
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3741499455
- CO2 Emissions (in grams): 6.5539

## Validation Metrics

- Loss: 0.355
- Accuracy: 0.982
- Macro F1: 0.983
- Micro F1: 0.982
- Weighted F1: 0.982
- Macro Precision: 0.983
- Micro Precision: 0.982
- Weighted Precision: 0.983
- Macro Recall: 0.983
- Micro Recall: 0.982
- Weighted Recall: 0.982
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["chaphoto/autotrain-data-test3"], "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": 6.553923974267747}}
transformers pytorch resnet image-classification autotrain vision dataset:chaphoto/autotrain-data-test3 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #resnet #image-classification #autotrain #vision #dataset-chaphoto/autotrain-data-test3 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3741499455
- CO2 Emissions (in grams): 6.5539

## Validation Metrics

- Loss: 0.355
- Accuracy: 0.982
- Macro F1: 0.983
- Micro F1: 0.982
- Weighted F1: 0.982
- Macro Precision: 0.983
- Micro Precision: 0.982
- Weighted Precision: 0.983
- Macro Recall: 0.983
- Micro Recall: 0.982
- Weighted Recall: 0.982
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3741499455
- CO2 Emissions (in grams): 6.5539 ## Validation Metrics

- Loss: 0.355
- Accuracy: 0.982
- Macro F1: 0.983
- Micro F1: 0.982
- Weighted F1: 0.982
- Macro Precision: 0.983
- Micro Precision: 0.982
- Weighted Precision: 0.983
- Macro Recall: 0.983
- Micro Recall: 0.982
- Weighted Recall: 0.982
TAGS
#transformers #pytorch #resnet #image-classification #autotrain #vision #dataset-chaphoto/autotrain-data-test3 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3741499455
- CO2 Emissions (in grams): 6.5539 ## Validation Metrics

- Loss: 0.355
- Accuracy: 0.982
- Macro F1: 0.983
- Micro F1: 0.982
- Weighted F1: 0.982
- Macro Precision: 0.983
- Micro Precision: 0.982
- Weighted Precision: 0.983
- Macro Recall: 0.983
- Micro Recall: 0.982
- Weighted Recall: 0.982