Prompt Engineering On Imagenet
Metrics
Harmonic mean
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Harmonic mean |
|---|---|
| promptkd-unsupervised-prompt-distillation-for | 77.62 |
| prompt-learning-via-meta-regularization | 74.09 |
| maple-multi-modal-prompt-learning | 73.47 |
| self-regulating-prompts-foundational-model | 74.01 |
| read-only-prompt-optimization-for-vision | 74.00 |
| beyond-sole-strength-customized-ensembles-for | 75.49 |
| learning-transferable-visual-models-from | 70.22 |
| learning-domain-invariant-prompt-for-vision | 74.02 |
| mmrl-multi-modal-representation-learning-for | 74.45 |
| learning-hierarchical-prompt-with-structured | 74.17 |
| dept-decoupled-prompt-tuning | 74.02 |
| hpt-hierarchically-prompting-vision-language | 74.24 |
| conditional-prompt-learning-for-vision | 73.10 |
| consistency-guided-prompt-learning-for-vision | 74.33 |