
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3716799077
- CO2 Emissions (in grams): 4.6334

## Validation Metrics

- Loss: 0.777
- Accuracy: 0.762
- Macro F1: 0.740
- Micro F1: 0.762
- Weighted F1: 0.742
- Macro Precision: 0.754
- Micro Precision: 0.762
- Weighted Precision: 0.754
- Macro Recall: 0.758
- Micro Recall: 0.762
- Weighted Recall: 0.762
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["lineups-io/autotrain-data-multifamily"], "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": 4.633385512099204}}
transformers pytorch swin image-classification autotrain vision dataset:lineups-io/autotrain-data-multifamily co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-lineups-io/autotrain-data-multifamily #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3716799077
- CO2 Emissions (in grams): 4.6334

## Validation Metrics

- Loss: 0.777
- Accuracy: 0.762
- Macro F1: 0.740
- Micro F1: 0.762
- Weighted F1: 0.742
- Macro Precision: 0.754
- Micro Precision: 0.762
- Weighted Precision: 0.754
- Macro Recall: 0.758
- Micro Recall: 0.762
- Weighted Recall: 0.762
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3716799077
- CO2 Emissions (in grams): 4.6334 ## Validation Metrics

- Loss: 0.777
- Accuracy: 0.762
- Macro F1: 0.740
- Micro F1: 0.762
- Weighted F1: 0.742
- Macro Precision: 0.754
- Micro Precision: 0.762
- Weighted Precision: 0.754
- Macro Recall: 0.758
- Micro Recall: 0.762
- Weighted Recall: 0.762
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-lineups-io/autotrain-data-multifamily #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3716799077
- CO2 Emissions (in grams): 4.6334 ## Validation Metrics

- Loss: 0.777
- Accuracy: 0.762
- Macro F1: 0.740
- Micro F1: 0.762
- Weighted F1: 0.742
- Macro Precision: 0.754
- Micro Precision: 0.762
- Weighted Precision: 0.754
- Macro Recall: 0.758
- Micro Recall: 0.762
- Weighted Recall: 0.762
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-lineups-io/autotrain-data-multifamily #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3716799077
- CO2 Emissions (in grams): 4.6334## Validation Metrics

- Loss: 0.777
- Accuracy: 0.762
- Macro F1: 0.740
- Micro F1: 0.762
- Weighted F1: 0.742
- Macro Precision: 0.754
- Micro Precision: 0.762
- Weighted Precision: 0.754
- Macro Recall: 0.758
- Micro Recall: 0.762
- Weighted Recall: 0.762