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Wave 12 Group 3 Progress: ML Training Infrastructure Improvements ## Changes Summary ### Warning Fixes (W12-16B-WARNINGS: COMPLETE) - Fixed all actionable ML library warnings (0 warnings in ml/src/) - Fixed training example warnings (train_tft.rs, train_dqn.rs, train_ppo.rs, train_mamba2_dbn.rs) - Removed 900+ lines dead code (duplicate types, orphaned tests) - Enhanced metrics output with wall-clock timing Key fixes: - ml/examples/train_tft.rs: Changed 50→225 features, removed unused imports - ml/examples/train_tft_dbn.rs: Used training_duration and feature_config properly - ml/src/trainers/tft.rs: Fixed unused metadata, removed dead code methods - ml/src/dqn/: Deleted rainbow_types.rs (828 lines duplicate code) - ml/src/trainers/ppo.rs: Enhanced value pre-training metrics output ### Training Infrastructure - Added TFT Parquet support (ml/src/trainers/tft_parquet.rs) - Completed DQN training (30 epochs, 178 min) - Completed PPO training (30 epochs, production ready) - Completed MAMBA-2 retraining (20 epochs, best epoch 15) ### Test Data - Added 180-day Parquet files: ES.FUT, NQ.FUT, 6E.FUT, ZN.FUT - Added DBN validation examples - Added 225-feature validation examples ### Model Checkpoints - DQN: dqn_final_epoch30.safetensors (production ready) - PPO: ppo_actor/critic_epoch_30.safetensors (production ready) - MAMBA-2: best_model_epoch_15.safetensors (production ready) ## Remaining Work (W12-16B+) - Implement PPO Parquet support (4-6h) - Implement MAMBA-2 Parquet support (4-6h) - Wire gRPC orchestrator for Parquet training (2-3h) - Fix lazy loading implementation (8-12h) - Complete TFT training with 225 features 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
16 lines
344 B
JSON
16 lines
344 B
JSON
{
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"best_epoch": 15,
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"best_val_loss": 4.5852992613338595,
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"config": {
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"batch_size": 64,
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"d_model": 225,
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"dropout": 0.1,
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"learning_rate": 0.0001,
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"n_layers": 6,
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"seq_len": 60,
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"state_size": 16
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},
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"final_perplexity": 98.03252009550582,
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"total_epochs": 20,
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"training_duration_hours": 0.021275366113611114
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} |