
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 19984005
- CO2 Emissions (in grams): 20.790169878009916

## Validation Metrics

- Loss: 0.06693269312381744
- Accuracy: 0.9789
- Precision: 0.9843244336569579
- Recall: 0.9733
- AUC: 0.99695552
- F1: 0.9787811745776348

## 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/gagandeepkundi/autonlp-text-classification-19984005
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("gagandeepkundi/autonlp-text-classification-19984005", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("gagandeepkundi/autonlp-text-classification-19984005", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "es", "tags": "autonlp", "datasets": ["gagandeepkundi/autonlp-data-text-classification"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 20.790169878009916}
transformers pytorch roberta text-classification autonlp es dataset:gagandeepkundi/autonlp-data-text-classification co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #autonlp #es #dataset-gagandeepkundi/autonlp-data-text-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 19984005
- CO2 Emissions (in grams): 20.790169878009916

## Validation Metrics

- Loss: 0.06693269312381744
- Accuracy: 0.9789
- Precision: 0.9843244336569579
- Recall: 0.9733
- AUC: 0.99695552
- F1: 0.9787811745776348

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 19984005
- CO2 Emissions (in grams): 20.790169878009916 ## Validation Metrics

- Loss: 0.06693269312381744
- Accuracy: 0.9789
- Precision: 0.9843244336569579
- Recall: 0.9733
- AUC: 0.99695552
- F1: 0.9787811745776348 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #roberta #text-classification #autonlp #es #dataset-gagandeepkundi/autonlp-data-text-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 19984005
- CO2 Emissions (in grams): 20.790169878009916 ## Validation Metrics

- Loss: 0.06693269312381744
- Accuracy: 0.9789
- Precision: 0.9843244336569579
- Recall: 0.9733
- AUC: 0.99695552
- F1: 0.9787811745776348 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #roberta #text-classification #autonlp #es #dataset-gagandeepkundi/autonlp-data-text-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 19984005
- CO2 Emissions (in grams): 20.790169878009916## Validation Metrics

- Loss: 0.06693269312381744
- Accuracy: 0.9789
- Precision: 0.9843244336569579
- Recall: 0.9733
- AUC: 0.99695552
- F1: 0.9787811745776348## Usage

You can use cURL to access this model:



Or Python API: