
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3642997339
- CO2 Emissions (in grams): 0.0044

## Validation Metrics

- Loss: 0.244
- Accuracy: 0.925
- Precision: 0.924
- Recall: 0.927
- AUC: 0.971
- F1: 0.925

## Usage

You can use cURL to access this model:

```
$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/ziadA123/autotrain-adult-classification-3642997339
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("ziadA123/autotrain-adult-classification-3642997339", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("ziadA123/autotrain-adult-classification-3642997339", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)
```
{"language": ["unk"], "tags": ["autotrain", "text-classification"], "datasets": ["ziadA123/autotrain-data-adult-classification"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0.0043891444981216995}}
transformers pytorch bert text-classification autotrain unk dataset:ziadA123/autotrain-data-adult-classification co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-ziadA123/autotrain-data-adult-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3642997339
- CO2 Emissions (in grams): 0.0044

## Validation Metrics

- Loss: 0.244
- Accuracy: 0.925
- Precision: 0.924
- Recall: 0.927
- AUC: 0.971
- F1: 0.925

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3642997339
- CO2 Emissions (in grams): 0.0044 ## Validation Metrics

- Loss: 0.244
- Accuracy: 0.925
- Precision: 0.924
- Recall: 0.927
- AUC: 0.971
- F1: 0.925 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-ziadA123/autotrain-data-adult-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3642997339
- CO2 Emissions (in grams): 0.0044 ## Validation Metrics

- Loss: 0.244
- Accuracy: 0.925
- Precision: 0.924
- Recall: 0.927
- AUC: 0.971
- F1: 0.925 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-ziadA123/autotrain-data-adult-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3642997339
- CO2 Emissions (in grams): 0.0044## Validation Metrics

- Loss: 0.244
- Accuracy: 0.925
- Precision: 0.924
- Recall: 0.927
- AUC: 0.971
- F1: 0.925## Usage

You can use cURL to access this model:



Or Python API: