

## Validation Metrics

- Loss: 0.001
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000
{"tags": ["vision", "image-classification"], "widget": [{"src": "https://cf.shopee.co.id/file/395eda08423ea6bc13274abc3dad44c6", "example_title": "Bagus"}, {"src": "https://cdn.pixabay.com/photo/2017/03/15/18/06/lemon-2146987_1280.jpg", "example_title": "Tidak Bagus"}], "co2_eq_emissions": {"emissions": 2.02289641653325}}
transformers pytorch swin image-classification vision co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #vision #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 



## Validation Metrics

- Loss: 0.001
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000
## Validation Metrics

- Loss: 0.001
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000
TAGS
#transformers #pytorch #swin #image-classification #vision #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 ## Validation Metrics

- Loss: 0.001
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000
TAGS
#transformers #pytorch #swin #image-classification #vision #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
## Validation Metrics

- Loss: 0.001
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000