
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3739699410
- CO2 Emissions (in grams): 12.1730

## Validation Metrics

- Loss: 0.162
- Accuracy: 0.949
- Macro F1: 0.954
- Micro F1: 0.949
- Weighted F1: 0.949
- Macro Precision: 0.958
- Micro Precision: 0.949
- Weighted Precision: 0.950
- Macro Recall: 0.951
- Micro Recall: 0.949
- Weighted Recall: 0.949
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["dazzle-nu/autotrain-data-weather-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": 12.172961992218216}}
transformers pytorch beit image-classification autotrain vision dataset:dazzle-nu/autotrain-data-weather-classification co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-dazzle-nu/autotrain-data-weather-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3739699410
- CO2 Emissions (in grams): 12.1730

## Validation Metrics

- Loss: 0.162
- Accuracy: 0.949
- Macro F1: 0.954
- Micro F1: 0.949
- Weighted F1: 0.949
- Macro Precision: 0.958
- Micro Precision: 0.949
- Weighted Precision: 0.950
- Macro Recall: 0.951
- Micro Recall: 0.949
- Weighted Recall: 0.949
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3739699410
- CO2 Emissions (in grams): 12.1730 ## Validation Metrics

- Loss: 0.162
- Accuracy: 0.949
- Macro F1: 0.954
- Micro F1: 0.949
- Weighted F1: 0.949
- Macro Precision: 0.958
- Micro Precision: 0.949
- Weighted Precision: 0.950
- Macro Recall: 0.951
- Micro Recall: 0.949
- Weighted Recall: 0.949
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-dazzle-nu/autotrain-data-weather-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3739699410
- CO2 Emissions (in grams): 12.1730 ## Validation Metrics

- Loss: 0.162
- Accuracy: 0.949
- Macro F1: 0.954
- Micro F1: 0.949
- Weighted F1: 0.949
- Macro Precision: 0.958
- Micro Precision: 0.949
- Weighted Precision: 0.950
- Macro Recall: 0.951
- Micro Recall: 0.949
- Weighted Recall: 0.949
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-dazzle-nu/autotrain-data-weather-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3739699410
- CO2 Emissions (in grams): 12.1730## Validation Metrics

- Loss: 0.162
- Accuracy: 0.949
- Macro F1: 0.954
- Micro F1: 0.949
- Weighted F1: 0.949
- Macro Precision: 0.958
- Micro Precision: 0.949
- Weighted Precision: 0.950
- Macro Recall: 0.951
- Micro Recall: 0.949
- Weighted Recall: 0.949