Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Inquiry about resources and processng time #6

Open
surajk222 opened this issue Jul 5, 2024 · 1 comment
Open

Inquiry about resources and processng time #6

surajk222 opened this issue Jul 5, 2024 · 1 comment

Comments

@surajk222
Copy link

surajk222 commented Jul 5, 2024

Hi,
I am currently working with the NExT-QA dataset and I ran your code using the model meta-llama/Meta-Llama-3-8B, as GPT-3.5 and GPT-4 are not open source. Could you please provide details on the resources you used to achieve the results with the NExT-QA dataset? Additionally, how long did it take for 1000 annotations to be processed?

@CeeZh
Copy link
Owner

CeeZh commented Jul 8, 2024

Hi,

I used 4 A6000 GPUs and it takes 1-2h to run llama-3-8B on Next-qa val set (~5k examples). It takes 3-6h to run llama-3-70B depending on the length of your captions.

I have run LLava-1.5 captions + llama-3-70B on nextqa before. The results are Causal (63.1), Temporal (56.3), Descriptive (70.0), All (62.0). Hope this information help you.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants