
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 50583120813
- CO2 Emissions (in grams): 0.3292

## Validation Metrics

- Loss: 0.602
- Accuracy: 0.750
- Precision: 0.812
- Recall: 0.812
- AUC: 0.793
- F1: 0.812
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["suatatan/autotrain-data-red-arrow-finder"], "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": 0.32918055904446797}}
transformers pytorch beit image-classification autotrain vision dataset:suatatan/autotrain-data-red-arrow-finder co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-suatatan/autotrain-data-red-arrow-finder #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 50583120813
- CO2 Emissions (in grams): 0.3292

## Validation Metrics

- Loss: 0.602
- Accuracy: 0.750
- Precision: 0.812
- Recall: 0.812
- AUC: 0.793
- F1: 0.812
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 50583120813
- CO2 Emissions (in grams): 0.3292 ## Validation Metrics

- Loss: 0.602
- Accuracy: 0.750
- Precision: 0.812
- Recall: 0.812
- AUC: 0.793
- F1: 0.812
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-suatatan/autotrain-data-red-arrow-finder #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 50583120813
- CO2 Emissions (in grams): 0.3292 ## Validation Metrics

- Loss: 0.602
- Accuracy: 0.750
- Precision: 0.812
- Recall: 0.812
- AUC: 0.793
- F1: 0.812
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-suatatan/autotrain-data-red-arrow-finder #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 50583120813
- CO2 Emissions (in grams): 0.3292## Validation Metrics

- Loss: 0.602
- Accuracy: 0.750
- Precision: 0.812
- Recall: 0.812
- AUC: 0.793
- F1: 0.812