huangfu
745868a456
Group samples by identical inputs before splitting, add target-aware stratification options, and cover the behavior with tests so repeated-input rows no longer leak across train, validation, and test sets. Made-with: Cursor
60 lines
1.1 KiB
YAML
60 lines
1.1 KiB
YAML
# 温和正则 + 略提高 V_pi 权重（在 default 基线上小幅改动，便于对比）
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# 使用: python -m src.main train --config configs/mild_reg.yaml
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data_path: data/dataset.txt
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split_ratios: [0.7, 0.15, 0.15]
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random_seed: 42
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split_mode: grouped_stratified
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split_stratify_target: V_pi
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split_stratify_bins: 10
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remove_duplicate_rows: true
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outlier_strategy: none
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outlier_apply_to: targets
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outlier_config:
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iqr_k: 1.5
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zscore_threshold: 4.0
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quantile_lower: 0.001
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quantile_upper: 0.999
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filter_v_pi_range: true
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v_pi_min: 0.0
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v_pi_max: 500.0
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remove_nonpositive_vpi: false
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model:
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input_dim: 8
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hidden_dims: [200, 300, 350, 300, 200]
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output_dim: 3
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batchnorm: false
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dropout: 0.05
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residual: false
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optimizer:
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name: adamw
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lr: 0.001
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weight_decay: 0.0001
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scheduler:
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type: cosine
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plateau_factor: 0.5
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plateau_patience: 10
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plateau_min_lr: 1.0e-6
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training:
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batch_size: 128
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epochs: 300
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early_stopping_patience: 30
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num_workers: 0
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loss:
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type: huber
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huber_delta: 1.0
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target_weights: [1.0, 1.0, 1.2]
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output_dir: results
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last_run_dir: null
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