
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 39543103134
- CO2 Emissions (in grams): 1.9112

## Validation Metrics

- Loss: 0.011
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["ppicazo/autotrain-data-astrophotography-object-classifier-alpha3"], "widget": [{"src": "https://astronomy.sfo3.digitaloceanspaces.com/datasets/leo_triplet_19hrs_preview.png", "example_title": "Leo Triplet"}, {"src": "https://astronomy.sfo3.digitaloceanspaces.com/datasets/Cone_Preview.png", "example_title": "Cone Nebula"}, {"src": "https://astronomy.sfo3.digitaloceanspaces.com/datasets/HeartPreview.png", "example_title": "Heart Nebula"}], "co2_eq_emissions": {"emissions": 1.9111577522230074}}
transformers pytorch vit image-classification autotrain vision dataset:ppicazo/autotrain-data-astrophotography-object-classifier-alpha3 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-ppicazo/autotrain-data-astrophotography-object-classifier-alpha3 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 39543103134
- CO2 Emissions (in grams): 1.9112

## Validation Metrics

- Loss: 0.011
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 39543103134
- CO2 Emissions (in grams): 1.9112 ## Validation Metrics

- Loss: 0.011
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-ppicazo/autotrain-data-astrophotography-object-classifier-alpha3 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 39543103134
- CO2 Emissions (in grams): 1.9112 ## Validation Metrics

- Loss: 0.011
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-ppicazo/autotrain-data-astrophotography-object-classifier-alpha3 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 39543103134
- CO2 Emissions (in grams): 1.9112## Validation Metrics

- Loss: 0.011
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000