
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 50807121083
- CO2 Emissions (in grams): 2.4235

## Validation Metrics

- Loss: 0.999
- Accuracy: 0.507
- Macro F1: 0.347
- Micro F1: 0.507
- Weighted F1: 0.397
- Macro Precision: 0.626
- Micro Precision: 0.507
- Weighted Precision: 0.600
- Macro Recall: 0.409
- Micro Recall: 0.507
- Weighted Recall: 0.507
{"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": 2.4235157312621385}}
transformers pytorch resnet image-classification autotrain vision dataset:Lakera/autotrain-data-cancer-lakera co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #resnet #image-classification #autotrain #vision #dataset-Lakera/autotrain-data-cancer-lakera #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 50807121083
- CO2 Emissions (in grams): 2.4235

## Validation Metrics

- Loss: 0.999
- Accuracy: 0.507
- Macro F1: 0.347
- Micro F1: 0.507
- Weighted F1: 0.397
- Macro Precision: 0.626
- Micro Precision: 0.507
- Weighted Precision: 0.600
- Macro Recall: 0.409
- Micro Recall: 0.507
- Weighted Recall: 0.507
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 50807121083
- CO2 Emissions (in grams): 2.4235 ## Validation Metrics

- Loss: 0.999
- Accuracy: 0.507
- Macro F1: 0.347
- Micro F1: 0.507
- Weighted F1: 0.397
- Macro Precision: 0.626
- Micro Precision: 0.507
- Weighted Precision: 0.600
- Macro Recall: 0.409
- Micro Recall: 0.507
- Weighted Recall: 0.507
TAGS
#transformers #pytorch #resnet #image-classification #autotrain #vision #dataset-Lakera/autotrain-data-cancer-lakera #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 50807121083
- CO2 Emissions (in grams): 2.4235 ## Validation Metrics

- Loss: 0.999
- Accuracy: 0.507
- Macro F1: 0.347
- Micro F1: 0.507
- Weighted F1: 0.397
- Macro Precision: 0.626
- Micro Precision: 0.507
- Weighted Precision: 0.600
- Macro Recall: 0.409
- Micro Recall: 0.507
- Weighted Recall: 0.507
TAGS
#transformers #pytorch #resnet #image-classification #autotrain #vision #dataset-Lakera/autotrain-data-cancer-lakera #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 50807121083
- CO2 Emissions (in grams): 2.4235## Validation Metrics

- Loss: 0.999
- Accuracy: 0.507
- Macro F1: 0.347
- Micro F1: 0.507
- Weighted F1: 0.397
- Macro Precision: 0.626
- Micro Precision: 0.507
- Weighted Precision: 0.600
- Macro Recall: 0.409
- Micro Recall: 0.507
- Weighted Recall: 0.507