
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 38998102356
- CO2 Emissions (in grams): 5.2619

## Validation Metrics

- Loss: 0.030
- Accuracy: 0.993
- Precision: 0.991
- Recall: 0.995
- AUC: 1.000
- F1: 0.993

## 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/systash/autotrain-fake_news_fine_tuned_v4-38998102356
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("systash/autotrain-fake_news_fine_tuned_v4-38998102356", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("systash/autotrain-fake_news_fine_tuned_v4-38998102356", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["unk"], "tags": ["autotrain", "text-classification"], "datasets": ["systash/autotrain-data-fake_news_fine_tuned_v4"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 5.261861894487811}}
transformers pytorch roberta text-classification autotrain unk dataset:systash/autotrain-data-fake_news_fine_tuned_v4 co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #roberta #text-classification #autotrain #unk #dataset-systash/autotrain-data-fake_news_fine_tuned_v4 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 38998102356
- CO2 Emissions (in grams): 5.2619

## Validation Metrics

- Loss: 0.030
- Accuracy: 0.993
- Precision: 0.991
- Recall: 0.995
- AUC: 1.000
- F1: 0.993

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 38998102356
- CO2 Emissions (in grams): 5.2619 ## Validation Metrics

- Loss: 0.030
- Accuracy: 0.993
- Precision: 0.991
- Recall: 0.995
- AUC: 1.000
- F1: 0.993 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #roberta #text-classification #autotrain #unk #dataset-systash/autotrain-data-fake_news_fine_tuned_v4 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 38998102356
- CO2 Emissions (in grams): 5.2619 ## Validation Metrics

- Loss: 0.030
- Accuracy: 0.993
- Precision: 0.991
- Recall: 0.995
- AUC: 1.000
- F1: 0.993 ## Usage

You can use cURL to access this model:



Or Python API: