
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44246111622
- CO2 Emissions (in grams): 0.1825

## Validation Metrics

- Loss: 1.397
- Accuracy: 0.200
- Macro F1: 0.100
- Micro F1: 0.200
- Weighted F1: 0.080
- Macro Precision: 0.062
- Micro Precision: 0.200
- Weighted Precision: 0.050
- Macro Recall: 0.250
- Micro Recall: 0.200
- Weighted Recall: 0.200
{"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": 0.18253460390372658}}
transformers pytorch resnet image-classification autotrain vision dataset:SebasV/autotrain-data-tableros_factibilidad co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #resnet #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: 44246111622
- CO2 Emissions (in grams): 0.1825

## Validation Metrics

- Loss: 1.397
- Accuracy: 0.200
- Macro F1: 0.100
- Micro F1: 0.200
- Weighted F1: 0.080
- Macro Precision: 0.062
- Micro Precision: 0.200
- Weighted Precision: 0.050
- Macro Recall: 0.250
- Micro Recall: 0.200
- Weighted Recall: 0.200
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 44246111622
- CO2 Emissions (in grams): 0.1825 ## Validation Metrics

- Loss: 1.397
- Accuracy: 0.200
- Macro F1: 0.100
- Micro F1: 0.200
- Weighted F1: 0.080
- Macro Precision: 0.062
- Micro Precision: 0.200
- Weighted Precision: 0.050
- Macro Recall: 0.250
- Micro Recall: 0.200
- Weighted Recall: 0.200
TAGS
#transformers #pytorch #resnet #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: 44246111622
- CO2 Emissions (in grams): 0.1825 ## Validation Metrics

- Loss: 1.397
- Accuracy: 0.200
- Macro F1: 0.100
- Micro F1: 0.200
- Weighted F1: 0.080
- Macro Precision: 0.062
- Micro Precision: 0.200
- Weighted Precision: 0.050
- Macro Recall: 0.250
- Micro Recall: 0.200
- Weighted Recall: 0.200
TAGS
#transformers #pytorch #resnet #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: 44246111622
- CO2 Emissions (in grams): 0.1825## Validation Metrics

- Loss: 1.397
- Accuracy: 0.200
- Macro F1: 0.100
- Micro F1: 0.200
- Weighted F1: 0.080
- Macro Precision: 0.062
- Micro Precision: 0.200
- Weighted Precision: 0.050
- Macro Recall: 0.250
- Micro Recall: 0.200
- Weighted Recall: 0.200