
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 41243106351
- CO2 Emissions (in grams): 1.3811

## Validation Metrics

- Loss: 0.161
- Accuracy: 0.936
- Macro F1: 0.936
- Micro F1: 0.936
- Weighted F1: 0.936
- Macro Precision: 0.936
- Micro Precision: 0.936
- Weighted Precision: 0.936
- Macro Recall: 0.936
- Micro Recall: 0.936
- Weighted Recall: 0.936
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["mouss/autotrain-data-bikes-ag"], "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": 1.381064904462668}}
transformers pytorch swin image-classification autotrain vision dataset:mouss/autotrain-data-bikes-ag co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-mouss/autotrain-data-bikes-ag #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 41243106351
- CO2 Emissions (in grams): 1.3811

## Validation Metrics

- Loss: 0.161
- Accuracy: 0.936
- Macro F1: 0.936
- Micro F1: 0.936
- Weighted F1: 0.936
- Macro Precision: 0.936
- Micro Precision: 0.936
- Weighted Precision: 0.936
- Macro Recall: 0.936
- Micro Recall: 0.936
- Weighted Recall: 0.936
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 41243106351
- CO2 Emissions (in grams): 1.3811 ## Validation Metrics

- Loss: 0.161
- Accuracy: 0.936
- Macro F1: 0.936
- Micro F1: 0.936
- Weighted F1: 0.936
- Macro Precision: 0.936
- Micro Precision: 0.936
- Weighted Precision: 0.936
- Macro Recall: 0.936
- Micro Recall: 0.936
- Weighted Recall: 0.936
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-mouss/autotrain-data-bikes-ag #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 41243106351
- CO2 Emissions (in grams): 1.3811 ## Validation Metrics

- Loss: 0.161
- Accuracy: 0.936
- Macro F1: 0.936
- Micro F1: 0.936
- Weighted F1: 0.936
- Macro Precision: 0.936
- Micro Precision: 0.936
- Weighted Precision: 0.936
- Macro Recall: 0.936
- Micro Recall: 0.936
- Weighted Recall: 0.936
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-mouss/autotrain-data-bikes-ag #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 41243106351
- CO2 Emissions (in grams): 1.3811## Validation Metrics

- Loss: 0.161
- Accuracy: 0.936
- Macro F1: 0.936
- Micro F1: 0.936
- Weighted F1: 0.936
- Macro Precision: 0.936
- Micro Precision: 0.936
- Weighted Precision: 0.936
- Macro Recall: 0.936
- Micro Recall: 0.936
- Weighted Recall: 0.936