
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1436353679
- CO2 Emissions (in grams): 2.4820
- Currently,The model has been trained to recognize o ly the following species:
-Sergal
-Protogen
-Wolf
-Fox
-Synth
-Shark
-Dragon

Works best if submitted image's background isn't plain black/transparent

## Validation Metrics

- Loss: 0.302
- Accuracy: 0.896
- Macro F1: 0.895
- Micro F1: 0.896
- Weighted F1: 0.897
- Macro Precision: 0.900
- Micro Precision: 0.896
- Weighted Precision: 0.908
- Macro Recall: 0.900
- Micro Recall: 0.896
- Weighted Recall: 0.896
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["MommySernox/autotrain-data-furrygendataset"], "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": 2.482027438387914}}
transformers pytorch autotrain vision image-classification dataset:MommySernox/autotrain-data-furrygendataset co2_eq_emissions endpoints_compatible region:us
TAGS
#transformers #pytorch #autotrain #vision #image-classification #dataset-MommySernox/autotrain-data-furrygendataset #co2_eq_emissions #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1436353679
- CO2 Emissions (in grams): 2.4820
- Currently,The model has been trained to recognize o ly the following species:
-Sergal
-Protogen
-Wolf
-Fox
-Synth
-Shark
-Dragon

Works best if submitted image's background isn't plain black/transparent

## Validation Metrics

- Loss: 0.302
- Accuracy: 0.896
- Macro F1: 0.895
- Micro F1: 0.896
- Weighted F1: 0.897
- Macro Precision: 0.900
- Micro Precision: 0.896
- Weighted Precision: 0.908
- Macro Recall: 0.900
- Micro Recall: 0.896
- Weighted Recall: 0.896
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1436353679
- CO2 Emissions (in grams): 2.4820
- Currently,The model has been trained to recognize o ly the following species:
-Sergal
-Protogen
-Wolf
-Fox
-Synth
-Shark
-Dragon

Works best if submitted image's background isn't plain black/transparent ## Validation Metrics

- Loss: 0.302
- Accuracy: 0.896
- Macro F1: 0.895
- Micro F1: 0.896
- Weighted F1: 0.897
- Macro Precision: 0.900
- Micro Precision: 0.896
- Weighted Precision: 0.908
- Macro Recall: 0.900
- Micro Recall: 0.896
- Weighted Recall: 0.896
TAGS
#transformers #pytorch #autotrain #vision #image-classification #dataset-MommySernox/autotrain-data-furrygendataset #co2_eq_emissions #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1436353679
- CO2 Emissions (in grams): 2.4820
- Currently,The model has been trained to recognize o ly the following species:
-Sergal
-Protogen
-Wolf
-Fox
-Synth
-Shark
-Dragon

Works best if submitted image's background isn't plain black/transparent ## Validation Metrics

- Loss: 0.302
- Accuracy: 0.896
- Macro F1: 0.895
- Micro F1: 0.896
- Weighted F1: 0.897
- Macro Precision: 0.900
- Micro Precision: 0.896
- Weighted Precision: 0.908
- Macro Recall: 0.900
- Micro Recall: 0.896
- Weighted Recall: 0.896
passage: TAGS
#transformers #pytorch #autotrain #vision #image-classification #dataset-MommySernox/autotrain-data-furrygendataset #co2_eq_emissions #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1436353679
- CO2 Emissions (in grams): 2.4820
- Currently,The model has been trained to recognize o ly the following species:
-Sergal
-Protogen
-Wolf
-Fox
-Synth
-Shark
-Dragon

Works best if submitted image's background isn't plain black/transparent## Validation Metrics

- Loss: 0.302
- Accuracy: 0.896
- Macro F1: 0.895
- Micro F1: 0.896
- Weighted F1: 0.897
- Macro Precision: 0.900
- Micro Precision: 0.896
- Weighted Precision: 0.908
- Macro Recall: 0.900
- Micro Recall: 0.896
- Weighted Recall: 0.896