### Dataset used 
[Fake and real news dataset](https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset)

### Labels
Fake news: 1 </br>
Real news: 0 

### Usage 
```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer, AutoConfig
import torch

config = AutoConfig.from_pretrained("bhavitvyamalik/fake-news_xtremedistil-l6-h256-uncased")
model = AutoModelForSequenceClassification.from_pretrained("bhavitvyamalik/fake-news_xtremedistil-l6-h256-uncased", config=config)
tokenizer = AutoTokenizer.from_pretrained("microsoft/xtremedistil-l6-h256-uncased", usefast=True)

text = "According to reports by Fox News, Biden is the President of the USA"
encode = tokenizer(text, max_length=512, truncation=True, padding="max_length", return_tensors="pt")

output = model(**encode)
print(torch.argmax(output["logits"]))
```

### Performance on test data 
```json
'test/accuracy': 0.9977836608886719,
'test/aucroc': 0.9999998807907104,
'test/f1': 0.9976308941841125,
'test/loss': 0.00828308891505003
```

### Run can be tracked here
[Wandb project for Fake news classifier](https://wandb.ai/bhavitvya/Fake%20news%20classifier?workspace=user-bhavitvya)
{"license": "mit"}
transformers pytorch bert text-classification license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #license-mit #autotrain_compatible #endpoints_compatible #region-us 

### Dataset used 
Fake and real news dataset

### Labels
Fake news: 1 </br>
Real news: 0 

### Usage 


### Performance on test data 


### Run can be tracked here
Wandb project for Fake news classifier
### Dataset used 
Fake and real news dataset ### Labels
Fake news: 1 </br>
Real news: 0 ### Usage ### Performance on test data ### Run can be tracked here
Wandb project for Fake news classifier
TAGS
#transformers #pytorch #bert #text-classification #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Dataset used 
Fake and real news dataset ### Labels
Fake news: 1 </br>
Real news: 0 ### Usage ### Performance on test data ### Run can be tracked here
Wandb project for Fake news classifier
passage: TAGS
#transformers #pytorch #bert #text-classification #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Dataset used 
Fake and real news dataset### Labels
Fake news: 1 </br>
Real news: 0### Usage### Performance on test data### Run can be tracked here
Wandb project for Fake news classifier