evaluation/README.md

evaluation/

Training logs and performance metrics.

1. Contents

logs/
├── face_orientation_training_log.json           # MLP (latest run)
├── mlp_face_orientation_training_log.json       # MLP (alternate)
└── xgboost_face_orientation_training_log.json   # XGBoost

2. Log Format

Each JSON file records the full training history:

MLP logs:

{
  "config": { "epochs": 30, "lr": 0.001, "batch_size": 32, ... },
  "history": {
    "train_loss": [0.287, 0.260, ...],
    "val_loss":   [0.256, 0.245, ...],
    "train_acc":  [0.889, 0.901, ...],
    "val_acc":    [0.905, 0.909, ...]
  },
  "test": { "accuracy": 0.929, "f1": 0.929, "roc_auc": 0.971 }
}

XGBoost logs:

{
  "config": { "n_estimators": 600, "max_depth": 8, "learning_rate": 0.149, ... },
  "train_losses": [0.577, ...],
  "val_losses":   [0.576, ...],
  "test": { "accuracy": 0.959, "f1": 0.959, "roc_auc": 0.991 }
}

3. Generated By

• python -m models.mlp.train → writes MLP log
• python -m models.xgboost.train → writes XGBoost log
• Notebooks in notebooks/ also save logs here