
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 300303
- CO2 Emissions (in grams): 32.869648157119876

## Validation Metrics

- Loss: 0.05070499703288078
- Accuracy: 0.9834
- Macro F1: 0.9834026834840477
- Micro F1: 0.9834
- Weighted F1: 0.9834026834840479
- Macro Precision: 0.9834502145172822
- Micro Precision: 0.9834
- Weighted Precision: 0.9834502145172822
- Macro Recall: 0.9833999999999999
- Micro Recall: 0.9834
- Weighted Recall: 0.9834
{"tags": "autotrain", "datasets": ["abhishek/autotrain-data-vision_79ca848474e24ad3a520c09e36452e85", "cifar10"], "co2_eq_emissions": 32.869648157119876, "model-index": [{"name": "autotrain_cifar10_vit_base", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "cifar10", "type": "cifar10"}, "metrics": [{"type": "accuracy", "value": 0.9834, "name": "Accuracy"}]}, {"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "cifar10", "type": "cifar10", "config": "plain_text", "split": "test"}, "metrics": [{"type": "accuracy", "value": 0.9811, "name": "Accuracy", "verified": true}, {"type": "precision", "value": 0.9812371727477451, "name": "Precision Macro", "verified": true}, {"type": "precision", "value": 0.9811, "name": "Precision Micro", "verified": true}, {"type": "precision", "value": 0.9812371727477451, "name": "Precision Weighted", "verified": true}, {"type": "recall", "value": 0.9811, "name": "Recall Macro", "verified": true}, {"type": "recall", "value": 0.9811, "name": "Recall Micro", "verified": true}, {"type": "recall", "value": 0.9811, "name": "Recall Weighted", "verified": true}, {"type": "f1", "value": 0.9811240087824231, "name": "F1 Macro", "verified": true}, {"type": "f1", "value": 0.9811, "name": "F1 Micro", "verified": true}, {"type": "f1", "value": 0.981124008782423, "name": "F1 Weighted", "verified": true}, {"type": "loss", "value": 0.0649944543838501, "name": "loss", "verified": true}]}]}]}
transformers pytorch vit image-classification autotrain dataset:abhishek/autotrain-data-vision_79ca848474e24ad3a520c09e36452e85 dataset:cifar10 model-index co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #image-classification #autotrain #dataset-abhishek/autotrain-data-vision_79ca848474e24ad3a520c09e36452e85 #dataset-cifar10 #model-index #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 300303
- CO2 Emissions (in grams): 32.869648157119876

## Validation Metrics

- Loss: 0.05070499703288078
- Accuracy: 0.9834
- Macro F1: 0.9834026834840477
- Micro F1: 0.9834
- Weighted F1: 0.9834026834840479
- Macro Precision: 0.9834502145172822
- Micro Precision: 0.9834
- Weighted Precision: 0.9834502145172822
- Macro Recall: 0.9833999999999999
- Micro Recall: 0.9834
- Weighted Recall: 0.9834
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 300303
- CO2 Emissions (in grams): 32.869648157119876 ## Validation Metrics

- Loss: 0.05070499703288078
- Accuracy: 0.9834
- Macro F1: 0.9834026834840477
- Micro F1: 0.9834
- Weighted F1: 0.9834026834840479
- Macro Precision: 0.9834502145172822
- Micro Precision: 0.9834
- Weighted Precision: 0.9834502145172822
- Macro Recall: 0.9833999999999999
- Micro Recall: 0.9834
- Weighted Recall: 0.9834
TAGS
#transformers #pytorch #vit #image-classification #autotrain #dataset-abhishek/autotrain-data-vision_79ca848474e24ad3a520c09e36452e85 #dataset-cifar10 #model-index #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 300303
- CO2 Emissions (in grams): 32.869648157119876 ## Validation Metrics

- Loss: 0.05070499703288078
- Accuracy: 0.9834
- Macro F1: 0.9834026834840477
- Micro F1: 0.9834
- Weighted F1: 0.9834026834840479
- Macro Precision: 0.9834502145172822
- Micro Precision: 0.9834
- Weighted Precision: 0.9834502145172822
- Macro Recall: 0.9833999999999999
- Micro Recall: 0.9834
- Weighted Recall: 0.9834
passage: TAGS
#transformers #pytorch #vit #image-classification #autotrain #dataset-abhishek/autotrain-data-vision_79ca848474e24ad3a520c09e36452e85 #dataset-cifar10 #model-index #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 300303
- CO2 Emissions (in grams): 32.869648157119876## Validation Metrics

- Loss: 0.05070499703288078
- Accuracy: 0.9834
- Macro F1: 0.9834026834840477
- Micro F1: 0.9834
- Weighted F1: 0.9834026834840479
- Macro Precision: 0.9834502145172822
- Micro Precision: 0.9834
- Weighted Precision: 0.9834502145172822
- Macro Recall: 0.9833999999999999
- Micro Recall: 0.9834
- Weighted Recall: 0.9834