
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 41086106044
- CO2 Emissions (in grams): 0.1871

## Validation Metrics

- Loss: 1.110
- Accuracy: 0.100
- Macro F1: 0.074
- Micro F1: 0.100
- Weighted F1: 0.111
- Macro Precision: 0.083
- Micro Precision: 0.100
- Weighted Precision: 0.125
- Macro Recall: 0.067
- Micro Recall: 0.100
- Weighted Recall: 0.100
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["Younesao/autotrain-data-test"], "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": 0.18712822898352202}}
transformers pytorch resnet image-classification autotrain vision dataset:Younesao/autotrain-data-test co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #resnet #image-classification #autotrain #vision #dataset-Younesao/autotrain-data-test #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 41086106044
- CO2 Emissions (in grams): 0.1871

## Validation Metrics

- Loss: 1.110
- Accuracy: 0.100
- Macro F1: 0.074
- Micro F1: 0.100
- Weighted F1: 0.111
- Macro Precision: 0.083
- Micro Precision: 0.100
- Weighted Precision: 0.125
- Macro Recall: 0.067
- Micro Recall: 0.100
- Weighted Recall: 0.100
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 41086106044
- CO2 Emissions (in grams): 0.1871 ## Validation Metrics

- Loss: 1.110
- Accuracy: 0.100
- Macro F1: 0.074
- Micro F1: 0.100
- Weighted F1: 0.111
- Macro Precision: 0.083
- Micro Precision: 0.100
- Weighted Precision: 0.125
- Macro Recall: 0.067
- Micro Recall: 0.100
- Weighted Recall: 0.100
TAGS
#transformers #pytorch #resnet #image-classification #autotrain #vision #dataset-Younesao/autotrain-data-test #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 41086106044
- CO2 Emissions (in grams): 0.1871 ## Validation Metrics

- Loss: 1.110
- Accuracy: 0.100
- Macro F1: 0.074
- Micro F1: 0.100
- Weighted F1: 0.111
- Macro Precision: 0.083
- Micro Precision: 0.100
- Weighted Precision: 0.125
- Macro Recall: 0.067
- Micro Recall: 0.100
- Weighted Recall: 0.100
TAGS
#transformers #pytorch #resnet #image-classification #autotrain #vision #dataset-Younesao/autotrain-data-test #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 41086106044
- CO2 Emissions (in grams): 0.1871## Validation Metrics

- Loss: 1.110
- Accuracy: 0.100
- Macro F1: 0.074
- Micro F1: 0.100
- Weighted F1: 0.111
- Macro Precision: 0.083
- Micro Precision: 0.100
- Weighted Precision: 0.125
- Macro Recall: 0.067
- Micro Recall: 0.100
- Weighted Recall: 0.100