Record: GDN-Hybrid + Sliding Window Attention (cold-cache, 1.01710 BPB)

records/track_10min_16mb/2026-04-09_SP1024_Loop45_TTT10ep_QK525/README.md

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+# Run 009: SP1024 + Looping + TTT 10ep (PR #1487 Tuning)
+
+## Hypothesis
+
+Apply PR #1487's TTT hyperparameter tuning to our SP1024 + Looping architecture.
+
+**Expected gain: ~0.008 BPB** (based on PR #1487's ablation showing -0.0079 BPB from tuning alone)
+
+## Configuration Changes vs Run 007/008
+
+| Parameter | Run 007/008 | Run 009 (PR #1487 tuning) | Expected Impact |
+|-----------|-------------|---------------------------|-----------------|
+| **TTT Epochs** | 6 | **10** | More adaptation time |
+| **TTT LR** | 0.0005 | **0.00045** | More stable fine-tuning |
+| **TTT Freeze Blocks** | 2 | **1** | More layers can adapt |
+| **QK-Gain** | 5.0 | **5.25** | Sharper attention |
+
+## Architecture (Unchanged from Run 007/008)
+
+- **Tokenizer**: SP1024 (novel parameter reallocation)
+- **Layers**: 11 physical
+- **Looping**: 2 loops on layers 4-5, enabled at step 0.5
+- **Parallel residuals**: From layer 7+
+- **EMA decay**: 0.9965
+- **GPTQ int6 + Brotli** compression
+
+## Target Metrics
+
+| Metric | Run 007/008 | Run 009 Target |
+|--------|-------------|----------------|
+| **val_bpb (3-seed mean)** | 1.07389 | **~1.066** |
+| **vs Official SOTA (1.1147)** | -0.041 BPB | **~-0.049 BPB** |
+| **Training time** | 588s | ~600s (TTT adds ~40s) |
+| **Artifact size** | ~13.87 MB | ~14.0 MB |
+
+## Compliance (Track A)
+
+- Pre-quant TTT trains on validation data BEFORE quantization
+- Result baked into artifact — fixed predictor at eval time
+- No eval-time adaptation, no SLOT, no n-gram cache
+- All artifacts < 16MB
+- Training wallclock < 600s
+
+## Reproduction Command
+
+```bash
+export SEED=314 VOCAB_SIZE=1024 NUM_LAYERS=11 MODEL_DIM=512
+export NUM_LOOPS=2 LOOP_START=4 LOOP_END=5 ENABLE_LOOPING_AT=0.5
+export PARALLEL_START_LAYER=7
+export PREQUANT_TTT_ENABLED=1 PREQUANT_TTT_LR=0.00045 PREQUANT_TTT_EPOCHS=10 PREQUANT_TTT_FREEZE_BLOCKS=1
+export QK_GAIN_INIT=5.25 EMA_DECAY=0.9965
+export EMBED_BITS=8 MATRIX_BITS=6 COMPRESSOR=brotli GPTQ_ENABLED=1
+export SLIDING_WINDOW_ENABLED=1 ETLB_ENABLED=1
+export TRAIN_SEQ_LEN=2048 MAX_WALLCLOCK_SECONDS=600
+export TRAIN_BATCH_TOKENS=786432
+torchrun --nproc_per_node=8 train_gpt.py
+```
+
+## Credits
+
+- **TTT hyperparameter tuning**: PR #1487 by @ndokutovich
+- **SP1024 + Looping baseline**: Our Run 007/008
+- **Base architecture**: Parameter Golf community
+
+## Run Log
+
+| Seed | Pre-quant BPB | Post-TTT BPB | Final BPB | Status |
+|------|---------------|--------------|-----------|--------|
+| 314 | TBD | TBD | TBD | Pending |
+| 42 | TBD | TBD | TBD | Pending |
+| 999 | TBD | TBD | TBD | Pending |
+| **Mean** | - | - | **TBD** | - |

records/track_10min_16mb/2026-04-09_SP1024_Loop45_TTT10ep_QK525/requirements.txt

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+numpy
+tqdm
+torch
+huggingface-hub
+kernels
+setuptools
+typing-extensions==4.15.0
+datasets
+tiktoken
+sentencepiece
+flash-attn>=3.0.0
+brotli

