8d89fe80ff
- 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
76 lines
2.5 KiB
Bash
Executable File
76 lines
2.5 KiB
Bash
Executable File
#!/bin/bash
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#
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# MAMBA-2 Production Training Launch Script
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#
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# Configuration:
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# - 200 epochs (early stopping at ~150)
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# - 32 batch size (4GB VRAM optimized)
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# - 0.0001 learning rate
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# - 60 sequence length
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# - 128 hidden dim (memory efficient)
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# - 64 state dim
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# - GPU acceleration (RTX 3050 Ti)
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# - 360 training files (665,483 bars)
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#
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# Expected Duration: 2-3 hours
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#
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set -e # Exit on error
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# Configuration
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EPOCHS=200
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BATCH_SIZE=32
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LEARNING_RATE=0.0001
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SEQ_LENGTH=60
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HIDDEN_DIM=128
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STATE_DIM=64
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DATA_DIR="test_data/real/databento/ml_training"
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OUTPUT_DIR="ml/trained_models/production/mamba2"
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# Create output directory
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mkdir -p "$OUTPUT_DIR"
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# Print configuration
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echo "╔═══════════════════════════════════════════════════════════╗"
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echo "║ MAMBA-2 Production Training Launch ║"
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echo "╚═══════════════════════════════════════════════════════════╝"
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echo ""
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echo "Configuration:"
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echo " Epochs: $EPOCHS"
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echo " Batch Size: $BATCH_SIZE"
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echo " Learning Rate: $LEARNING_RATE"
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echo " Sequence Length: $SEQ_LENGTH"
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echo " Hidden Dim: $HIDDEN_DIM"
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echo " State Dim: $STATE_DIM"
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echo " Data Directory: $DATA_DIR"
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echo " Output Directory: $OUTPUT_DIR"
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echo ""
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echo "GPU: RTX 3050 Ti (4GB VRAM)"
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echo "Data: 360 files, 665,483 bars"
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echo "Expected Duration: 2-3 hours"
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echo ""
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echo "Starting training..."
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echo ""
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# Launch training with CUDA
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CUDA_VISIBLE_DEVICES=0 cargo run --release -p ml --example train_mamba2_dbn --features cuda -- \
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--epochs "$EPOCHS" \
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--batch-size "$BATCH_SIZE" \
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--learning-rate "$LEARNING_RATE" \
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--sequence-length "$SEQ_LENGTH" \
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--hidden-dim "$HIDDEN_DIM" \
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--state-dim "$STATE_DIM" \
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--data-dir "$DATA_DIR" \
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--output-dir "$OUTPUT_DIR" \
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--use-gpu \
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2>&1 | tee "$OUTPUT_DIR/training.log"
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echo ""
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echo "╔═══════════════════════════════════════════════════════════╗"
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echo "║ MAMBA-2 Training Complete ║"
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echo "╚═══════════════════════════════════════════════════════════╝"
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echo ""
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echo "Checkpoints saved to: $OUTPUT_DIR"
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echo "Training log: $OUTPUT_DIR/training.log"
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echo ""
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