calibration_config.json

{
  "temperature": 0.5308,
  "threshold_fake": 0.05,
  "threshold_credible": 0.95,
  "model_name": "xlm-roberta-base",
  "wandb_run_id": "g9qn9beq",
  "test_macro_f1": 0.9361,
  "test_fake_recall": 0.8462,
  "test_fake_precision": 0.9066,
  "test_fake_f1": 0.8753,
  "threshold_rationale": "0.05 chosen over scipy-optimal 0.0135: gains only 1 extra true positive vs 42 fewer false positives. 0.50 raw argmax also strong but 0.05 recovers 2 additional fakes with minimal precision cost (0.907 vs 0.916)."
}