
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 689620825
- CO2 Emissions (in grams): 20.656741915705204

## Validation Metrics

- Loss: 0.7315372824668884
- Accuracy: 0.6354949675117849
- Precision: 0.63792194092827
- Recall: 0.6191451241361658
- AUC: 0.6912165223485615
- F1: 0.6283932978308872

## 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/unjustify/autotrain-commonsence-689620825
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("unjustify/autotrain-commonsence-689620825", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("unjustify/autotrain-commonsence-689620825", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autotrain", "datasets": ["unjustify/autotrain-data-commonsence"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 20.656741915705204}
transformers pytorch distilbert text-classification autotrain en dataset:unjustify/autotrain-data-commonsence co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #autotrain #en #dataset-unjustify/autotrain-data-commonsence #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 689620825
- CO2 Emissions (in grams): 20.656741915705204

## Validation Metrics

- Loss: 0.7315372824668884
- Accuracy: 0.6354949675117849
- Precision: 0.63792194092827
- Recall: 0.6191451241361658
- AUC: 0.6912165223485615
- F1: 0.6283932978308872

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 689620825
- CO2 Emissions (in grams): 20.656741915705204 ## Validation Metrics

- Loss: 0.7315372824668884
- Accuracy: 0.6354949675117849
- Precision: 0.63792194092827
- Recall: 0.6191451241361658
- AUC: 0.6912165223485615
- F1: 0.6283932978308872 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #distilbert #text-classification #autotrain #en #dataset-unjustify/autotrain-data-commonsence #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 689620825
- CO2 Emissions (in grams): 20.656741915705204 ## Validation Metrics

- Loss: 0.7315372824668884
- Accuracy: 0.6354949675117849
- Precision: 0.63792194092827
- Recall: 0.6191451241361658
- AUC: 0.6912165223485615
- F1: 0.6283932978308872 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #distilbert #text-classification #autotrain #en #dataset-unjustify/autotrain-data-commonsence #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 689620825
- CO2 Emissions (in grams): 20.656741915705204## Validation Metrics

- Loss: 0.7315372824668884
- Accuracy: 0.6354949675117849
- Precision: 0.63792194092827
- Recall: 0.6191451241361658
- AUC: 0.6912165223485615
- F1: 0.6283932978308872## Usage

You can use cURL to access this model:



Or Python API: