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forecasting-v3 AAPL/ABBV/MCD development study.[2016-08-08, 2021-08-08), selected with
[2021-08-08, 2022-08-08), and refit on [2016-08-08, 2022-08-08).
The three selected refit epoch counts were 7, 1, and 4.[2022-08-08, 2023-08-08). The sealed
reserve [2023-08-08, 2026-08-08) was not read or scored.seedN/ directory contains:model_seedN.pt: weights and the core architecture metadatacalibration_seedN.npz: class-return supports and train/refit calibrationresults.json: training history and development metricsrun_manifest.json: exact configuration and source hashessource/ contains the model definitions and frozen V7 runner used to create
the checkpoints. protocol.md records the study contract. Prediction sheets
and market data are intentionally excluded.1import torch
2
3checkpoint = torch.load(
4 "seed0/model_seed0.pt",
5 map_location="cpu",
6 weights_only=True,
7)
8state_dict = checkpoint["state_dict"]
9print(checkpoint["assets"])
10print(checkpoint["supervised_horizons"])| Seed | Selected epoch | NLL |
|---|---|---|
| 0 | 7 | 2.9471515 |
| 1 | 1 | 2.9441110 |
| 2 | 4 | 2.9445206 |
| Probability ensemble | - | 2.9435108 |