Zero-shot Classification on ImageNet
71.87AccuracyCLIPFT + A
Evaluation Results
| Method | Links | |
|---|---|---|
| CLIPFT + ABackbone=ViT-B/16, Prompting Strategy=LLM Attributes, Training Samples per Class=16, Training Protocol=Fine-tuned2024.01 | 71.87 | |
| CLIP + ABackbone=ViT-B/16, Prompting Strategy=LLM Attributes, Training Samples per Class=0, Training Protocol=Zero-shot (Pre-trained)2024.01 | 69.74 | |
| CLIP-A-selfBackbone=ViT-B/16, Prompting Strategy=GPT Attributes, Training Samples per Class=16, Training Protocol=Adapter Tuning2024.01 | 68.3 | |
| CLIPBackbone=ViT-B/16, Prompting Strategy=Standard, Training Samples per Class=0, Training Protocol=Zero-shot (Pre-trained)2024.01 | 67.41 |