
# Model Trained Using AutoTrain

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

## Validation Metrics
loss: 0.26987823843955994

f1: 0.88656798460874

precision: 0.8705374354229316

recall: 0.9032

auc: 0.956008976

accuracy: 0.88444

{"language": ["unk"], "tags": ["autotrain", "text-classification"], "datasets": ["imdb"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0}}
transformers pytorch bert text-classification autotrain unk dataset:imdb co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-imdb #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: 0.26987823843955994

f1: 0.88656798460874

precision: 0.8705374354229316

recall: 0.9032

auc: 0.956008976

accuracy: 0.88444

# Model Trained Using AutoTrain

- Problem type: Text Classification
- CO2 Emissions (in grams): 0.0000 ## Validation Metrics
loss: 0.26987823843955994

f1: 0.88656798460874

precision: 0.8705374354229316

recall: 0.9032

auc: 0.956008976

accuracy: 0.88444
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-imdb #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: 0.26987823843955994

f1: 0.88656798460874

precision: 0.8705374354229316

recall: 0.9032

auc: 0.956008976

accuracy: 0.88444
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-imdb #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: 0.26987823843955994

f1: 0.88656798460874

precision: 0.8705374354229316

recall: 0.9032

auc: 0.956008976

accuracy: 0.88444