
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2947785378
- CO2 Emissions (in grams): 2.5972

## Validation Metrics

- Loss: 1.470
- Accuracy: 0.408
- Macro F1: 0.261
- Micro F1: 0.408
- Weighted F1: 0.392
- Macro Precision: 0.285
- Micro Precision: 0.408
- Weighted Precision: 0.421
- Macro Recall: 0.266
- Micro Recall: 0.408
- Weighted Recall: 0.408
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["ivensamdh/autotrain-data-convnext_test_masterage"], "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": 2.59724118879757}}
transformers pytorch convnext image-classification autotrain vision dataset:ivensamdh/autotrain-data-convnext_test_masterage co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #convnext #image-classification #autotrain #vision #dataset-ivensamdh/autotrain-data-convnext_test_masterage #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2947785378
- CO2 Emissions (in grams): 2.5972

## Validation Metrics

- Loss: 1.470
- Accuracy: 0.408
- Macro F1: 0.261
- Micro F1: 0.408
- Weighted F1: 0.392
- Macro Precision: 0.285
- Micro Precision: 0.408
- Weighted Precision: 0.421
- Macro Recall: 0.266
- Micro Recall: 0.408
- Weighted Recall: 0.408
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2947785378
- CO2 Emissions (in grams): 2.5972 ## Validation Metrics

- Loss: 1.470
- Accuracy: 0.408
- Macro F1: 0.261
- Micro F1: 0.408
- Weighted F1: 0.392
- Macro Precision: 0.285
- Micro Precision: 0.408
- Weighted Precision: 0.421
- Macro Recall: 0.266
- Micro Recall: 0.408
- Weighted Recall: 0.408
TAGS
#transformers #pytorch #convnext #image-classification #autotrain #vision #dataset-ivensamdh/autotrain-data-convnext_test_masterage #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2947785378
- CO2 Emissions (in grams): 2.5972 ## Validation Metrics

- Loss: 1.470
- Accuracy: 0.408
- Macro F1: 0.261
- Micro F1: 0.408
- Weighted F1: 0.392
- Macro Precision: 0.285
- Micro Precision: 0.408
- Weighted Precision: 0.421
- Macro Recall: 0.266
- Micro Recall: 0.408
- Weighted Recall: 0.408
TAGS
#transformers #pytorch #convnext #image-classification #autotrain #vision #dataset-ivensamdh/autotrain-data-convnext_test_masterage #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2947785378
- CO2 Emissions (in grams): 2.5972## Validation Metrics

- Loss: 1.470
- Accuracy: 0.408
- Macro F1: 0.261
- Micro F1: 0.408
- Weighted F1: 0.392
- Macro Precision: 0.285
- Micro Precision: 0.408
- Weighted Precision: 0.421
- Macro Recall: 0.266
- Micro Recall: 0.408
- Weighted Recall: 0.408