Model
Training performance and model diagnostics
Showing simulated data. Live Supabase integration coming soon.
Training Reward Curve
Episode reward over 150 training epochs (latest model)
In-Sample vs Out-of-Sample
Checking for overfitting -- smaller gap is better
| Metric | In-Sample | Out-of-Sample | Gap | Status |
|---|---|---|---|---|
| Win Rate | 40.3 | 36.1 | 10% | |
| Avg PnL | 2.1 | -3.8 | 281% | |
| Sharpe | 0.52 | 0.18 | 65% | |
| Profit Factor | 1.02 | 0.82 | 20% | |
| Max DD | -5.4 | -8.7 | 61% | |
| Trades/Day | 3.4 | 3.1 | 9% |
Max DD gap is 81% -- the model may be underestimating tail risk out-of-sample. Consider wider stoploss or drawdown-aware training.
Action Distribution
How often the model goes long, short, or stays neutral
Long38% · 119 trades
Avg PnL: -1.2 bps
Short29% · 90 trades
Avg PnL: -2.6 bps
Neutral33% · 103 trades
Avg PnL: 0 bps
Confidence Distribution
Model prediction confidence vs actual PnL
Higher confidence → higher PnL -- the model is well-calibrated
Feature Importance
Which inputs the model relies on most (top 10)
CVD 5m
18.0%+3%
Taker Buy Ratio
14.0%+1%
RSI (14)
11.0%-1%
OFI 5m
9.0%+2%
Volume Spike
8.0%---
Futures Premium
7.0%-1%
Trade Intensity
6.0%+1%
Large Trade Imbalance
5.0%---
Hurst Exponent
4.0%+1%
ATR (14)
3.0%-1%
Weekly Retraining History
Performance delta after each Friday retraining cycle
| Week | WR Before | WR After | PnL Before | PnL After | Result |
|---|---|---|---|---|---|
| W11 | 36% | 38.7% | -3.2 bps | -1.4 bps | Healthy |
| W12 | 38.7% | 39.1% | -1.4 bps | -1.1 bps | Healthy |
| W13 | 39.1% | 40.3% | -1.1 bps | -1.8 bps | Caution |