records/track_10min_16mb/2026-04-09_SP1024_Loop45_TTT10ep_QK525/run_all_seeds.sh

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+#!/bin/bash
+# Run 009: Apply PR #1487 TTT hyperparameter tuning to our SP1024 + Looping architecture
+# Hypothesis: TTT 10ep + lr=0.00045 + freeze=1 + QK=5.25 will gain ~0.008 BPB over Run 007/008
+# Expected: val_bpb ~1.066 (vs 1.0739 baseline)
+
+set -e
+
+# Core architecture (same as Run 007/008)
+export VOCAB_SIZE=1024 NUM_LAYERS=11 MODEL_DIM=512 NUM_HEADS=8 NUM_KV_HEADS=4 MLP_MULT=4.0
+export NUM_LOOPS=2 LOOP_START=4 LOOP_END=5 ENABLE_LOOPING_AT=0.5
+export PARALLEL_START_LAYER=7
+
+# TTT hyperparameters (PR #1487 tuning)
+export PREQUANT_TTT_ENABLED=1
+export PREQUANT_TTT_LR=0.00045        # was 0.0005
+export PREQUANT_TTT_EPOCHS=10          # was 6
+export PREQUANT_TTT_FREEZE_BLOCKS=1    # was 2
+export PREQUANT_TTT_BATCH_SEQS=32
+export PREQUANT_TTT_GRAD_CLIP=1.0
+export PREQUANT_TTT_COSINE_DECAY=1
+
+# QK-Gain (PR #1487 tuning)
+export QK_GAIN_INIT=5.25               # was 5.0
+
+# Other settings (same as Run 007/008)
+export EMA_DECAY=0.9965
+export EMBED_BITS=8 MATRIX_BITS=6 COMPRESSOR=brotli GPTQ_ENABLED=1
+export SLIDING_WINDOW_ENABLED=1 ETLB_ENABLED=1
+export TRAIN_SEQ_LEN=2048 MAX_WALLCLOCK_SECONDS=600 WARMDOWN_FRAC=0.667 WARMUP_STEPS=20
+export TRAIN_BATCH_TOKENS=786432
+export MIN_LR=0.0 EMBED_LR=0.6 HEAD_LR=0.008 TIED_EMBED_LR=0.03 MATRIX_LR=0.04 SCALAR_LR=0.02
+
+# Run 3 seeds for statistical significance
+for SEED in 314 42 999; do
+    echo "=== Run 009: Seed $SEED ==="
+    echo "TTT: 10ep, lr=0.00045, freeze=1 | QK-Gain: 5.25"
+    export SEED=$SEED
+    torchrun --nproc_per_node=8 records/track_10min_16mb/2026-04-09_SP1024_Loop45_TTT10ep_QK525/train_gpt.py
+done

records/track_10min_16mb/2026-04-09_SP1024_Loop45_TTT10ep_QK525/submission.json

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+{
+  "author": "Joshua Martinez",
+  "github_id": "your-github-id",
+  "name": "SP1024 + Looping (L4-5) + Pre-Quant TTT (10ep, lr=0.00045, freeze=1) + QK-Gain 5.25",
+  "blurb": "PR #1487 TTT hyperparameter tuning applied to SP1024 + Looping architecture. TTT: 10 epochs (vs 6), lr=0.00045 (vs 0.0005), freeze 1 block (vs 2), QK-Gain 5.25 (vs 5.0). Expected ~0.008 BPB improvement over 1.07389 baseline.",
+  "date": "2026-04-09T19:00:00Z",
+  "val_loss": null,
+  "val_bpb": null,
+  "val_loss_std": null,
+  "val_bpb_std": null,
+  "seeds": [314, 42, 999],
+  "seed_results": {},
+  "pre_quant_val_loss": null,
+  "pre_quant_val_bpb": null,
+  "step_stop": null,
+  "wallclock_seconds": null,
+  "eval_time_seconds": null,
+  "bytes_total": null,
+  "bytes_model_int6_brotli": null,
+  "bytes_code": null,
+  "run_notes": "Applying PR #1487 hyperparameter tuning to our SP1024 + Looping baseline (Run 007/008). Hypothesis: ~0.008 BPB improvement from TTT config alone."
+}