reports.json

{
  "overall": {
    "at_0.5": {
      "precision_macro": 0.6608465608465608,
      "recall_macro": 0.7035714285714285,
      "f1_macro": 0.6764388665555447,
      "precision_weighted": 0.8374859708193041,
      "recall_weighted": 0.8106060606060606,
      "f1_weighted": 0.821655123645515,
      "accuracy": 0.8106060606060606,
      "confusion_matrix": [
        [
          96,
          16
        ],
        [
          9,
          11
        ]
      ],
      "classification_report": "              precision    recall  f1-score   support\n\n no-recl (0)     0.9143    0.8571    0.8848       112\n    recl (1)     0.4074    0.5500    0.4681        20\n\n    accuracy                         0.8106       132\n   macro avg     0.6608    0.7036    0.6764       132\nweighted avg     0.8375    0.8106    0.8217       132\n",
      "threshold": 0.5
    },
    "at_best_global": {
      "precision_macro": 0.6608465608465608,
      "recall_macro": 0.7035714285714285,
      "f1_macro": 0.6764388665555447,
      "precision_weighted": 0.8374859708193041,
      "recall_weighted": 0.8106060606060606,
      "f1_weighted": 0.821655123645515,
      "accuracy": 0.8106060606060606,
      "confusion_matrix": [
        [
          96,
          16
        ],
        [
          9,
          11
        ]
      ],
      "classification_report": "              precision    recall  f1-score   support\n\n no-recl (0)     0.9143    0.8571    0.8848       112\n    recl (1)     0.4074    0.5500    0.4681        20\n\n    accuracy                         0.8106       132\n   macro avg     0.6608    0.7036    0.6764       132\nweighted avg     0.8375    0.8106    0.8217       132\n",
      "threshold": 0.5
    },
    "at_best_by_lang": {
      "precision_macro": 0.6608465608465608,
      "recall_macro": 0.7035714285714285,
      "f1_macro": 0.6764388665555447,
      "precision_weighted": 0.8374859708193041,
      "recall_weighted": 0.8106060606060606,
      "f1_weighted": 0.821655123645515,
      "accuracy": 0.8106060606060606,
      "confusion_matrix": [
        [
          96,
          16
        ],
        [
          9,
          11
        ]
      ],
      "classification_report": "              precision    recall  f1-score   support\n\n no-recl (0)     0.9143    0.8571    0.8848       112\n    recl (1)     0.4074    0.5500    0.4681        20\n\n    accuracy                         0.8106       132\n   macro avg     0.6608    0.7036    0.6764       132\nweighted avg     0.8375    0.8106    0.8217       132\n",
      "thresholds_by_lang": {
        "es": 0.5
      }
    }
  },
  "thresholds": {
    "global_best": {
      "threshold": 0.5,
      "f1_macro": 0.6764388665555447,
      "precision_macro": 0.6608465608465608,
      "recall_macro": 0.7035714285714285
    },
    "by_lang_best": {
      "es": {
        "threshold": 0.5,
        "f1_macro": 0.6764388665555447,
        "precision_macro": 0.6608465608465608,
        "recall_macro": 0.7035714285714285
      }
    },
    "default": 0.5
  },
  "per_lang": {
    "at_0.5": [
      {
        "lang": "es",
        "n": 132,
        "accuracy": 0.8106060606060606,
        "f1_macro": 0.6764388665555447,
        "precision_macro": 0.6608465608465608,
        "recall_macro": 0.7035714285714285,
        "f1_weighted": 0.821655123645515,
        "precision_weighted": 0.8374859708193041,
        "recall_weighted": 0.8106060606060606
      }
    ],
    "at_best_global": [
      {
        "lang": "es",
        "n": 132,
        "accuracy": 0.8106060606060606,
        "f1_macro": 0.6764388665555447,
        "precision_macro": 0.6608465608465608,
        "recall_macro": 0.7035714285714285,
        "f1_weighted": 0.821655123645515,
        "precision_weighted": 0.8374859708193041,
        "recall_weighted": 0.8106060606060606
      }
    ],
    "at_best_by_lang": [
      {
        "lang": "es",
        "n": 132,
        "accuracy": 0.8106060606060606,
        "f1_macro": 0.6764388665555447,
        "precision_macro": 0.6608465608465608,
        "recall_macro": 0.7035714285714285,
        "f1_weighted": 0.821655123645515,
        "precision_weighted": 0.8374859708193041,
        "recall_weighted": 0.8106060606060606
      }
    ]
  }
}