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Add other files and folders, including data related, notebook, test and evaluation
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# evaluation/
Training logs and performance metrics.
## 1. Contents
```
logs/
β”œβ”€β”€ face_orientation_training_log.json # MLP (latest run)
β”œβ”€β”€ 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:**
```json
{
"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:**
```json
{
"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` β†’ writes MLP log
- `python -m models.xgboost.train` β†’ writes XGBoost log
- Notebooks in `notebooks/` also save logs here