db8e6d11f263461d78578868610cf74f4a826e2d
Fast scalar mode (default, for CMA loop): - Rewards: fill quality (PnL when fills happen), moderate fill rate (5-15% sweet spot) - Tolerates: no-fills (valid advisory recommendation) - Penalizes: extreme fill rates (<3% lazy, >30% picked off), adverse selection, drawdown - Light noop penalty (-0.5) vs old heavy (-50) — no-fills are valid signals Advantage mode (for offline analysis): - advantage = raw_performance - baseline_performance - baseline = exponential moving average (decay=0.995) - Clipped to [-10, +10] - Reduces score variance 5.5x vs raw scoring Scoring mode selection: PolicyEvaluator(scoring_mode='fast') — default for CMA loop PolicyEvaluator(scoring_mode='advantage') — for offline analysis 8 new tests for scoring modes. Total: 1186 tests, 50 files, all green.
Description
Sentiment analysis engine with ONNX FinBERT + LoRA adapters
Languages
Python
99.9%
Dockerfile
0.1%