
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3129688461
- CO2 Emissions (in grams): 8.0323

## Validation Metrics

- Loss: 0.445
- Accuracy: 0.774
- Precision: 0.738
- Recall: 0.990
- AUC: 0.920
- F1: 0.846
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["learnsolana/autotrain-data-chest-xray-demo"], "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": 8.032313770239128}}
transformers pytorch resnet image-classification autotrain vision dataset:learnsolana/autotrain-data-chest-xray-demo co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #resnet #image-classification #autotrain #vision #dataset-learnsolana/autotrain-data-chest-xray-demo #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3129688461
- CO2 Emissions (in grams): 8.0323

## Validation Metrics

- Loss: 0.445
- Accuracy: 0.774
- Precision: 0.738
- Recall: 0.990
- AUC: 0.920
- F1: 0.846
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3129688461
- CO2 Emissions (in grams): 8.0323 ## Validation Metrics

- Loss: 0.445
- Accuracy: 0.774
- Precision: 0.738
- Recall: 0.990
- AUC: 0.920
- F1: 0.846
TAGS
#transformers #pytorch #resnet #image-classification #autotrain #vision #dataset-learnsolana/autotrain-data-chest-xray-demo #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3129688461
- CO2 Emissions (in grams): 8.0323 ## Validation Metrics

- Loss: 0.445
- Accuracy: 0.774
- Precision: 0.738
- Recall: 0.990
- AUC: 0.920
- F1: 0.846
TAGS
#transformers #pytorch #resnet #image-classification #autotrain #vision #dataset-learnsolana/autotrain-data-chest-xray-demo #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3129688461
- CO2 Emissions (in grams): 8.0323## Validation Metrics

- Loss: 0.445
- Accuracy: 0.774
- Precision: 0.738
- Recall: 0.990
- AUC: 0.920
- F1: 0.846