
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3599096563
- CO2 Emissions (in grams): 4.3848

## Validation Metrics

- Loss: 0.090
- Accuracy: 0.975
- Macro F1: 0.966
- Micro F1: 0.975
- Weighted F1: 0.975
- Macro Precision: 0.966
- Micro Precision: 0.975
- Weighted Precision: 0.975
- Macro Recall: 0.966
- Micro Recall: 0.975
- Weighted Recall: 0.975
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["Dwarni/autotrain-data-ant-image-classification"], "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": 4.384842539782406}}
transformers pytorch swin image-classification autotrain vision dataset:Dwarni/autotrain-data-ant-image-classification co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-Dwarni/autotrain-data-ant-image-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3599096563
- CO2 Emissions (in grams): 4.3848

## Validation Metrics

- Loss: 0.090
- Accuracy: 0.975
- Macro F1: 0.966
- Micro F1: 0.975
- Weighted F1: 0.975
- Macro Precision: 0.966
- Micro Precision: 0.975
- Weighted Precision: 0.975
- Macro Recall: 0.966
- Micro Recall: 0.975
- Weighted Recall: 0.975
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3599096563
- CO2 Emissions (in grams): 4.3848 ## Validation Metrics

- Loss: 0.090
- Accuracy: 0.975
- Macro F1: 0.966
- Micro F1: 0.975
- Weighted F1: 0.975
- Macro Precision: 0.966
- Micro Precision: 0.975
- Weighted Precision: 0.975
- Macro Recall: 0.966
- Micro Recall: 0.975
- Weighted Recall: 0.975
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-Dwarni/autotrain-data-ant-image-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3599096563
- CO2 Emissions (in grams): 4.3848 ## Validation Metrics

- Loss: 0.090
- Accuracy: 0.975
- Macro F1: 0.966
- Micro F1: 0.975
- Weighted F1: 0.975
- Macro Precision: 0.966
- Micro Precision: 0.975
- Weighted Precision: 0.975
- Macro Recall: 0.966
- Micro Recall: 0.975
- Weighted Recall: 0.975