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Prompt Engineering On Imagenet V2

Metrics

Top-1 accuracy %

Results

Performance results of various models on this benchmark

Model Name
Top-1 accuracy %
Paper TitleRepository
CoCoOp64.07Conditional Prompt Learning for Vision-Language Models
MaPLe64.07MaPLe: Multi-modal Prompt Learning
POMP63.8--
CLIP60.83Learning Transferable Visual Models From Natural Language Supervision
HPT65.25Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
MMRL64.47MMRL: Multi-Modal Representation Learning for Vision-Language Models
HPT++65.31HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
PromptSRC64.35Self-regulating Prompts: Foundational Model Adaptation without Forgetting
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