
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3739699407
- CO2 Emissions (in grams): 0.0526

## Validation Metrics

- Loss: 0.149
- Accuracy: 0.952
- Macro F1: 0.957
- Micro F1: 0.952
- Weighted F1: 0.952
- Macro Precision: 0.961
- Micro Precision: 0.952
- Weighted Precision: 0.953
- Macro Recall: 0.955
- Micro Recall: 0.952
- Weighted Recall: 0.952
{"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": 0.05261654582866757}}
transformers pytorch vit image-classification autotrain vision dataset:dazzle-nu/autotrain-data-weather-classification co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #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: 3739699407
- CO2 Emissions (in grams): 0.0526

## Validation Metrics

- Loss: 0.149
- Accuracy: 0.952
- Macro F1: 0.957
- Micro F1: 0.952
- Weighted F1: 0.952
- Macro Precision: 0.961
- Micro Precision: 0.952
- Weighted Precision: 0.953
- Macro Recall: 0.955
- Micro Recall: 0.952
- Weighted Recall: 0.952
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3739699407
- CO2 Emissions (in grams): 0.0526 ## Validation Metrics

- Loss: 0.149
- Accuracy: 0.952
- Macro F1: 0.957
- Micro F1: 0.952
- Weighted F1: 0.952
- Macro Precision: 0.961
- Micro Precision: 0.952
- Weighted Precision: 0.953
- Macro Recall: 0.955
- Micro Recall: 0.952
- Weighted Recall: 0.952
TAGS
#transformers #pytorch #vit #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: 3739699407
- CO2 Emissions (in grams): 0.0526 ## Validation Metrics

- Loss: 0.149
- Accuracy: 0.952
- Macro F1: 0.957
- Micro F1: 0.952
- Weighted F1: 0.952
- Macro Precision: 0.961
- Micro Precision: 0.952
- Weighted Precision: 0.953
- Macro Recall: 0.955
- Micro Recall: 0.952
- Weighted Recall: 0.952
TAGS
#transformers #pytorch #vit #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: 3739699407
- CO2 Emissions (in grams): 0.0526## Validation Metrics

- Loss: 0.149
- Accuracy: 0.952
- Macro F1: 0.957
- Micro F1: 0.952
- Weighted F1: 0.952
- Macro Precision: 0.961
- Micro Precision: 0.952
- Weighted Precision: 0.953
- Macro Recall: 0.955
- Micro Recall: 0.952
- Weighted Recall: 0.952