configs/quick_training_config.yaml

# 快速训练配置文件
# Quick Training Configuration - 用于快速验证和调试

# 训练基本信息
training_info:
  experiment_name: "emotion_prediction_quick"
  description: "基于MLP的情绪与生理状态变化预测模型快速训练"
  seed: 42

# 数据配置
data:
  # 数据路径
  train_data_path: "data/train.csv"
  val_data_path: "data/val.csv"
  test_data_path: "data/test.csv"
  
  # 数据预处理
  preprocessing:
    # 特征标准化
    feature_scaling:
      method: "standard"  # standard, min_max, robust, none
      pad_features: "standard"    # PAD特征标准化方法
      vitality_feature: "min_max" # 活力值标准化方法
    
    # 数据增强
    augmentation:
      enabled: false
      noise_std: 0.01
      mixup_alpha: 0.2
  
  # 数据加载 - 较小的批次大小用于快速训练
  dataloader:
    batch_size: 32
    num_workers: 2
    pin_memory: true
    shuffle: true
    drop_last: false

# 训练超参数 - 快速训练设置
training:
  # 优化器配置
  optimizer:
    type: "AdamW"
    learning_rate: 0.001  # 稍高的学习率
    weight_decay: 0.01
    betas: [0.9, 0.999]
    eps: 1e-8
  
  # 学习率调度
  scheduler:
    type: "CosineAnnealingLR"
    T_max: 50  # 与max_epochs相同
    eta_min: 1e-6
    verbose: true
  
  # 训练轮次 - 快速训练
  epochs:
    max_epochs: 50
    early_stopping:
      enabled: true
      patience: 10  # 较短的耐心
      min_delta: 1e-4
      monitor: "val_loss"
      mode: "min"
  
  # 损失函数
  loss:
    type: "MSELoss"
    reduction: "mean"
    
    # 多任务损失权重
    multi_task_weights:
      delta_pad: 1.0
      delta_pressure: 1.0
      confidence: 0.5

# 验证配置
validation:
  # 验证频率
  val_frequency: 1
  
  # 验证指标
  metrics:
    - "MSE"
    - "MAE"
    - "RMSE"
    - "R2"
    - "MAPE"
  
  # 模型选择
  model_selection:
    criterion: "val_loss"
    mode: "min"

# 日志和保存配置
logging:
  # 日志级别
  level: "INFO"
  
  # 日志文件
  log_dir: "logs"
  log_file: "training.log"
  
  # TensorBoard
  tensorboard:
    enabled: true
    log_dir: "runs"
    comment: "_quick_train"
  
  # 进度条
  progress_bar:
    enabled: true
    update_frequency: 5  # 更频繁的更新

# 检查点保存
checkpointing:
  # 保存目录
  save_dir: "checkpoints"
  
  # 保存策略
  save_strategy: "best"
  
  # 文件命名
  filename_template: "model_epoch_{epoch}_val_{val_loss:.4f}.pth"
  
  # 保存内容
  save_items:
    - "model_state_dict"
    - "optimizer_state_dict"
    - "scheduler_state_dict"
    - "epoch"
    - "loss"
    - "metrics"
    - "config"

# 硬件配置
hardware:
  # 设备选择
  device: "auto"
  
  # GPU配置
  gpu:
    id: 0
    memory_fraction: 0.8
    allow_growth: true
  
  # 混合精度训练
  mixed_precision:
    enabled: false
    opt_level: "O1"

# 调试配置
debug:
  # 调试模式
  enabled: true
  
  # 快速训练（用于调试）
  fast_train:
    enabled: true
    max_epochs: 50
    batch_size: 32
    subset_size: 1000
  
  # 梯度检查
  gradient_checking:
    enabled: true
    clip_value: 1.0
  
  # 数据检查
  data_checking:
    enabled: true
    check_nan: true
    check_inf: true
    check_range: true

# 实验跟踪
experiment_tracking:
  # 是否启用实验跟踪
  enabled: false
  
  # MLflow配置
  mlflow:
    tracking_uri: "http://localhost:5000"
    experiment_name: "emotion_prediction_quick"
    run_name: null
    tags: {}
    params: {}