pytorch bert text-classification en dataset:tristantristantristan/autotrain-data-rumour_detection transformers autotrain co2_eq_emissions
---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- tristantristantristan/autotrain-data-rumour_detection
co2_eq_emissions: 0.056186258092819436
---

# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 813825547
- CO2 Emissions (in grams): 0.056186258092819436

## Validation Metrics

- Loss: 0.15057753026485443
- Accuracy: 0.9738805970149254
- Precision: 0.9469026548672567
- Recall: 0.9304347826086956
- AUC: 0.9891149437157905
- F1: 0.9385964912280702

## 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/tristantristantristan/autotrain-rumour_detection-813825547
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("tristantristantristan/autotrain-rumour_detection-813825547", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("tristantristantristan/autotrain-rumour_detection-813825547", use_auth_token=True)

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

outputs = model(**inputs)
```