
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 417310793
- CO2 Emissions (in grams): 9.446754273734577

## Validation Metrics

- Loss: 0.25755178928375244
- Accuracy: 0.9407114624505929
- Precision: 0.8600823045267489
- Recall: 0.95
- AUC: 0.9732501264968797
- F1: 0.9028077753779697

## 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 AutoNLP"}' https://api-inference.huggingface.co/models/evandrodiniz/autonlp-api-boamente-417310793
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("evandrodiniz/autonlp-api-boamente-417310793", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("evandrodiniz/autonlp-api-boamente-417310793", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "unk", "tags": "autonlp", "datasets": ["evandrodiniz/autonlp-data-api-boamente"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 9.446754273734577}
transformers pytorch bert text-classification autonlp unk dataset:evandrodiniz/autonlp-data-api-boamente co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autonlp #unk #dataset-evandrodiniz/autonlp-data-api-boamente #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 417310793
- CO2 Emissions (in grams): 9.446754273734577

## Validation Metrics

- Loss: 0.25755178928375244
- Accuracy: 0.9407114624505929
- Precision: 0.8600823045267489
- Recall: 0.95
- AUC: 0.9732501264968797
- F1: 0.9028077753779697

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 417310793
- CO2 Emissions (in grams): 9.446754273734577 ## Validation Metrics

- Loss: 0.25755178928375244
- Accuracy: 0.9407114624505929
- Precision: 0.8600823045267489
- Recall: 0.95
- AUC: 0.9732501264968797
- F1: 0.9028077753779697 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autonlp #unk #dataset-evandrodiniz/autonlp-data-api-boamente #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 417310793
- CO2 Emissions (in grams): 9.446754273734577 ## Validation Metrics

- Loss: 0.25755178928375244
- Accuracy: 0.9407114624505929
- Precision: 0.8600823045267489
- Recall: 0.95
- AUC: 0.9732501264968797
- F1: 0.9028077753779697 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #bert #text-classification #autonlp #unk #dataset-evandrodiniz/autonlp-data-api-boamente #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 417310793
- CO2 Emissions (in grams): 9.446754273734577## Validation Metrics

- Loss: 0.25755178928375244
- Accuracy: 0.9407114624505929
- Precision: 0.8600823045267489
- Recall: 0.95
- AUC: 0.9732501264968797
- F1: 0.9028077753779697## Usage

You can use cURL to access this model:



Or Python API: