metadata
license: apache-2.0
language:
- en
metrics:
- accuracy: 1
- recall: 1
- f1: 1
base_model:
- distilbert/distilroberta-base
tags:
- fake-news
- text-classification
- transformers
- distilroberta
- nlp
- deep-learning
- pytorch
- huggingface
- fine-tuning
- misinformation
FakeBerta: A Fine-Tuned DistilRoBERTa Model for Fake News Detection
You can check the model's fine-tuning code on my GitHub.
Model Overview
FakeBerta is a fine-tuned version of DistilRoBERTa for detecting fake news. The model is trained to classify news articles as real (0) or fake (1) using natural language processing (NLP) techniques. Base Model: DistilRoBERTa Task: Fake news classification
Example of code using AutoModelForSequenceCalssification:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
import torch
model_name = "YerayEsp/FakeBerta"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)
inputs = tokenizer("Breaking: Scientists discover water on Mars!", return_tensors="pt")
outputs = model(**inputs)
logits = outputs.logits
predicted_class = torch.argmax(logits).item()
print(f"Predicted class: {predicted_class}") # 0 = Real, 1 = Fake
Library: Transformers (Hugging Face)