base_model: MCG-NJU/videomae-base-finetuned-kinetics
library_name: peft
pipeline_tag: video-classification
language:
- en
tags:
- misinformation-detection
- social-media
- fakett
- peft
- lora
- transformers
- base_model:adapter:MCG-NJU/videomae-base-finetuned-kinetics
VideoMAE — Video-Only Misinformation Detection on FakeTT
Authors: Andrei-Gabriel Radu, Ciprian-Octavian Truică, Elena-Simona Apostol
National University of Science and Technology POLITEHNICA Bucharest
LoRA adapter fine-tuned from MCG-NJU/videomae-base-finetuned-kinetics for binary video-only misinformation classification on FakeTT.
This model accompanies the bachelor thesis Misinformation Detection in Social Media Videos.
Results
| Dataset | Modality | Macro-F1 |
|---|---|---|
| FakeTT | Video-only | 0.7750 |
Model
- Base model:
MCG-NJU/videomae-base-finetuned-kinetics - Task: Binary misinformation classification
- Modality: Video-only
- Fine-tuning: LoRA / PEFT
- Dataset: FakeTT
- Number of classes: 2
- Primary metric: Macro-F1
Training
- LoRA rank (
r): 8 - LoRA alpha: 32
- LoRA dropout: 0.05
- Target modules:
query,value,key,dense - Bias: none
Usage
from peft import PeftModel
from transformers import AutoImageProcessor, AutoModelForVideoClassification
repo_id = "DS4AI-UPB/videomae-misinfo-lora"
base_model_id = "MCG-NJU/videomae-base-finetuned-kinetics"
processor = AutoImageProcessor.from_pretrained(repo_id)
base_model = AutoModelForVideoClassification.from_pretrained(
base_model_id, num_labels=2, ignore_mismatched_sizes=True
)
model = PeftModel.from_pretrained(base_model, repo_id).eval()
Use the same frame sampling and preprocessing procedure as during training before passing pixel_values to the model.
Intended Use
Research and benchmarking of video-only misinformation detection on short social-media videos.
Limitations
The model does not use titles, descriptions or other textual metadata. It can miss linguistic misinformation cues and can degrade under domain shift or a different frame-sampling strategy.
Citation
@thesis{radu2026misinformation,
author = {Radu, Andrei-Gabriel and Truică, Ciprian-Octavian and Apostol, Elena-Simona},
title = {Misinformation Detection in Social Media Videos},
school = {National University of Science and Technology POLITEHNICA Bucharest},
year = {2026}
}