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indobert-binary-sentiment-classifier

Text Classification
Safetensors
Indonesian
bert
sentiment-analysis
indonesian
indobert
context-conditioned
Eval Results (legacy)
Model card Files
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indobert-binary-sentiment-classifier
File size: 1,506 Bytes
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{
  "task": "context-conditioned-binary-sentiment",
  "base_model": "indobenchmark/indobert-large-p2",
  "num_labels": 2,
  "label_names": [
    "Negatif",
    "Positif"
  ],
  "trained_at": "2026-03-28T04:46:17.832313",
  "epochs": 5,
  "batch_size": 16,
  "learning_rate": 2e-05,
  "max_length": 256,
  "train_samples": 11938,
  "val_samples": 2107,
  "unique_contexts": 188,
  "class_weights": {
    "Negatif": 0.6781,
    "Positif": 1.904
  },
  "eval_loss": 0.3284696340560913,
  "eval_accuracy": 0.9606074988134788,
  "eval_f1_macro": 0.9494468467911159,
  "eval_f1_weighted": 0.9607315060581719,
  "eval_precision_macro": 0.9466677468135667,
  "eval_recall_macro": 0.9523280061254744,
  "classification_report": {
    "Negatif": {
      "precision": 0.9766688269604666,
      "recall": 0.9697554697554698,
      "f1-score": 0.9731998708427511,
      "support": 1554.0
    },
    "Positif": {
      "precision": 0.9166666666666666,
      "recall": 0.9349005424954792,
      "f1-score": 0.9256938227394808,
      "support": 553.0
    },
    "accuracy": 0.9606074988134788,
    "macro avg": {
      "precision": 0.9466677468135667,
      "recall": 0.9523280061254744,
      "f1-score": 0.9494468467911159,
      "support": 2107.0
    },
    "weighted avg": {
      "precision": 0.9609207516674095,
      "recall": 0.9606074988134788,
      "f1-score": 0.9607315060581719,
      "support": 2107.0
    }
  },
  "confusion_matrix": [
    [
      1507,
      47
    ],
    [
      36,
      517
    ]
  ]
}