
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 38061100888
- CO2 Emissions (in grams): 0.0038

## Validation Metrics

- Loss: 0.017
- Accuracy: 0.990
- Macro F1: 0.990
- Micro F1: 0.990
- Weighted F1: 0.990
- Macro Precision: 0.990
- Micro Precision: 0.990
- Weighted Precision: 0.990
- Macro Recall: 0.990
- Micro Recall: 0.990
- Weighted Recall: 0.990
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["omarques/autotrain-data-flower-classifier-6"], "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": 0.0038337670741491253}}
transformers pytorch beit image-classification autotrain vision dataset:omarques/autotrain-data-flower-classifier-6 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-omarques/autotrain-data-flower-classifier-6 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 38061100888
- CO2 Emissions (in grams): 0.0038

## Validation Metrics

- Loss: 0.017
- Accuracy: 0.990
- Macro F1: 0.990
- Micro F1: 0.990
- Weighted F1: 0.990
- Macro Precision: 0.990
- Micro Precision: 0.990
- Weighted Precision: 0.990
- Macro Recall: 0.990
- Micro Recall: 0.990
- Weighted Recall: 0.990
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 38061100888
- CO2 Emissions (in grams): 0.0038 ## Validation Metrics

- Loss: 0.017
- Accuracy: 0.990
- Macro F1: 0.990
- Micro F1: 0.990
- Weighted F1: 0.990
- Macro Precision: 0.990
- Micro Precision: 0.990
- Weighted Precision: 0.990
- Macro Recall: 0.990
- Micro Recall: 0.990
- Weighted Recall: 0.990
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-omarques/autotrain-data-flower-classifier-6 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 38061100888
- CO2 Emissions (in grams): 0.0038 ## Validation Metrics

- Loss: 0.017
- Accuracy: 0.990
- Macro F1: 0.990
- Micro F1: 0.990
- Weighted F1: 0.990
- Macro Precision: 0.990
- Micro Precision: 0.990
- Weighted Precision: 0.990
- Macro Recall: 0.990
- Micro Recall: 0.990
- Weighted Recall: 0.990