VLMEvalKit Evaluation Results Collection
Explore tradeoffs between privacy and fairness in machine learning models
Create detailed data reports
Display a Bokeh plot
Analyze your dataset with guided tools
Display server status information
Browse and filter AI model evaluation results
Compare classifier performance on datasets
Create a detailed report from a dataset
Check your progress in a Deep RL course
Browse and filter LLM benchmark results
Multilingual metrics for the LMSys Arena Leaderboard
Predict soil shear strength using input parameters
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.