
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2797882537
- CO2 Emissions (in grams): 2.7585

## Validation Metrics

- Loss: 0.076
- Accuracy: 0.970
- Precision: 0.980
- Recall: 0.988
- AUC: 0.991
- F1: 0.984
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["team-marmalade/autotrain-data-lots_of_text"], "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": 2.7585473731043173}}
transformers pytorch swin image-classification autotrain vision dataset:team-marmalade/autotrain-data-lots_of_text co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-team-marmalade/autotrain-data-lots_of_text #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2797882537
- CO2 Emissions (in grams): 2.7585

## Validation Metrics

- Loss: 0.076
- Accuracy: 0.970
- Precision: 0.980
- Recall: 0.988
- AUC: 0.991
- F1: 0.984
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2797882537
- CO2 Emissions (in grams): 2.7585 ## Validation Metrics

- Loss: 0.076
- Accuracy: 0.970
- Precision: 0.980
- Recall: 0.988
- AUC: 0.991
- F1: 0.984
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-team-marmalade/autotrain-data-lots_of_text #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2797882537
- CO2 Emissions (in grams): 2.7585 ## Validation Metrics

- Loss: 0.076
- Accuracy: 0.970
- Precision: 0.980
- Recall: 0.988
- AUC: 0.991
- F1: 0.984
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-team-marmalade/autotrain-data-lots_of_text #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2797882537
- CO2 Emissions (in grams): 2.7585## Validation Metrics

- Loss: 0.076
- Accuracy: 0.970
- Precision: 0.980
- Recall: 0.988
- AUC: 0.991
- F1: 0.984