
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 39701103400
- CO2 Emissions (in grams): 0.0010

## Validation Metrics

- Loss: 0.137
- Accuracy: 0.947
- Precision: 1.000
- Recall: 0.923
- AUC: 1.000
- F1: 0.960
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["davanstrien/autotrain-data-map_no_map_twitter_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": 0.0009796683022820969}}
transformers pytorch swin image-classification autotrain vision dataset:davanstrien/autotrain-data-map_no_map_twitter_demo co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-davanstrien/autotrain-data-map_no_map_twitter_demo #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 39701103400
- CO2 Emissions (in grams): 0.0010

## Validation Metrics

- Loss: 0.137
- Accuracy: 0.947
- Precision: 1.000
- Recall: 0.923
- AUC: 1.000
- F1: 0.960
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 39701103400
- CO2 Emissions (in grams): 0.0010 ## Validation Metrics

- Loss: 0.137
- Accuracy: 0.947
- Precision: 1.000
- Recall: 0.923
- AUC: 1.000
- F1: 0.960
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-davanstrien/autotrain-data-map_no_map_twitter_demo #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 39701103400
- CO2 Emissions (in grams): 0.0010 ## Validation Metrics

- Loss: 0.137
- Accuracy: 0.947
- Precision: 1.000
- Recall: 0.923
- AUC: 1.000
- F1: 0.960
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-davanstrien/autotrain-data-map_no_map_twitter_demo #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 39701103400
- CO2 Emissions (in grams): 0.0010## Validation Metrics

- Loss: 0.137
- Accuracy: 0.947
- Precision: 1.000
- Recall: 0.923
- AUC: 1.000
- F1: 0.960