# Fake News Classification Distilbert 🤗
This model was trained on 32,326 news articles from CLÉMENT BISAILLON's dataset on Kaggle. The goal is to classify fake news from real news. 

0 : Fake News, 1 : Real News

# Sources
Dataset used: https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset

Base Distilbert: https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english






{"license": "mit", "widget": [{"text": "Health and Human Services Secretary Xavier Becerra declared the monkeypox outbreak a public health emergency on Thursday in an effort to galvanize awareness and unlock additional flexibility and funding to fight the virus\u2019s spread."}]}
transformers pytorch safetensors distilbert text-classification license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #license-mit #autotrain_compatible #endpoints_compatible #region-us 

# Fake News Classification Distilbert 
This model was trained on 32,326 news articles from CLÉMENT BISAILLON's dataset on Kaggle. The goal is to classify fake news from real news. 

0 : Fake News, 1 : Real News

# Sources
Dataset used: URL

Base Distilbert: URL






# Fake News Classification Distilbert 
This model was trained on 32,326 news articles from CLÉMENT BISAILLON's dataset on Kaggle. The goal is to classify fake news from real news. 

0 : Fake News, 1 : Real News # Sources
Dataset used: URL

Base Distilbert: URL
TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 # Fake News Classification Distilbert 
This model was trained on 32,326 news articles from CLÉMENT BISAILLON's dataset on Kaggle. The goal is to classify fake news from real news. 

0 : Fake News, 1 : Real News # Sources
Dataset used: URL

Base Distilbert: URL
passage: TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #license-mit #autotrain_compatible #endpoints_compatible #region-us 
# Fake News Classification Distilbert 
This model was trained on 32,326 news articles from CLÉMENT BISAILLON's dataset on Kaggle. The goal is to classify fake news from real news. 

0 : Fake News, 1 : Real News# Sources
Dataset used: URL

Base Distilbert: URL