
# DistilBERT (uncased) for FaceNews Classification

This model is a classification model built by fine-tuning
[DistilBERT base model](https://huggingface.co/distilbert-base-uncased).
This model was trained using
[fake-and-real-news-dataset](https://www.kaggle.com/clmentbisaillon/fake-and-real-news-dataset)
for five epochs.

> **NOTE:**
This model is just a POC (proof-of-concept) for a fellowship I was applying for.

## Intended uses & limitations

Note that this model is primarily aimed at classifying an article to either
"Fake" or "Real". 

### How to use

Check this [notebook](https://www.kaggle.com/code/mohamedanwarvic/fakenewsclassifier-fatima-fellowship) on Kaggle.
{"language": "en", "license": "apache-2.0", "tags": ["exbert"], "datasets": ["bookcorpus", "wikipedia"]}
transformers pytorch distilbert text-classification exbert en dataset:bookcorpus dataset:wikipedia license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #exbert #en #dataset-bookcorpus #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


# DistilBERT (uncased) for FaceNews Classification

This model is a classification model built by fine-tuning
DistilBERT base model.
This model was trained using
fake-and-real-news-dataset
for five epochs.

> NOTE:
This model is just a POC (proof-of-concept) for a fellowship I was applying for.

## Intended uses & limitations

Note that this model is primarily aimed at classifying an article to either
"Fake" or "Real". 

### How to use

Check this notebook on Kaggle.
# DistilBERT (uncased) for FaceNews Classification

This model is a classification model built by fine-tuning
DistilBERT base model.
This model was trained using
fake-and-real-news-dataset
for five epochs.

> NOTE:
This model is just a POC (proof-of-concept) for a fellowship I was applying for. ## Intended uses & limitations

Note that this model is primarily aimed at classifying an article to either
"Fake" or "Real". ### How to use

Check this notebook on Kaggle.
TAGS
#transformers #pytorch #distilbert #text-classification #exbert #en #dataset-bookcorpus #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # DistilBERT (uncased) for FaceNews Classification

This model is a classification model built by fine-tuning
DistilBERT base model.
This model was trained using
fake-and-real-news-dataset
for five epochs.

> NOTE:
This model is just a POC (proof-of-concept) for a fellowship I was applying for. ## Intended uses & limitations

Note that this model is primarily aimed at classifying an article to either
"Fake" or "Real". ### How to use

Check this notebook on Kaggle.
passage: TAGS
#transformers #pytorch #distilbert #text-classification #exbert #en #dataset-bookcorpus #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# DistilBERT (uncased) for FaceNews Classification

This model is a classification model built by fine-tuning
DistilBERT base model.
This model was trained using
fake-and-real-news-dataset
for five epochs.

> NOTE:
This model is just a POC (proof-of-concept) for a fellowship I was applying for.## Intended uses & limitations

Note that this model is primarily aimed at classifying an article to either
"Fake" or "Real".### How to use

Check this notebook on Kaggle.