TimesNet_ad.yaml 606 B

123456789101112131415161718192021222324252627282930313233343536
  1. batch_size: 128
  2. seq_len: 100
  3. do_eval: True
  4. epoch: 5
  5. training: True
  6. task: anomaly
  7. to_static_train: False
  8. use_amp: False
  9. amp_level: O2
  10. dataset:
  11. name: TSADDataset
  12. dataset_root: ./data/
  13. train_path: ./data/train.csv
  14. val_path: ./data/val.csv
  15. scale: True
  16. time_feat: False
  17. info_params:
  18. freq: 1
  19. label_col: "label"
  20. time_col: "timestamp"
  21. feature_cols: "feature_0,feature_1"
  22. model:
  23. name: TimesNet_AD
  24. model_cfg:
  25. e_layers: 2
  26. num_kernels: 6
  27. d_model: 32
  28. d_ff: 64
  29. top_k: 3
  30. window_sampling_limit: Null
  31. optimizer_params:
  32. learning_rate: 0.0005
  33. gamma: 0.9