I did something similar in March using Opus 4.6 (iirc) on google's "Parameter Golf" challenge, "a challenge to train the best language model that fits in a 16MB artifact and trains in under 10 minutes on 8xH100s, evaluated by compression on the FineWeb validation set (tokenizer-agnostic, bits per byte)."

I never ended up writing it up, but you can watch me spend $600 as it explored different experiments: https://github.com/rbitr/parameter-golf/blob/main/BUDGET.md

I found, similar to another comment, that it got in local minima very easily and continued to pursue loosing ideas instead of exploring (despite being prompted to do so and being aware of how much budget it had left). I also found it tended to ignore instructions. And one example, when I fed it a better solution that had come along from the public leaderboard, it ignored everything it had done and started exploring locally around that new solution, which wasn't very interesting or productive.

Would be interesting to re-run with a newer model but it's hard for me to justify the money again.