submission: XSA-all + Soft-Round QAT + Full GPTQ + MLP 3.5x + AdamW TTT#631
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Track: 10min_16mb Based on: PR openai#549 (LeakyReLU+ParallelMuon), PR openai#606 (Soft-Round+AdamW TTT), PR openai#609 (XSA-all+Full GPTQ) Changes from SOTA (openai#549): - XSA on all 11 layers (was 4) - Soft-Round QAT with tanh-based differentiable rounding (alpha 1->16) - Full GPTQ with Hessian-aware column-reordered Cholesky error compensation - MHA 8/8 (was GQA 8/4) - MLP 3.5x expansion (1792 hidden, was 3.0x/1536) - BigramHash vocabulary 8192 (was 2048) - AdamW TTT with grouped LR and cosine schedule (was SGD) - Early QAT threshold 0.5 (was late 0.15) - Selective ±1 magnitude pruning to hit size target
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This has no submission.json / val_bpb value, so I can't score it. Also, since this is based on #609, a word of warning that you need to make sure no training data is accessed at eval time, so any calibration mechanisms have to be part of the 600s of training time. |
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Track: 10min_16mb
Based on: PR #549 (LeakyReLU+ParallelMuon), PR #606 (Soft-Round+AdamW TTT), PR #609 (XSA-all+Full GPTQ)
Changes from SOTA (#549):