Vilio: State-of-the-art Visio-Linguistic Models applied to Hateful Memes
Vilio: State-of-the-art Visio-Linguistic Models applied to Hateful Memes
Niklas Muennighoff

Abstract
This work presents Vilio, an implementation of state-of-the-art visio-linguistic models and their application to the Hateful Memes Dataset. The implemented models have been fitted into a uniform code-base and altered to yield better performance. The goal of Vilio is to provide a user-friendly starting point for any visio-linguistic problem. An ensemble of 5 different V+L models implemented in Vilio achieves 2nd place in the Hateful Memes Challenge out of 3,300 participants. The code is available at https://github.com/Muennighoff/vilio.
Code Repositories
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| meme-classification-on-hateful-memes | Vilio | Accuracy: 0.695 ROC-AUC: 0.825 |
Build AI with AI
From idea to launch — accelerate your AI development with free AI co-coding, out-of-the-box environment and best price of GPUs.