
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 43390110454
- CO2 Emissions (in grams): 3.4952

## Validation Metrics

- Loss: 0.750
- Accuracy: 0.751
- Macro F1: 0.678
- Micro F1: 0.751
- Weighted F1: 0.746
- Macro Precision: 0.726
- Micro Precision: 0.751
- Weighted Precision: 0.753
- Macro Recall: 0.665
- Micro Recall: 0.751
- Weighted Recall: 0.751
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["Rickyfwh/autotrain-data-js-classfication-test-2"], "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": 3.495241141356263}}
transformers pytorch swin image-classification autotrain vision dataset:Rickyfwh/autotrain-data-js-classfication-test-2 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-Rickyfwh/autotrain-data-js-classfication-test-2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 43390110454
- CO2 Emissions (in grams): 3.4952

## Validation Metrics

- Loss: 0.750
- Accuracy: 0.751
- Macro F1: 0.678
- Micro F1: 0.751
- Weighted F1: 0.746
- Macro Precision: 0.726
- Micro Precision: 0.751
- Weighted Precision: 0.753
- Macro Recall: 0.665
- Micro Recall: 0.751
- Weighted Recall: 0.751
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 43390110454
- CO2 Emissions (in grams): 3.4952 ## Validation Metrics

- Loss: 0.750
- Accuracy: 0.751
- Macro F1: 0.678
- Micro F1: 0.751
- Weighted F1: 0.746
- Macro Precision: 0.726
- Micro Precision: 0.751
- Weighted Precision: 0.753
- Macro Recall: 0.665
- Micro Recall: 0.751
- Weighted Recall: 0.751
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-Rickyfwh/autotrain-data-js-classfication-test-2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 43390110454
- CO2 Emissions (in grams): 3.4952 ## Validation Metrics

- Loss: 0.750
- Accuracy: 0.751
- Macro F1: 0.678
- Micro F1: 0.751
- Weighted F1: 0.746
- Macro Precision: 0.726
- Micro Precision: 0.751
- Weighted Precision: 0.753
- Macro Recall: 0.665
- Micro Recall: 0.751
- Weighted Recall: 0.751
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #dataset-Rickyfwh/autotrain-data-js-classfication-test-2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 43390110454
- CO2 Emissions (in grams): 3.4952## Validation Metrics

- Loss: 0.750
- Accuracy: 0.751
- Macro F1: 0.678
- Micro F1: 0.751
- Weighted F1: 0.746
- Macro Precision: 0.726
- Micro Precision: 0.751
- Weighted Precision: 0.753
- Macro Recall: 0.665
- Micro Recall: 0.751
- Weighted Recall: 0.751