
# Model Trained Using AutoTrain

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

## Validation Metrics
loss: 0.694091796875

f1: 0.6666666666666666

precision: 0.5

recall: 1.0

auc: 0.5

accuracy: 0.5

{"language": ["unk"], "tags": ["autotrain", "text-classification"], "datasets": ["abhishek/autotrain-data-advtest7"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0}}
transformers pytorch bert text-classification autotrain unk dataset:abhishek/autotrain-data-advtest7 co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-abhishek/autotrain-data-advtest7 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

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

## Validation Metrics
loss: 0.694091796875

f1: 0.6666666666666666

precision: 0.5

recall: 1.0

auc: 0.5

accuracy: 0.5

# Model Trained Using AutoTrain

- Problem type: Text Classification
- CO2 Emissions (in grams): 0.0000 ## Validation Metrics
loss: 0.694091796875

f1: 0.6666666666666666

precision: 0.5

recall: 1.0

auc: 0.5

accuracy: 0.5
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-abhishek/autotrain-data-advtest7 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Text Classification
- CO2 Emissions (in grams): 0.0000 ## Validation Metrics
loss: 0.694091796875

f1: 0.6666666666666666

precision: 0.5

recall: 1.0

auc: 0.5

accuracy: 0.5
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-abhishek/autotrain-data-advtest7 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Model Trained Using AutoTrain

- Problem type: Text Classification
- CO2 Emissions (in grams): 0.0000## Validation Metrics
loss: 0.694091796875

f1: 0.6666666666666666

precision: 0.5

recall: 1.0

auc: 0.5

accuracy: 0.5