VLMEvalKit Evaluation Results Collection
Detect bank fraud without revealing personal data
Predict linear relationships between numbers
Analyze and visualize car data
Build, preprocess, and train machine learning models
Profile a dataset and publish the report on Hugging Face
Multilingual metrics for the LMSys Arena Leaderboard
Search for tagged characters in Animagine datasets
Browse and filter LLM benchmark results
Generate detailed data reports
Label data for machine learning models
Uncensored General Intelligence Leaderboard
Explore and submit NER models
The Open VLM Leaderboard is a data visualization tool designed to showcase the evaluation results of various Vision-Language Models (VLMs). It is part of the VLMEvalKit framework, enabling users to explore and compare the performance of different models across diverse datasets and metrics. The leaderboard provides a comprehensive overview of model effectiveness, helping researchers and practitioners identify top-performing models for specific tasks.
1. What is the purpose of the Open VLM Leaderboard?
The Open VLM Leaderboard is designed to provide a centralized platform for evaluating and comparing Vision-Language Models. It helps users identify the best-performing models for specific tasks and datasets.
2. Can I customize the metrics displayed on the leaderboard?
Yes, the leaderboard allows users to filter and customize the metrics displayed, enabling a focused analysis of model performance according to their needs.
3. How often are the leaderboard results updated?
The leaderboard is updated in real-time as new model evaluations are added to the VLMEvalKit framework. This ensures users always have access to the latest benchmark results.