
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 34284130630
- CO2 Emissions (in grams): 0.4145

## Validation Metrics

- Loss: 0.070
- Accuracy: 0.989
- Precision: 0.978
- Recall: 1.000
- AUC: 0.998
- F1: 0.989
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["frncscp/autotrain-data-autopatacotron"], "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": 0.41447738215787666}}
transformers pytorch swin image-classification autotrain vision dataset:frncscp/autotrain-data-autopatacotron co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-frncscp/autotrain-data-autopatacotron #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 34284130630
- CO2 Emissions (in grams): 0.4145

## Validation Metrics

- Loss: 0.070
- Accuracy: 0.989
- Precision: 0.978
- Recall: 1.000
- AUC: 0.998
- F1: 0.989
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 34284130630
- CO2 Emissions (in grams): 0.4145 ## Validation Metrics

- Loss: 0.070
- Accuracy: 0.989
- Precision: 0.978
- Recall: 1.000
- AUC: 0.998
- F1: 0.989
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-frncscp/autotrain-data-autopatacotron #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 34284130630
- CO2 Emissions (in grams): 0.4145 ## Validation Metrics

- Loss: 0.070
- Accuracy: 0.989
- Precision: 0.978
- Recall: 1.000
- AUC: 0.998
- F1: 0.989