c32db97d57
- Added 30 new sources (5 RSS + 25 Telegram) for previously ZERO-coverage assets - Fixed model loading priority: ONNX > LoRA v2 > PyTorch > Mock - ONNX FinBERT (pre-trained on 1.2M financial docs) now PRIMARY - best for real-world text - LoRA v2 models trained on 518 carefully labeled samples (balanced Bearish/Bullish/Neutral) - Emotion LoRA v2 trained with weighted loss (greed/fear 2x, joy 1.5x) - 30 new sources: STX, FET, XTZ, ENJ, ETC, TRX, ONG, DASH, LTC, ZIL, NEAR, APT, SUI, ICP - Early stopping (patience=3) on both LoRA trainings - Human-in-the-loop verification CLI tool created - Disk-conscious: save_total_limit=1, adapters 6-8MB each Pipeline now correctly classifies: - BTC breaks 100k → +0.54 Bullish ✅ - Major hack → -0.23 Bearish ✅ - HODL → +0.91 Bullish ✅ - Rug pull → -0.30 Bearish ✅ - SEC sues → -0.30 Bearish ✅ - ETF approval → +0.32 Bullish ✅ - Whale accumulation → +0.31 Bullish ✅ Models: ONNX FinBERT (PRIORITY 1) + LoRA v2 adapters (6-8MB each) Training data: 518 carefully labeled samples (190 real + 328 synthetic) Early stopping (patience=3) on both FinBERT and DistilRoBERTa LoRA Emotion LoRA v2: weighted loss (greed/fear 2x, joy 1.5x) + early stopping
57 lines
455 B
Plaintext
57 lines
455 B
Plaintext
# Git
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.git/
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.gitignore
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# Python
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__pycache__/
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*.py[cod]
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*.so
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.Python
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build/
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dist/
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*.egg-info/
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# Virtual environments
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venv/
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env/
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# IDE
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.vscode/
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.idea/
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# OS
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.DS_Store
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Thumbs.db
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# Logs
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*.log
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logs/
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# Data
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data/
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*.parquet
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*.npz
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# Model cache
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~/.cache/
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# Test output
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.pytest_cache/
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.coverage
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htmlcov/
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# Config secrets
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.env
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config/*.local.yaml
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# Documentation
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README.md
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docs/
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# Tests
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tests/
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scripts/
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# Prefect flows (copied separately)
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prefect_flows/
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