![CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet – arXiv Vanity CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet – arXiv Vanity](https://media.arxiv-vanity.com/render-output/7111142/x3.png)
CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet – arXiv Vanity
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![ViFi-CLIP | A simple baseline to adapt CLIP for video action recognition tasks. ViFi-CLIP (Video Fine-tuned CLIP) performs competitive to more complex approaches having dedicated components designed to model temporal information in ViFi-CLIP | A simple baseline to adapt CLIP for video action recognition tasks. ViFi-CLIP (Video Fine-tuned CLIP) performs competitive to more complex approaches having dedicated components designed to model temporal information in](https://muzairkhattak.github.io/ViFi-CLIP/docs/Vclip_prompting_block_diagram.png)
ViFi-CLIP | A simple baseline to adapt CLIP for video action recognition tasks. ViFi-CLIP (Video Fine-tuned CLIP) performs competitive to more complex approaches having dedicated components designed to model temporal information in
![Aran Komatsuzaki on Twitter: "CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet Demonstrates that CLIP is better or at least competitive in Aran Komatsuzaki on Twitter: "CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet Demonstrates that CLIP is better or at least competitive in](https://pbs.twimg.com/media/Fj0ltX9WIAIjwcR.png)
Aran Komatsuzaki on Twitter: "CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet Demonstrates that CLIP is better or at least competitive in
![ViFi-CLIP | A simple baseline to adapt CLIP for video action recognition tasks. ViFi-CLIP (Video Fine-tuned CLIP) performs competitive to more complex approaches having dedicated components designed to model temporal information in ViFi-CLIP | A simple baseline to adapt CLIP for video action recognition tasks. ViFi-CLIP (Video Fine-tuned CLIP) performs competitive to more complex approaches having dedicated components designed to model temporal information in](https://muzairkhattak.github.io/ViFi-CLIP/docs/Vclip_block_diagram.png)
ViFi-CLIP | A simple baseline to adapt CLIP for video action recognition tasks. ViFi-CLIP (Video Fine-tuned CLIP) performs competitive to more complex approaches having dedicated components designed to model temporal information in
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Have you tried to fine-tune the clip model (as official Vit-B-32) in your datasets? · Issue #25 · mlfoundations/open_clip · GitHub
![Mitchell Wortsman on Twitter: "Can zero-shot models such as CLIP be fine- tuned without reducing out-of-distribution accuracy? Yes! Our new method for robust fine-tuning improves average OOD accuracy by 9% on multiple ImageNet Mitchell Wortsman on Twitter: "Can zero-shot models such as CLIP be fine- tuned without reducing out-of-distribution accuracy? Yes! Our new method for robust fine-tuning improves average OOD accuracy by 9% on multiple ImageNet](https://pbs.twimg.com/media/E-yNT4JUcAUFAoa.jpg:large)
Mitchell Wortsman on Twitter: "Can zero-shot models such as CLIP be fine- tuned without reducing out-of-distribution accuracy? Yes! Our new method for robust fine-tuning improves average OOD accuracy by 9% on multiple ImageNet
![Fine-tuning CLIP for automatic extraction of product features from images | by Squadra Machine Learning Company | Medium Fine-tuning CLIP for automatic extraction of product features from images | by Squadra Machine Learning Company | Medium](https://miro.medium.com/v2/resize:fit:942/1*GLJ-tLwI-WEwjktyJaFh6w.png)
Fine-tuning CLIP for automatic extraction of product features from images | by Squadra Machine Learning Company | Medium
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