
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 7024732
- CO2 Emissions (in grams): 0.2438639401641305

## Validation Metrics

- Loss: 0.16775867342948914
- Accuracy: 0.9473333333333334
- Macro F1: 0.9473921270228505
- Micro F1: 0.9473333333333334
- Weighted F1: 0.9473921270228505
- Macro Precision: 0.9478705813419325
- Micro Precision: 0.9473333333333334
- Weighted Precision: 0.9478705813419323
- Macro Recall: 0.9473333333333332
- Micro Recall: 0.9473333333333334
- Weighted Recall: 0.9473333333333334
{"tags": "autotrain", "datasets": ["abhishek/autotrain-data-vision_877913e77fb94b7abd4dafc5ebf830b0", "fashion_mnist"], "co2_eq_emissions": 0.2438639401641305, "model-index": [{"name": "autotrain_fashion_mnist_vit_base", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "fashion_mnist", "type": "fashion_mnist"}, "metrics": [{"type": "accuracy", "value": 0.9473, "name": "Accuracy"}]}, {"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "fashion_mnist", "type": "fashion_mnist", "config": "fashion_mnist", "split": "test"}, "metrics": [{"type": "accuracy", "value": 0.9431, "name": "Accuracy", "verified": true}, {"type": "precision", "value": 0.9435374485262068, "name": "Precision Macro", "verified": true}, {"type": "precision", "value": 0.9431, "name": "Precision Micro", "verified": true}, {"type": "precision", "value": 0.9435374485262069, "name": "Precision Weighted", "verified": true}, {"type": "recall", "value": 0.9430999999999999, "name": "Recall Macro", "verified": true}, {"type": "recall", "value": 0.9431, "name": "Recall Micro", "verified": true}, {"type": "recall", "value": 0.9431, "name": "Recall Weighted", "verified": true}, {"type": "f1", "value": 0.9431357840300738, "name": "F1 Macro", "verified": true}, {"type": "f1", "value": 0.9431, "name": "F1 Micro", "verified": true}, {"type": "f1", "value": 0.9431357840300738, "name": "F1 Weighted", "verified": true}, {"type": "loss", "value": 0.17352284491062164, "name": "loss", "verified": true}]}]}]}
transformers pytorch vit image-classification autotrain dataset:abhishek/autotrain-data-vision_877913e77fb94b7abd4dafc5ebf830b0 dataset:fashion_mnist model-index co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #vit #image-classification #autotrain #dataset-abhishek/autotrain-data-vision_877913e77fb94b7abd4dafc5ebf830b0 #dataset-fashion_mnist #model-index #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 7024732
- CO2 Emissions (in grams): 0.2438639401641305

## Validation Metrics

- Loss: 0.16775867342948914
- Accuracy: 0.9473333333333334
- Macro F1: 0.9473921270228505
- Micro F1: 0.9473333333333334
- Weighted F1: 0.9473921270228505
- Macro Precision: 0.9478705813419325
- Micro Precision: 0.9473333333333334
- Weighted Precision: 0.9478705813419323
- Macro Recall: 0.9473333333333332
- Micro Recall: 0.9473333333333334
- Weighted Recall: 0.9473333333333334
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 7024732
- CO2 Emissions (in grams): 0.2438639401641305 ## Validation Metrics

- Loss: 0.16775867342948914
- Accuracy: 0.9473333333333334
- Macro F1: 0.9473921270228505
- Micro F1: 0.9473333333333334
- Weighted F1: 0.9473921270228505
- Macro Precision: 0.9478705813419325
- Micro Precision: 0.9473333333333334
- Weighted Precision: 0.9478705813419323
- Macro Recall: 0.9473333333333332
- Micro Recall: 0.9473333333333334
- Weighted Recall: 0.9473333333333334
TAGS
#transformers #pytorch #vit #image-classification #autotrain #dataset-abhishek/autotrain-data-vision_877913e77fb94b7abd4dafc5ebf830b0 #dataset-fashion_mnist #model-index #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 7024732
- CO2 Emissions (in grams): 0.2438639401641305 ## Validation Metrics

- Loss: 0.16775867342948914
- Accuracy: 0.9473333333333334
- Macro F1: 0.9473921270228505
- Micro F1: 0.9473333333333334
- Weighted F1: 0.9473921270228505
- Macro Precision: 0.9478705813419325
- Micro Precision: 0.9473333333333334
- Weighted Precision: 0.9478705813419323
- Macro Recall: 0.9473333333333332
- Micro Recall: 0.9473333333333334
- Weighted Recall: 0.9473333333333334
passage: TAGS
#transformers #pytorch #vit #image-classification #autotrain #dataset-abhishek/autotrain-data-vision_877913e77fb94b7abd4dafc5ebf830b0 #dataset-fashion_mnist #model-index #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 7024732
- CO2 Emissions (in grams): 0.2438639401641305## Validation Metrics

- Loss: 0.16775867342948914
- Accuracy: 0.9473333333333334
- Macro F1: 0.9473921270228505
- Micro F1: 0.9473333333333334
- Weighted F1: 0.9473921270228505
- Macro Precision: 0.9478705813419325
- Micro Precision: 0.9473333333333334
- Weighted Precision: 0.9478705813419323
- Macro Recall: 0.9473333333333332
- Micro Recall: 0.9473333333333334
- Weighted Recall: 0.9473333333333334