
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2977085925
- CO2 Emissions (in grams): 0.8069

## Validation Metrics

- Loss: 0.647
- Accuracy: 0.697
- Precision: 0.065
- Recall: 0.667
- AUC: 0.601
- F1: 0.118
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["Arm627/autotrain-data-wasp_classification_2.0"], "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": 0.8068778967193102}}
transformers pytorch vit image-classification autotrain vision dataset:Arm627/autotrain-data-wasp_classification_2.0 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-Arm627/autotrain-data-wasp_classification_2.0 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2977085925
- CO2 Emissions (in grams): 0.8069

## Validation Metrics

- Loss: 0.647
- Accuracy: 0.697
- Precision: 0.065
- Recall: 0.667
- AUC: 0.601
- F1: 0.118
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2977085925
- CO2 Emissions (in grams): 0.8069 ## Validation Metrics

- Loss: 0.647
- Accuracy: 0.697
- Precision: 0.065
- Recall: 0.667
- AUC: 0.601
- F1: 0.118
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-Arm627/autotrain-data-wasp_classification_2.0 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2977085925
- CO2 Emissions (in grams): 0.8069 ## Validation Metrics

- Loss: 0.647
- Accuracy: 0.697
- Precision: 0.065
- Recall: 0.667
- AUC: 0.601
- F1: 0.118
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-Arm627/autotrain-data-wasp_classification_2.0 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2977085925
- CO2 Emissions (in grams): 0.8069## Validation Metrics

- Loss: 0.647
- Accuracy: 0.697
- Precision: 0.065
- Recall: 0.667
- AUC: 0.601
- F1: 0.118