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config 1.5 kB

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  1. [General]
  2. revision = "first"
  3. datapath = "./data/smallset/imdb/"
  4. embed_path = "./data/smallset/imdb/embedding.txt"
  5. optimizer = "adam"
  6. attn_mode = "rout"
  7. seq_encoder = "bilstm"
  8. out_caps_num = 5
  9. rout_iter = 3
  10. max_snt_num = 40
  11. max_wd_num = 40
  12. max_epochs = 50
  13. pre_trained = true
  14. batch_sz = 32
  15. batch_sz_min = 32
  16. bucket_sz = 5000
  17. partial_update_until_epoch = 2
  18. embed_size = 300
  19. hidden_size = 200
  20. dense_hidden = [300, 10]
  21. lr = 0.0002
  22. decay_steps = 1000
  23. decay_rate = 0.9
  24. dropout = 0.2
  25. early_stopping = 7
  26. reg = 1e-06
  27. [My]
  28. datapath = "./data/smallset/imdb/"
  29. embed_path = "./data/smallset/imdb/embedding.txt"
  30. optimizer = "adam"
  31. attn_mode = "rout"
  32. seq_encoder = "bilstm"
  33. out_caps_num = 5
  34. rout_iter = 3
  35. max_snt_num = 40
  36. max_wd_num = 40
  37. max_epochs = 50
  38. pre_trained = true
  39. batch_sz = 32
  40. batch_sz_min = 32
  41. bucket_sz = 5000
  42. partial_update_until_epoch = 2
  43. embed_size = 300
  44. hidden_size = 200
  45. dense_hidden = [300, 10]
  46. lr = 0.0002
  47. decay_steps = 1000
  48. decay_rate = 0.9
  49. dropout = 0.2
  50. early_stopping = 70
  51. reg = 1e-05
  52. test = 5
  53. new_attr = 40
  54. [POS]
  55. epochs = 20
  56. batch_size = 1
  57. pickle_path = "./data_for_tests/"
  58. validate = true
  59. save_best_dev = true
  60. model_saved_path = "./"
  61. rnn_hidden_units = 100
  62. rnn_layers = 1
  63. rnn_bi_direction = true
  64. word_emb_dim = 100
  65. dropout = 0.5
  66. use_crf = true
  67. [POS_test]
  68. save_output = true
  69. validate_in_training = true
  70. save_dev_input = false
  71. save_loss = true
  72. batch_size = 1
  73. pickle_path = "./data_for_tests/"
  74. rnn_hidden_units = 100
  75. rnn_layers = 1
  76. rnn_bi_direction = true
  77. word_emb_dim = 100
  78. dropout = 0.5
  79. use_crf = true

一款轻量级的自然语言处理(NLP)工具包,目标是减少用户项目中的工程型代码,例如数据处理循环、训练循环、多卡运行等