jgrusewski
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3853988af7
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feat(hyperopt): Complete DQN hyperopt analysis and PSO optimizer fix
- Fixed PSO budget calculation bug in ml/src/hyperopt/optimizer.rs
- Root cause: Division by n_particles in sequential execution
- Now correctly calculates max_iters = remaining_trials (no division)
- Result: 50 trials complete instead of 23 (100% vs 46%)
- Added comprehensive DQN hyperopt results analysis
- 39/50 trials analyzed across 2 RunPod deployments
- Best hyperparameters identified: LR 4.89e-5 (ultra-low)
- Created DQN_HYPEROPT_RESULTS_SUMMARY.md with expert validation
- GitLab CI/CD pipeline operational (48 lines fixed)
- Fixed YAML syntax errors (unquoted colons)
- All 7 jobs validated and working
- Warning cleanup complete (136 → 0 warnings)
- Removed 143 lines dead code
- Fixed visibility, unused imports, Debug traits
- Archived Wave D reports to docs/archive/
- 8 early stopping reports moved
- Root directory cleaned up
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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2025-11-02 21:49:07 +01:00 |
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jgrusewski
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8d89fe80ff
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chore: Second cleanup wave - organize root directory
- Archive: 85 agent .txt files → docs/archive/agents/legacy_txt/
- Scripts: Move 110 shell scripts → scripts/ (keep deploy.sh in root)
- Models: Move 18 .safetensors → ml/models/checkpoints/training_artifacts/
- Delete: 34 directories (~33GB freed) - target/, coverage_*, test artifacts
- Build: Clean 14 build artifacts (.rlib, .o, .pid, binaries)
- Tests: Move 14 .rs files → tests/standalone/
- SQL: Move 5 files → sql/ (keep init-db*.sql for Docker)
- Wave 153: Archive to docs/archive/historical/wave153/
- Docs: Archive 9 markdown files to wave_d/reports/ and historical/
Total impact: ~34GB freed (both waves), root directory cleaned from 583 to ~40 essential files
Directory count reduced from 65 to 31 (52% reduction)
All historical data preserved in organized archive structure
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2025-10-30 01:26:02 +01:00 |
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jgrusewski
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6da9d262db
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feat(ml): MAMBA-2 P0 fixes + hyperparameter optimization (13 params)
CRITICAL P0 FIXES (Validated - Loss 0.87 → 0.07):
- Add sigmoid activation to inference and training (ml/src/mamba/mod.rs:798, 1538)
- Fix config.total_decay_steps (was hardcoded 10000) (ml/src/mamba/mod.rs:2271)
- Update d_state: 16→64, 32→64 (Mamba-2 spec) (ml/src/mamba/mod.rs:178, 730)
HYPERPARAMETER OPTIMIZATION:
- Implement 13-parameter Bayesian optimization with argmin
- Add async data loading with 3-batch prefetch (+20-30% speedup)
- Create hyperopt adapter: ml/src/hyperopt/adapters/mamba2.rs
- Add example: ml/examples/hyperopt_mamba2_demo.rs
VALIDATION:
- Local test: Loss 0.07 vs 0.87 (12× improvement)
- Val loss: 0.04-0.14 vs 1.2 (27× improvement)
- Accuracy: 12-30% vs 1-5% (3-6× improvement)
- All binaries rebuilt and uploaded to Runpod S3
DEPLOYMENT:
- RTX 4090 pod active (n0fq2ikt4uk0zy)
- Training: 10 trials × 50 epochs, batch_size=256
- Expected: 1.3 days, $10.41 cost
Fixes #P0-sigmoid #P0-decay-steps #hyperopt-mamba2
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2025-10-28 14:11:18 +01:00 |
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