
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2932785109
- CO2 Emissions (in grams): 0.0171

## Validation Metrics

- Loss: 1.241
- Accuracy: 0.372
- Macro F1: 0.228
- Micro F1: 0.372
- Weighted F1: 0.344
- Macro Precision: 0.190
- Micro Precision: 0.372
- Weighted Precision: 0.337
- Macro Recall: 0.355
- Micro Recall: 0.372
- Weighted Recall: 0.372
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["AdamOswald1/autotrain-data-let"], "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": 0.017109641157049823}}
transformers pytorch vit image-classification autotrain vision dataset:AdamOswald1/autotrain-data-let co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-AdamOswald1/autotrain-data-let #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2932785109
- CO2 Emissions (in grams): 0.0171

## Validation Metrics

- Loss: 1.241
- Accuracy: 0.372
- Macro F1: 0.228
- Micro F1: 0.372
- Weighted F1: 0.344
- Macro Precision: 0.190
- Micro Precision: 0.372
- Weighted Precision: 0.337
- Macro Recall: 0.355
- Micro Recall: 0.372
- Weighted Recall: 0.372
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2932785109
- CO2 Emissions (in grams): 0.0171 ## Validation Metrics

- Loss: 1.241
- Accuracy: 0.372
- Macro F1: 0.228
- Micro F1: 0.372
- Weighted F1: 0.344
- Macro Precision: 0.190
- Micro Precision: 0.372
- Weighted Precision: 0.337
- Macro Recall: 0.355
- Micro Recall: 0.372
- Weighted Recall: 0.372
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-AdamOswald1/autotrain-data-let #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2932785109
- CO2 Emissions (in grams): 0.0171 ## Validation Metrics

- Loss: 1.241
- Accuracy: 0.372
- Macro F1: 0.228
- Micro F1: 0.372
- Weighted F1: 0.344
- Macro Precision: 0.190
- Micro Precision: 0.372
- Weighted Precision: 0.337
- Macro Recall: 0.355
- Micro Recall: 0.372
- Weighted Recall: 0.372
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-AdamOswald1/autotrain-data-let #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2932785109
- CO2 Emissions (in grams): 0.0171## Validation Metrics

- Loss: 1.241
- Accuracy: 0.372
- Macro F1: 0.228
- Micro F1: 0.372
- Weighted F1: 0.344
- Macro Precision: 0.190
- Micro Precision: 0.372
- Weighted Precision: 0.337
- Macro Recall: 0.355
- Micro Recall: 0.372
- Weighted Recall: 0.372