Prompt Engineering On Oxford Iiit Pet Dataset
Metrics
Harmonic mean
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Harmonic mean |
|---|---|
| learning-transferable-visual-models-from | 94.12 |
| hpt-hierarchically-prompting-vision-language | 96.91 |
| read-only-prompt-optimization-for-vision | 96.05 |
| maple-multi-modal-prompt-learning | 96.58 |
| dept-decoupled-prompt-tuning | 96.37 |
| learning-hierarchical-prompt-with-structured | 96.71 |
| prompt-learning-via-meta-regularization | 96.49 |
| learning-domain-invariant-prompt-for-vision | 96.26 |
| self-regulating-prompts-foundational-model | 96.30 |
| consistency-guided-prompt-learning-for-vision | 96.87 |
| mmrl-multi-modal-representation-learning-for | 96.74 |
| conditional-prompt-learning-for-vision | 96.43 |
| promptkd-unsupervised-prompt-distillation-for | 97.15 |