
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3628796990
- CO2 Emissions (in grams): 1.1778

## Validation Metrics

- Loss: 0.091
- Accuracy: 0.976
- Precision: 0.984
- Recall: 0.968
- AUC: 0.990
- F1: 0.976
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["Kluuking/autotrain-data-cat-vs-dog250_250"], "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": 1.1778070728273002}}
transformers pytorch beit image-classification autotrain vision dataset:Kluuking/autotrain-data-cat-vs-dog250_250 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-Kluuking/autotrain-data-cat-vs-dog250_250 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3628796990
- CO2 Emissions (in grams): 1.1778

## Validation Metrics

- Loss: 0.091
- Accuracy: 0.976
- Precision: 0.984
- Recall: 0.968
- AUC: 0.990
- F1: 0.976
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3628796990
- CO2 Emissions (in grams): 1.1778 ## Validation Metrics

- Loss: 0.091
- Accuracy: 0.976
- Precision: 0.984
- Recall: 0.968
- AUC: 0.990
- F1: 0.976
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-Kluuking/autotrain-data-cat-vs-dog250_250 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3628796990
- CO2 Emissions (in grams): 1.1778 ## Validation Metrics

- Loss: 0.091
- Accuracy: 0.976
- Precision: 0.984
- Recall: 0.968
- AUC: 0.990
- F1: 0.976
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-Kluuking/autotrain-data-cat-vs-dog250_250 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3628796990
- CO2 Emissions (in grams): 1.1778## Validation Metrics

- Loss: 0.091
- Accuracy: 0.976
- Precision: 0.984
- Recall: 0.968
- AUC: 0.990
- F1: 0.976