
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44552112263
- CO2 Emissions (in grams): 0.2586

## Validation Metrics

- Loss: 0.098
- Accuracy: 0.923
- Macro F1: 0.911
- Micro F1: 0.923
- Weighted F1: 0.918
- Macro Precision: 0.958
- Micro Precision: 0.923
- Weighted Precision: 0.933
- Macro Recall: 0.889
- Micro Recall: 0.923
- Weighted Recall: 0.923
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["bazudde/autotrain-data-sweet-potato-classification"], "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": 0.2585547491917275}}
transformers pytorch beit image-classification autotrain vision dataset:bazudde/autotrain-data-sweet-potato-classification co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-bazudde/autotrain-data-sweet-potato-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44552112263
- CO2 Emissions (in grams): 0.2586

## Validation Metrics

- Loss: 0.098
- Accuracy: 0.923
- Macro F1: 0.911
- Micro F1: 0.923
- Weighted F1: 0.918
- Macro Precision: 0.958
- Micro Precision: 0.923
- Weighted Precision: 0.933
- Macro Recall: 0.889
- Micro Recall: 0.923
- Weighted Recall: 0.923
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44552112263
- CO2 Emissions (in grams): 0.2586 ## Validation Metrics

- Loss: 0.098
- Accuracy: 0.923
- Macro F1: 0.911
- Micro F1: 0.923
- Weighted F1: 0.918
- Macro Precision: 0.958
- Micro Precision: 0.923
- Weighted Precision: 0.933
- Macro Recall: 0.889
- Micro Recall: 0.923
- Weighted Recall: 0.923
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-bazudde/autotrain-data-sweet-potato-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44552112263
- CO2 Emissions (in grams): 0.2586 ## Validation Metrics

- Loss: 0.098
- Accuracy: 0.923
- Macro F1: 0.911
- Micro F1: 0.923
- Weighted F1: 0.918
- Macro Precision: 0.958
- Micro Precision: 0.923
- Weighted Precision: 0.933
- Macro Recall: 0.889
- Micro Recall: 0.923
- Weighted Recall: 0.923
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-bazudde/autotrain-data-sweet-potato-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44552112263
- CO2 Emissions (in grams): 0.2586## Validation Metrics

- Loss: 0.098
- Accuracy: 0.923
- Macro F1: 0.911
- Micro F1: 0.923
- Weighted F1: 0.918
- Macro Precision: 0.958
- Micro Precision: 0.923
- Weighted Precision: 0.933
- Macro Recall: 0.889
- Micro Recall: 0.923
- Weighted Recall: 0.923