#santa-2024
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Does anyone know why calculator which is given returns that error-no batchsize argument?
In this competition, evaluation codes are strange...From now, all bugs are fixed?
Yeah idk
Eval results also seem to depend on which gpu you use and batch size messes with it
The latest version of metric v28 does not use the parameter batch size anymore. It always uses batch size 1. Earlier versions of metric did use batch size.
I am looking for a team to join
Let's connect, We have some project to discuss AI related
how i can get dataset i have problems while finding the dataset
Hey all, not much action in this channel it seems. I took a stab at the challenge this week with little success. Just getting started, so hopefully better times ahead. Good luck!
welcome to santa2024, this is a blackbox optimization problem, so lot of computing power required ๐
Hey @quasi radish, right, I'm just now thinking that I understand the problem. Took me a moment to get started as I didn't quite understand the ask and was attempting to solve with R, which I was unable to figure out using the Gemma 2 model connection.
I ended up taking a shot with Python, my first venture with the language, still a bit unclear about what we're doing. Ultimately, to operate within the 12 hour time and memory usage limits I ended up splitting the records into groups of 10 tokens, then taking a small sampling (n = 16) to feed into Gemma 2 before taking the best sequence chunks and combining back together. My score isn't great ~ 1089, but I'll take it as this unique challenge is a bit outside my comfort zone. This alone takes ~11 hours to run, so any increase to the sample size hits the time threshold and cancels the script.
I am curious though, how folks are able to generate a single 20/30/40-token length permutation, let alone many, within the limits of the kaggle tool. I assume using the evaluation metric locally helps, but that's just scoring, not permutation generation. Any thoughts?
https://www.kaggle.com/code/josephnehrenz/santa-2024-perplexity-score-minimization
I think using external computing resources is a must here, if you want to get anywhere. The search space is inconceivably huge, so any kind of "brute-force" search will unlikely to get you anywhere, therefore, there is a special type of solution that are "better" for each sample.
at this point, if you want to do anything better than the top public score, you need to pick your battle, pick a sample, pick the "solution" you think applies to that sample, and optimize the heck out of it, with luck, you can break out of the local minima and find a path downward.
Hi,
we have a problem in posting new topic inorder to write the write up ( we are the 3rd team)
we can't create new topic ( it says first internal error then too many requests) :/
any ideas !
@analog terrace
Have you reached out to support? They're usually really good about helping resolve issues like this.
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