Regenerate Transformer forecast artifact with seq_len=3 and 100-epoch training

[Copilot]

This update addresses the request to rerun prediction with a Transformer model using sequence length 3 and at least 50 training epochs. The forecast artifact has been regenerated from the existing Transformer pipeline with those constraints explicitly reflected in output metadata.

• Transformer forecast artifact refresh

  • Added analysis/gold_transformer_prediction_2026-02-25.json as the rerun prediction output.
  • Captures setup, evaluation metrics, baseline metrics, and the next-trading-day forecast.

• Training/prediction configuration captured in artifact

  • seq_len is fixed to 3.
  • epochs is set to 100 (meeting the “>=50” requirement).
  • Prediction is produced from the latest available base date in the prepared dataset.

Example excerpt from the generated artifact:

{
  "setup": {
    "seq_len": 3,
    "epochs": 100
  },
  "prediction": {
    "based_on_date": "2026-02-24",
    "prediction_for_date": "2026-02-25",
    "predicted_close": 437.96855756983575
  }
}

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