This model is part of the YouTube Fact Checker project, where transcript sentences are first classified and only factual or disputed claims are forwarded to an LLM for verification.

Model Overview

Architecture: RoBERTa

Task: Text Classification

Framework: Hugging Face Transformers

Language: English

The model classifies each sentence into one of three categories:

Label	Meaning
LABEL_0	NOT_A_CLAIM
LABEL_1	FACTUAL_CLAIM
LABEL_2	DISPUTED_CLAIM

Example

Input

Water boils at 100°C at sea level.

Output

FACTUAL_CLAIM

Input

The Earth is flat.

Output

DISPUTED_CLAIM

Input

I really enjoyed this video.

Output

NOT_A_CLAIM

Intended Use

This model is designed as the first stage of an AI-powered fact-checking pipeline.

Pipeline:

YouTube Video
      │
      ▼
Transcript Extraction
      │
      ▼
Sentence Segmentation
      │
      ▼
RoBERTa Claim Classifier
      │
      ▼
LLM Fact Verification
      │
      ▼
HTML / PDF Report

The classifier helps reduce unnecessary LLM calls by filtering out sentences that are not factual claims.

Usage

python

from transformers import pipeline

classifier = pipeline(
    "text-classification",
    model="AyushRawat1718/youtube-fact-checker-roberta"
)

result = classifier("The moon landing was faked.")

print(result)

Training

The model was fine-tuned for claim classification using a custom labeled dataset.

The objective was to distinguish between:

Non-claims
Verifiable factual claims
Disputed claims

Limitations

Designed primarily for English text.
Performs best on transcript-style sentences.
Does not perform factual verification.
Final verification should be performed using an external LLM.

Related Project

This model is used in the YouTube Fact Checker project.

Features include:

YouTube transcript extraction
Sentence segmentation using spaCy
Claim classification using this RoBERTa model
AI-powered fact verification (Gemini + Groq)
HTML/PDF report generation
FastAPI backend
React frontend (upcoming)

Author

Ayush Rawat

B.Tech Computer Science Engineering

AI • NLP • Full Stack Development

GitHub: https://github.com/AyushRawat1718

⭐ If you find this model useful, consider starring the GitHub repository.

ayushrawat-1718/youtube-fact-checker-roberta

YouTube Fact Checker - Claim Classification Model

Model Overview

Example

Intended Use

Usage

Training

Limitations

Related Project

Author

ayushrawat-1718/
youtube-fact-checker-roberta