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cyb004-baseline-classifier

Tabular Classification
PyTorch
cybersecurity
phishing
email-security
bec
social-engineering
synthetic-data
xgboost
baseline
Eval Results (legacy)
Model card Files
xet
 Community
cyb004-baseline-classifier
File size: 2,443 Bytes
16be928
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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{
  "purpose": "With n=100 campaigns, single-seed metrics carry test-fold variance. Multi-seed evaluation gives a more reliable picture.",
  "seeds_evaluated": [
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    31,
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  "per_seed": [
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      "test_n_classes": 7,
      "accuracy": 0.6547008547008547,
      "macro_f1": 0.6401276666852063,
      "macro_roc_auc_ovr": 0.935584434710217
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    {
      "seed": 7,
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      "accuracy": 0.6267123287671232,
      "macro_f1": 0.6141815367358149,
      "macro_roc_auc_ovr": 0.9256987657069029
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      "macro_f1": 0.5953435905708684,
      "macro_roc_auc_ovr": 0.9235372520169014
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    {
      "seed": 17,
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      "accuracy": 0.64349376114082,
      "macro_f1": 0.6328717716731788,
      "macro_roc_auc_ovr": 0.9426545946495839
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    {
      "seed": 23,
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      "accuracy": 0.5915254237288136,
      "macro_f1": 0.5734921834318393,
      "macro_roc_auc_ovr": 0.9245031023094512
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    {
      "seed": 31,
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    {
      "seed": 45,
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      "seed": 99,
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    {
      "seed": 123,
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      "macro_roc_auc_ovr": 0.9443324151480283
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    {
      "seed": 200,
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      "accuracy": 0.6931407942238267,
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      "macro_roc_auc_ovr": 0.9450377543018418
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  ],
  "aggregate": {
    "accuracy_mean": 0.6491180619923773,
    "accuracy_std": 0.03799334369624316,
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    "macro_f1_mean": 0.638316643797632,
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    "roc_auc_mean": 0.9367328092032338,
    "roc_auc_std": 0.009623085359130642
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}