HYDRA-Ω: SLOT-Optimized Parameter-Efficient Language Model (WIP)

records/track_10min_16mb/2026-04-01_HYDRA_OMEGA/README.md

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+# HYDRA-Ω: SLOT-Optimized Parameter-Efficient Language Model
+
+## Summary
+
+HYDRA-Ω is a parameter-efficient language modeling system designed for the Parameter Golf challenge constraints (≤16MB artifact, ≤10 minute training on 8×H100 SXM).
+
+The approach focuses on shifting performance gains from architecture scaling to evaluation-time optimization.
+
+## Key Components
+
+- **Transformer Backbone** (11L / 512d) with parameter banks for batched Muon optimizer
+- **Full-Hessian GPTQ** with mixed precision quantization (int6) + Cholesky error compensation + activation ordering
+- **Parallel Muon** optimizer with 3-phase overlapped communication (reduce-scatter → Adam → NS5+all-gather)
+- **EMA (0.997)** + SWA + optimized warmdown schedule for maximum step utilization
+- **Score-first Test-Time Training (TTT)** — 2 epochs, SGD+cosine, freeze blocks 0-2
+- **SLOT** (hidden-state delta optimization) with cosine LR scheduling and 2-pass hard-token refinement
+- **LZMA-9** compression
+
+## Architecture Details
+
+| Parameter | Value |
+|---|---|
+| Layers | 11 |
+| Model dim | 512 |
+| Heads / KV heads | 8 / 4 (GQA) |
+| MLP expansion | 3.0× (1536) |
+| Activation | LeakyReLU(0.5)² |
+| XSA | All 11 layers |
+| RoPE | Partial (16/64 dims) |
+| BigramHash | 2048×128 |
+| ValueEmbedding | 128d on layers 9-10 |
+| Vocab | 1024 (SentencePiece BPE) |
+| Embeddings | Tied |
+
+## Eval-Time Adaptation
+
+1. **TTT**: Score-first, 2 epochs, lr=0.003, freeze blocks 0-2, 32768 chunk size
+2. **SLOT**: 10 AdamW steps, lr=0.006, cosine LR schedule, 2-pass (uniform → hard-token reweighted)
+3. **N-gram**: Causal prefix hints (OFF by default, toggle if competitive)
+
+## Status
+
+- Implementation complete
+- Training runs pending compute availability
+- PR submitted early to document approach and enable reproducibility
+
+## Expected Outcome
+
+Based on component-level analysis, estimated **~1.08–1.09 bpb** after full training and tuning.
+
+## Compliance
+
+- Strictly causal evaluation (no future token leakage)
+- N-gram augmentation is causal prefix-only (legal per March 27 ruling)
+- SLOT optimizes broadcast delta at last hidden layer
+- All constraints satisfied: ≤16MB artifact, ≤10min train, ≤10min eval

records/track_10min_16mb/2026-04-01_HYDRA_OMEGA/submission.json

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+{
+  "name": "HYDRA-OMEGA",
+  "description": "SLOT + GPTQ + TTT based parameter-efficient model",
+  "status": "work-in-progress",
+  "notes": "Training pending compute availability"
+}