Zero Shot Transfer Image Classification On 1
평가 지표
Accuracy (Private)
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
모델 이름 | Accuracy (Private) |
---|---|
eva-clip-improved-training-techniques-for | 82 |
모델 2 | - |
eva-clip-18b-scaling-clip-to-18-billion | 83.8 |
learning-transferable-visual-models-from | 76.2 |
pali-a-jointly-scaled-multilingual-language | 85.4 |
learning-transferable-visual-models-from | - |
learning-customized-visual-models-with | 78.5 |
pali-a-jointly-scaled-multilingual-language | 72.11 |
internvl-scaling-up-vision-foundation-models | 83.2 |
learning-transferable-visual-models-from | 59.6 |
coca-contrastive-captioners-are-image-text | 86.3 |
모델 12 | 88.3 |
boldsymbol-m-2-encoder-advancing-bilingual | 88.5 |
alternating-gradient-descent-and-mixture-of | 83.9 |
scaling-vision-transformers-to-22-billion | 85.9 |
모델 16 | 81.8 |
scaling-up-visual-and-vision-language | 76.4 |
the-effectiveness-of-mae-pre-pretraining-for | 82.1 |
altclip-altering-the-language-encoder-in-clip | 74.5 |
your-diffusion-model-is-secretly-a-zero-shot | 61.4 |
combined-scaling-for-zero-shot-transfer | 85.7 |
the-effectiveness-of-mae-pre-pretraining-for | 81.1 |
lit-zero-shot-transfer-with-locked-image-text | 84.5 |