forbes-0023
363b49281b
- Project structure: solver/, freecad/, export/, configs/, scripts/, tests/, docs/ - pyproject.toml with dependency groups: core, train, freecad, dev - Hydra configs: dataset (synthetic, fusion360), model (baseline, gat), training (pretrain, finetune), export (production) - Dockerfile with CUDA+PyG GPU and CPU-only targets - docker-compose.yml for train, test, data-gen services - Makefile with targets: train, test, lint, format, type-check, data-gen, export, check - Pre-commit hooks: ruff, mypy, conventional commits - Gitea Actions CI: lint, type-check, test on push/PR - README with setup and usage instructions
43 lines
697 B
YAML
43 lines
697 B
YAML
# Synthetic pre-training config
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phase: pretrain
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dataset: synthetic
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model: baseline
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optimizer:
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name: adamw
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lr: 1e-3
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weight_decay: 1e-4
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scheduler:
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name: cosine_annealing
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T_max: 100
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eta_min: 1e-6
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training:
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epochs: 100
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batch_size: 64
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gradient_clip: 1.0
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early_stopping_patience: 10
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amp: true
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loss:
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edge_weight: 1.0
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graph_weight: 0.5
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joint_type_weight: 0.3
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dof_weight: 0.2
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redundant_penalty: 2.0 # safety loss multiplier
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checkpointing:
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save_best_val_loss: true
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save_best_val_accuracy: true
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save_every_n_epochs: 10
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checkpoint_dir: checkpoints/pretrain
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logging:
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backend: wandb # or tensorboard
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project: kindred-solver
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log_every_n_steps: 50
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seed: 42
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