
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3206689984
- CO2 Emissions (in grams): 2.1410

## Validation Metrics

- Loss: 0.303
- Accuracy: 0.846
- Precision: 0.846
- Recall: 0.846
- AUC: 0.929
- F1: 0.846
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["Kanr1u/autotrain-data-emma2"], "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": 2.1409787540187346}}
transformers pytorch swin image-classification autotrain vision dataset:Kanr1u/autotrain-data-emma2 co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-Kanr1u/autotrain-data-emma2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3206689984
- CO2 Emissions (in grams): 2.1410

## Validation Metrics

- Loss: 0.303
- Accuracy: 0.846
- Precision: 0.846
- Recall: 0.846
- AUC: 0.929
- F1: 0.846
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3206689984
- CO2 Emissions (in grams): 2.1410 ## Validation Metrics

- Loss: 0.303
- Accuracy: 0.846
- Precision: 0.846
- Recall: 0.846
- AUC: 0.929
- F1: 0.846
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-Kanr1u/autotrain-data-emma2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3206689984
- CO2 Emissions (in grams): 2.1410 ## Validation Metrics

- Loss: 0.303
- Accuracy: 0.846
- Precision: 0.846
- Recall: 0.846
- AUC: 0.929
- F1: 0.846
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-Kanr1u/autotrain-data-emma2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3206689984
- CO2 Emissions (in grams): 2.1410## Validation Metrics

- Loss: 0.303
- Accuracy: 0.846
- Precision: 0.846
- Recall: 0.846
- AUC: 0.929
- F1: 0.846