
# Model Trained Using AutoTrain

- Problem type: Text Classification
- CO2 Emissions (in grams): 0.0000

## Validation Metrics
loss: 0.688549816608429

f1: 0.7096774193548387

precision: 0.55

recall: 1.0

auc: 0.45075757575757575

accuracy: 0.55

{"language": ["unk"], "tags": ["autotrain", "text-classification"], "datasets": ["Tarive/autotrain-data-4xes-khh9-98zg"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0}}
transformers pytorch bert text-classification autotrain unk dataset:Tarive/autotrain-data-4xes-khh9-98zg co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-Tarive/autotrain-data-4xes-khh9-98zg #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Text Classification
- CO2 Emissions (in grams): 0.0000

## Validation Metrics
loss: 0.688549816608429

f1: 0.7096774193548387

precision: 0.55

recall: 1.0

auc: 0.45075757575757575

accuracy: 0.55

# Model Trained Using AutoTrain

- Problem type: Text Classification
- CO2 Emissions (in grams): 0.0000 ## Validation Metrics
loss: 0.688549816608429

f1: 0.7096774193548387

precision: 0.55

recall: 1.0

auc: 0.45075757575757575

accuracy: 0.55
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-Tarive/autotrain-data-4xes-khh9-98zg #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Text Classification
- CO2 Emissions (in grams): 0.0000 ## Validation Metrics
loss: 0.688549816608429

f1: 0.7096774193548387

precision: 0.55

recall: 1.0

auc: 0.45075757575757575

accuracy: 0.55