
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 40197105212
- CO2 Emissions (in grams): 0.0082

## Validation Metrics

- Loss: 0.063
- Accuracy: 0.980
- Precision: 0.984
- Recall: 0.990
- AUC: 0.997
- F1: 0.987
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["katielink/autotrain-data-cxr-cfdl-repro"], "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": 0.008232136939739352}}
transformers pytorch vit image-classification autotrain vision dataset:katielink/autotrain-data-cxr-cfdl-repro co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-katielink/autotrain-data-cxr-cfdl-repro #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 40197105212
- CO2 Emissions (in grams): 0.0082

## Validation Metrics

- Loss: 0.063
- Accuracy: 0.980
- Precision: 0.984
- Recall: 0.990
- AUC: 0.997
- F1: 0.987
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 40197105212
- CO2 Emissions (in grams): 0.0082 ## Validation Metrics

- Loss: 0.063
- Accuracy: 0.980
- Precision: 0.984
- Recall: 0.990
- AUC: 0.997
- F1: 0.987
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-katielink/autotrain-data-cxr-cfdl-repro #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 40197105212
- CO2 Emissions (in grams): 0.0082 ## Validation Metrics

- Loss: 0.063
- Accuracy: 0.980
- Precision: 0.984
- Recall: 0.990
- AUC: 0.997
- F1: 0.987
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-katielink/autotrain-data-cxr-cfdl-repro #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 40197105212
- CO2 Emissions (in grams): 0.0082## Validation Metrics

- Loss: 0.063
- Accuracy: 0.980
- Precision: 0.984
- Recall: 0.990
- AUC: 0.997
- F1: 0.987