0.890
- Macro F1: 0.890
- Micro F1: 0.890
- Weighted F1: 0.890
- Macro Precision: 0.892
- Micro Precision: 0.890
- Weighted Precision: 0.892
- Macro Recall: 0.890
- Micro Recall: 0.890
- Weighted Recall: 0.890
passage: TAGS
#transformers #pytorch #safetensors #autotrain #vision #image-classification #dataset-juliensimon/autotrain-data-food101 #co2_eq_emissions #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1471154050
- CO2 Emissions (in grams): 135.1875## Validation Metrics

- Loss: 0.391
- Accuracy: 0.890
- Macro F1: 0.890
- Micro F1: 0.890
- Weighted F1: 0.890
- Macro Precision: 0.892
- Micro Precision: 0.890
- Weighted Precision: 0.892
- Macro Recall: 0.890
- Micro Recall: 0.890
- Weighted Recall: 0.890