
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2885884378
- CO2 Emissions (in grams): 1.1398

## Validation Metrics

- Loss: 0.079
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["owsgfwnlgjuz/autotrain-data-test_auto_nlp"], "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": 1.139809838906873}}
transformers pytorch swin image-classification autotrain vision dataset:owsgfwnlgjuz/autotrain-data-test_auto_nlp co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-owsgfwnlgjuz/autotrain-data-test_auto_nlp #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2885884378
- CO2 Emissions (in grams): 1.1398

## Validation Metrics

- Loss: 0.079
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2885884378
- CO2 Emissions (in grams): 1.1398 ## Validation Metrics

- Loss: 0.079
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-owsgfwnlgjuz/autotrain-data-test_auto_nlp #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2885884378
- CO2 Emissions (in grams): 1.1398 ## Validation Metrics

- Loss: 0.079
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-owsgfwnlgjuz/autotrain-data-test_auto_nlp #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2885884378
- CO2 Emissions (in grams): 1.1398## Validation Metrics

- Loss: 0.079
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000