
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 50524120657
- CO2 Emissions (in grams): 0.0082

## Validation Metrics

- Loss: 0.299
- Accuracy: 0.900
- Precision: 0.931
- Recall: 0.900
- AUC: 0.952
- F1: 0.915
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["DanielDo/autotrain-data-segundaentrega"], "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": 0.00823845139737281}}
transformers pytorch swin image-classification autotrain vision dataset:DanielDo/autotrain-data-segundaentrega co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-DanielDo/autotrain-data-segundaentrega #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 50524120657
- CO2 Emissions (in grams): 0.0082

## Validation Metrics

- Loss: 0.299
- Accuracy: 0.900
- Precision: 0.931
- Recall: 0.900
- AUC: 0.952
- F1: 0.915
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 50524120657
- CO2 Emissions (in grams): 0.0082 ## Validation Metrics

- Loss: 0.299
- Accuracy: 0.900
- Precision: 0.931
- Recall: 0.900
- AUC: 0.952
- F1: 0.915
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-DanielDo/autotrain-data-segundaentrega #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 50524120657
- CO2 Emissions (in grams): 0.0082 ## Validation Metrics

- Loss: 0.299
- Accuracy: 0.900
- Precision: 0.931
- Recall: 0.900
- AUC: 0.952
- F1: 0.915
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-DanielDo/autotrain-data-segundaentrega #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 50524120657
- CO2 Emissions (in grams): 0.0082## Validation Metrics

- Loss: 0.299
- Accuracy: 0.900
- Precision: 0.931
- Recall: 0.900
- AUC: 0.952
- F1: 0.915