
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 50807121085
- CO2 Emissions (in grams): 0.0173

## Validation Metrics

- Loss: 0.039
- Accuracy: 0.973
- Macro F1: 0.971
- Micro F1: 0.973
- Weighted F1: 0.973
- Macro Precision: 0.974
- Micro Precision: 0.973
- Weighted Precision: 0.973
- Macro Recall: 0.968
- Micro Recall: 0.973
- Weighted Recall: 0.973
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["Lakera/autotrain-data-cancer-lakera"], "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": 0.017341401621589574}}
transformers pytorch beit image-classification autotrain vision dataset:Lakera/autotrain-data-cancer-lakera co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-Lakera/autotrain-data-cancer-lakera #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 50807121085
- CO2 Emissions (in grams): 0.0173

## Validation Metrics

- Loss: 0.039
- Accuracy: 0.973
- Macro F1: 0.971
- Micro F1: 0.973
- Weighted F1: 0.973
- Macro Precision: 0.974
- Micro Precision: 0.973
- Weighted Precision: 0.973
- Macro Recall: 0.968
- Micro Recall: 0.973
- Weighted Recall: 0.973
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 50807121085
- CO2 Emissions (in grams): 0.0173 ## Validation Metrics

- Loss: 0.039
- Accuracy: 0.973
- Macro F1: 0.971
- Micro F1: 0.973
- Weighted F1: 0.973
- Macro Precision: 0.974
- Micro Precision: 0.973
- Weighted Precision: 0.973
- Macro Recall: 0.968
- Micro Recall: 0.973
- Weighted Recall: 0.973
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-Lakera/autotrain-data-cancer-lakera #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 50807121085
- CO2 Emissions (in grams): 0.0173 ## Validation Metrics

- Loss: 0.039
- Accuracy: 0.973
- Macro F1: 0.971
- Micro F1: 0.973
- Weighted F1: 0.973
- Macro Precision: 0.974
- Micro Precision: 0.973
- Weighted Precision: 0.973
- Macro Recall: 0.968
- Micro Recall: 0.973
- Weighted Recall: 0.973
TAGS
#transformers #pytorch #beit #image-classification #autotrain #vision #dataset-Lakera/autotrain-data-cancer-lakera #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 50807121085
- CO2 Emissions (in grams): 0.0173## Validation Metrics

- Loss: 0.039
- Accuracy: 0.973
- Macro F1: 0.971
- Micro F1: 0.973
- Weighted F1: 0.973
- Macro Precision: 0.974
- Micro Precision: 0.973
- Weighted Precision: 0.973
- Macro Recall: 0.968
- Micro Recall: 0.973
- Weighted Recall: 0.973