
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1433953639
- CO2 Emissions (in grams): 0.0117

## Validation Metrics

- Loss: 0.606
- Accuracy: 0.880
- Macro F1: 0.844
- Micro F1: 0.880
- Weighted F1: 0.844
- Macro Precision: 0.827
- Micro Precision: 0.880
- Weighted Precision: 0.827
- Macro Recall: 0.880
- Micro Recall: 0.880
- Weighted Recall: 0.880
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["NimaBoscarino/autotrain-data-temp-nima"], "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": 0.01165947148172322}}
transformers pytorch autotrain vision image-classification dataset:NimaBoscarino/autotrain-data-temp-nima co2_eq_emissions endpoints_compatible region:us
TAGS
#transformers #pytorch #autotrain #vision #image-classification #dataset-NimaBoscarino/autotrain-data-temp-nima #co2_eq_emissions #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1433953639
- CO2 Emissions (in grams): 0.0117

## Validation Metrics

- Loss: 0.606
- Accuracy: 0.880
- Macro F1: 0.844
- Micro F1: 0.880
- Weighted F1: 0.844
- Macro Precision: 0.827
- Micro Precision: 0.880
- Weighted Precision: 0.827
- Macro Recall: 0.880
- Micro Recall: 0.880
- Weighted Recall: 0.880
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1433953639
- CO2 Emissions (in grams): 0.0117 ## Validation Metrics

- Loss: 0.606
- Accuracy: 0.880
- Macro F1: 0.844
- Micro F1: 0.880
- Weighted F1: 0.844
- Macro Precision: 0.827
- Micro Precision: 0.880
- Weighted Precision: 0.827
- Macro Recall: 0.880
- Micro Recall: 0.880
- Weighted Recall: 0.880
TAGS
#transformers #pytorch #autotrain #vision #image-classification #dataset-NimaBoscarino/autotrain-data-temp-nima #co2_eq_emissions #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1433953639
- CO2 Emissions (in grams): 0.0117 ## Validation Metrics

- Loss: 0.606
- Accuracy: 0.880
- Macro F1: 0.844
- Micro F1: 0.880
- Weighted F1: 0.844
- Macro Precision: 0.827
- Micro Precision: 0.880
- Weighted Precision: 0.827
- Macro Recall: 0.880
- Micro Recall: 0.880
- Weighted Recall: 0.880
passage: TAGS
#transformers #pytorch #autotrain #vision #image-classification #dataset-NimaBoscarino/autotrain-data-temp-nima #co2_eq_emissions #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1433953639
- CO2 Emissions (in grams): 0.0117## Validation Metrics

- Loss: 0.606
- Accuracy: 0.880
- Macro F1: 0.844
- Micro F1: 0.880
- Weighted F1: 0.844
- Macro Precision: 0.827
- Micro Precision: 0.880
- Weighted Precision: 0.827
- Macro Recall: 0.880
- Micro Recall: 0.880
- Weighted Recall: 0.880