
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3723199088
- CO2 Emissions (in grams): 0.0068

## Validation Metrics

- Loss: 0.007
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["8kkillian/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": 0.006795456289175795}}
transformers pytorch swin image-classification autotrain vision dataset:8kkillian/autotrain-data-weather-classification co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-8kkillian/autotrain-data-weather-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3723199088
- CO2 Emissions (in grams): 0.0068

## Validation Metrics

- Loss: 0.007
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3723199088
- CO2 Emissions (in grams): 0.0068 ## Validation Metrics

- Loss: 0.007
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-8kkillian/autotrain-data-weather-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3723199088
- CO2 Emissions (in grams): 0.0068 ## Validation Metrics

- Loss: 0.007
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000