
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48889118357
- CO2 Emissions (in grams): 1.4021

## Validation Metrics

- Loss: 0.038
- Accuracy: 0.986
- Macro F1: 0.977
- Micro F1: 0.986
- Weighted F1: 0.986
- Macro Precision: 0.980
- Micro Precision: 0.986
- Weighted Precision: 0.990
- Macro Recall: 0.982
- Micro Recall: 0.986
- Weighted Recall: 0.986
{"tags": ["autotrain", "vision", "image-classification"], "datasets": ["friesel/autotrain-data-tarkov_images_reduced_i"], "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": 1.402074313856096}}
transformers pytorch vit image-classification autotrain vision dataset:friesel/autotrain-data-tarkov_images_reduced_i co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-friesel/autotrain-data-tarkov_images_reduced_i #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48889118357
- CO2 Emissions (in grams): 1.4021

## Validation Metrics

- Loss: 0.038
- Accuracy: 0.986
- Macro F1: 0.977
- Micro F1: 0.986
- Weighted F1: 0.986
- Macro Precision: 0.980
- Micro Precision: 0.986
- Weighted Precision: 0.990
- Macro Recall: 0.982
- Micro Recall: 0.986
- Weighted Recall: 0.986
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48889118357
- CO2 Emissions (in grams): 1.4021 ## Validation Metrics

- Loss: 0.038
- Accuracy: 0.986
- Macro F1: 0.977
- Micro F1: 0.986
- Weighted F1: 0.986
- Macro Precision: 0.980
- Micro Precision: 0.986
- Weighted Precision: 0.990
- Macro Recall: 0.982
- Micro Recall: 0.986
- Weighted Recall: 0.986
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-friesel/autotrain-data-tarkov_images_reduced_i #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48889118357
- CO2 Emissions (in grams): 1.4021 ## Validation Metrics

- Loss: 0.038
- Accuracy: 0.986
- Macro F1: 0.977
- Micro F1: 0.986
- Weighted F1: 0.986
- Macro Precision: 0.980
- Micro Precision: 0.986
- Weighted Precision: 0.990
- Macro Recall: 0.982
- Micro Recall: 0.986
- Weighted Recall: 0.986
TAGS
#transformers #pytorch #vit #image-classification #autotrain #vision #dataset-friesel/autotrain-data-tarkov_images_reduced_i #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48889118357
- CO2 Emissions (in grams): 1.4021## Validation Metrics

- Loss: 0.038
- Accuracy: 0.986
- Macro F1: 0.977
- Micro F1: 0.986
- Weighted F1: 0.986
- Macro Precision: 0.980
- Micro Precision: 0.986
- Weighted Precision: 0.990
- Macro Recall: 0.982
- Micro Recall: 0.986
- Weighted Recall: 0.986