
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3341092265
- CO2 Emissions (in grams): 2.6501

## Validation Metrics

- Loss: 0.133
- Accuracy: 0.950
- Macro F1: 0.951
- Micro F1: 0.950
- Weighted F1: 0.950
- Macro Precision: 0.951
- Micro Precision: 0.950
- Weighted Precision: 0.950
- Macro Recall: 0.951
- Micro Recall: 0.950
- Weighted Recall: 0.950
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["Ailyth/autotrain-data-3lables"], "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": 2.650072914067399}}
transformers pytorch swin image-classification autotrain vision dataset:Ailyth/autotrain-data-3lables co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-Ailyth/autotrain-data-3lables #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3341092265
- CO2 Emissions (in grams): 2.6501

## Validation Metrics

- Loss: 0.133
- Accuracy: 0.950
- Macro F1: 0.951
- Micro F1: 0.950
- Weighted F1: 0.950
- Macro Precision: 0.951
- Micro Precision: 0.950
- Weighted Precision: 0.950
- Macro Recall: 0.951
- Micro Recall: 0.950
- Weighted Recall: 0.950
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3341092265
- CO2 Emissions (in grams): 2.6501 ## Validation Metrics

- Loss: 0.133
- Accuracy: 0.950
- Macro F1: 0.951
- Micro F1: 0.950
- Weighted F1: 0.950
- Macro Precision: 0.951
- Micro Precision: 0.950
- Weighted Precision: 0.950
- Macro Recall: 0.951
- Micro Recall: 0.950
- Weighted Recall: 0.950
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-Ailyth/autotrain-data-3lables #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3341092265
- CO2 Emissions (in grams): 2.6501 ## Validation Metrics

- Loss: 0.133
- Accuracy: 0.950
- Macro F1: 0.951
- Micro F1: 0.950
- Weighted F1: 0.950
- Macro Precision: 0.951
- Micro Precision: 0.950
- Weighted Precision: 0.950
- Macro Recall: 0.951
- Micro Recall: 0.950
- Weighted Recall: 0.950
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-Ailyth/autotrain-data-3lables #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3341092265
- CO2 Emissions (in grams): 2.6501## Validation Metrics

- Loss: 0.133
- Accuracy: 0.950
- Macro F1: 0.951
- Micro F1: 0.950
- Weighted F1: 0.950
- Macro Precision: 0.951
- Micro Precision: 0.950
- Weighted Precision: 0.950
- Macro Recall: 0.951
- Micro Recall: 0.950
- Weighted Recall: 0.950