
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44246111624
- CO2 Emissions (in grams): 0.3630

## Validation Metrics

- Loss: 1.413
- Accuracy: 0.400
- Macro F1: 0.375
- Micro F1: 0.400
- Weighted F1: 0.400
- Macro Precision: 0.375
- Micro Precision: 0.400
- Weighted Precision: 0.400
- Macro Recall: 0.375
- Micro Recall: 0.400
- Weighted Recall: 0.400
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["SebasV/autotrain-data-tableros_factibilidad"], "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": 0.36296304345687347}}
transformers pytorch beit image-classification autotrain vision dataset:SebasV/autotrain-data-tableros_factibilidad co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-SebasV/autotrain-data-tableros_factibilidad #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44246111624
- CO2 Emissions (in grams): 0.3630

## Validation Metrics

- Loss: 1.413
- Accuracy: 0.400
- Macro F1: 0.375
- Micro F1: 0.400
- Weighted F1: 0.400
- Macro Precision: 0.375
- Micro Precision: 0.400
- Weighted Precision: 0.400
- Macro Recall: 0.375
- Micro Recall: 0.400
- Weighted Recall: 0.400
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44246111624
- CO2 Emissions (in grams): 0.3630 ## Validation Metrics

- Loss: 1.413
- Accuracy: 0.400
- Macro F1: 0.375
- Micro F1: 0.400
- Weighted F1: 0.400
- Macro Precision: 0.375
- Micro Precision: 0.400
- Weighted Precision: 0.400
- Macro Recall: 0.375
- Micro Recall: 0.400
- Weighted Recall: 0.400
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-SebasV/autotrain-data-tableros_factibilidad #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44246111624
- CO2 Emissions (in grams): 0.3630 ## Validation Metrics

- Loss: 1.413
- Accuracy: 0.400
- Macro F1: 0.375
- Micro F1: 0.400
- Weighted F1: 0.400
- Macro Precision: 0.375
- Micro Precision: 0.400
- Weighted Precision: 0.400
- Macro Recall: 0.375
- Micro Recall: 0.400
- Weighted Recall: 0.400
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-SebasV/autotrain-data-tableros_factibilidad #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44246111624
- CO2 Emissions (in grams): 0.3630## Validation Metrics

- Loss: 1.413
- Accuracy: 0.400
- Macro F1: 0.375
- Micro F1: 0.400
- Weighted F1: 0.400
- Macro Precision: 0.375
- Micro Precision: 0.400
- Weighted Precision: 0.400
- Macro Recall: 0.375
- Micro Recall: 0.400
- Weighted Recall: 0.400