| # BNB-NOVADAX-TRADE — Phase 1 Supervised Pre-training | |
| ## Resultados | |
| - **Steps**: 204,000 | |
| - **Épocas**: 2 | |
| - **Tempo de treino**: 11.00h | |
| - **Val Loss**: 2.4436 | |
| - **Acc 30s**: 0.178 | |
| - **Acc 60s**: 0.246 | |
| - **Acc 120s**: 0.317 | |
| ## Arquitetura | |
| - Transformer Encoder | d_model=256 | 8 heads | 6 layers | FFN=1024 | |
| - ~10.7M parâmetros | |
| - Contexto: 120 segundos | |
| - Features: 12 features por timestep | |
| - Multi-task: direção 30s/60s/120s + spread futuro + NDX follow | |
| ## Dataset | |
| - Binance BTCUSDT 1s + NovaDax BTC_USDT | 2020-2026 | |
| - Split: 2020-2023 treino | 2024 val | 2025-2026 test (blind) | |
| ## Como usar (Phase 2 — RL Fine-tuning) | |
| ```python | |
| ckpt = torch.load('checkpoint_best.pt', map_location='cpu') | |
| model = TradingTransformer(ckpt['cfg']) | |
| model.load_state_dict(ckpt['model_state']) | |
| emb = model.get_embedding(x) # usar como encoder no PPO | |
| ``` | |