VLMEvalKit Evaluation Results Collection
Browse and filter AI model evaluation results
Submit evaluations for speaker tagging and view leaderboard
Visualize dataset distributions with facets
Display CLIP benchmark results for inference performance
View and compare pass@k metrics for AI models
Display color charts and diagrams
Generate images based on data
Generate a detailed dataset report
Parse bilibili bvid to aid / cid
Generate financial charts from stock data
Explore income data with an interactive visualization tool
Analyze and visualize Hugging Face model download stats
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.