
# Country flag classification
This model has been trained on flags from following countries.
- Austria
- Belgium
- Bulgaria
- Croatia
- Czech Republic
- Denmark
- Estonia
- Finland
- France
- Germany
- Greece
- Holland
- Hungary
- Ireland
- Italy
- Latvia
- Lithuania
- Luxembourg
- Malta
- Slovakia
- Slovenia
- South Cyprus
- Spain
- Sweden

## Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 61828134901
- CO2 Emissions (in grams): 0.3887

## Validation Metrics
- Loss: 0.157
- Accuracy: 0.947
- Macro F1: 0.938
- Micro F1: 0.947
- Weighted F1: 0.946
- Macro Precision: 0.951
- Micro Precision: 0.947
- Weighted Precision: 0.954
- Macro Recall: 0.938
- Micro Recall: 0.947
- Weighted Recall: 0.947

{"tags": ["vision", "image-classification", "flags", "geography"], "datasets": ["dwancin/country-flags"], "widget": [{"src": "https://huggingface.co/dwancin/flag-classification/resolve/main/flag.png", "example_title": "German flag"}, {"src": "https://huggingface.co/dwancin/flag-classification/resolve/main/flag2.png", "example_title": "Danish flag"}], "co2_eq_emissions": {"emissions": 0.3886756137436338}}
transformers pytorch swin image-classification vision flags geography dataset:dwancin/country-flags co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #vision #flags #geography #dataset-dwancin/country-flags #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Country flag classification
This model has been trained on flags from following countries.
- Austria
- Belgium
- Bulgaria
- Croatia
- Czech Republic
- Denmark
- Estonia
- Finland
- France
- Germany
- Greece
- Holland
- Hungary
- Ireland
- Italy
- Latvia
- Lithuania
- Luxembourg
- Malta
- Slovakia
- Slovenia
- South Cyprus
- Spain
- Sweden

## Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 61828134901
- CO2 Emissions (in grams): 0.3887

## Validation Metrics
- Loss: 0.157
- Accuracy: 0.947
- Macro F1: 0.938
- Micro F1: 0.947
- Weighted F1: 0.946
- Macro Precision: 0.951
- Micro Precision: 0.947
- Weighted Precision: 0.954
- Macro Recall: 0.938
- Micro Recall: 0.947
- Weighted Recall: 0.947

# Country flag classification
This model has been trained on flags from following countries.
- Austria
- Belgium
- Bulgaria
- Croatia
- Czech Republic
- Denmark
- Estonia
- Finland
- France
- Germany
- Greece
- Holland
- Hungary
- Ireland
- Italy
- Latvia
- Lithuania
- Luxembourg
- Malta
- Slovakia
- Slovenia
- South Cyprus
- Spain
- Sweden ## Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 61828134901
- CO2 Emissions (in grams): 0.3887 ## Validation Metrics
- Loss: 0.157
- Accuracy: 0.947
- Macro F1: 0.938
- Micro F1: 0.947
- Weighted F1: 0.946
- Macro Precision: 0.951
- Micro Precision: 0.947
- Weighted Precision: 0.954
- Macro Recall: 0.938
- Micro Recall: 0.947
- Weighted Recall: 0.947
TAGS
#transformers #pytorch #swin #image-classification #vision #flags #geography #dataset-dwancin/country-flags #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Country flag classification
This model has been trained on flags from following countries.
- Austria
- Belgium
- Bulgaria
- Croatia
- Czech Republic
- Denmark
- Estonia
- Finland
- France
- Germany
- Greece
- Holland
- Hungary
- Ireland
- Italy
- Latvia
- Lithuania
- Luxembourg
- Malta
- Slovakia
- Slovenia
- South Cyprus
- Spain
- Sweden ## Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 61828134901
- CO2 Emissions (in grams): 0.3887 ## Validation Metrics
- Loss: 0.157
- Accuracy: 0.947
- Macro F1: 0.938
- Micro F1: 0.947
- Weighted F1: 0.946
- Macro Precision: 0.951
- Micro Precision: 0.947
- Weighted Precision: 0.954
- Macro Recall: 0.938
- Micro Recall: 0.947
- Weighted Recall: 0.947