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{
  "backbone": "xlm-roberta-base",
  "num_labels": 2,
  "max_length": 160,
  "dropout": 0.25,
  "id2label": {
    "0": "FAKE",
    "1": "REAL"
  },
  "label2id": {
    "FAKE": 0,
    "REAL": 1
  },
  "decision_threshold": 0.52,
  "task": "binary-classification",
  "problem_type": "Multilingual Fake News Detection",
  "datasets": [
    "LIAR",
    "utahnlp/x-fact"
  ],
  "languages": "25 languages",
  "metrics": {
    "val_f1_macro": 0.6825,
    "test_accuracy": 0.6843,
    "test_f1_macro": 0.6818,
    "test_f1_tuned": 0.6894,
    "test_f1_weighted": 0.6798
  },
  "architecture": {
    "base": "xlm-roberta-base",
    "pooling": "AttentionPooling (all tokens, not just CLS)",
    "head": "Linear(768\u2192384) + GELU + Dropout + Linear(384\u21922)"
  }
}