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skshreyas714
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toxicity_classification

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  1. schema: '2.0'
    2. 

  2. stages:
    3. 

  3.   data-split:
    4. 

  4.     cmd: python3 src/data_split.py
    5. 

  5.     deps:
    6. 

  6.     - path: data/raw_data/train.csv
    7. 

  7.       md5: 791e42335500c447273a7dc85f58239e
    8. 

  8.       size: 68802655
    9. 

  9.     - path: src/data_split.py
    10. 

  10.       md5: a6fdd01ead673f13f51fff461f39188c
    11. 

  11.       size: 1243
    12. 

  12.     outs:
    13. 

  13.     - path: data/processed_data/x_test.npy
    14. 

  14.       md5: 575e522a4e1d06801263c14d828431f1
    15. 

  15.       size: 6701733
    16. 

  16.     - path: data/processed_data/x_train.npy
    17. 

  17.       md5: 06b7823ce0e11baf2e54e7d9ed7ba23c
    18. 

  18.       size: 26810751
    19. 

  19.     - path: data/processed_data/y_test.npy
    20. 

  20.       md5: eddd6c7205cf978eeaa1e4dbecf1c0e6
    21. 

  21.       size: 1787368
    22. 

  22.     - path: data/processed_data/y_train.npy
    23. 

  23.       md5: 0be8c4bc8246de494dc92ebec0c2062c
    24. 

  24.       size: 7148864
    25. 

  25.   data-preprocess:
    26. 

  26.     cmd: python3 src/data_preprocess.py
    27. 

  27.     deps:
    28. 

  28.     - path: data/processed_data/x_test.npy
    29. 

  29.       md5: 575e522a4e1d06801263c14d828431f1
    30. 

  30.       size: 6701733
    31. 

  31.     - path: data/processed_data/x_train.npy
    32. 

  32.       md5: 06b7823ce0e11baf2e54e7d9ed7ba23c
    33. 

  33.       size: 26810751
    34. 

  34.     - path: src/data_preprocess.py
    35. 

  35.       md5: 6e996d4e169ba0d4baa70f71bd0ce1bc
    36. 

  36.       size: 2447
    37. 

  37.     outs:
    38. 

  38.     - path: data/embedding_matrix.npy
    39. 

  39.       md5: 7181ce899a529a2bf22d1da38622dd6b
    40. 

  40.       size: 312844928
    41. 

  41.     - path: models/tokenizer.pkl
    42. 

  42.       md5: 61f2c3228db89aa526b68b184a3fc029
    43. 

  43.       size: 5726036
    44. 

  44.   model-training:
    45. 

  45.     cmd: python3 src/model_training.py
    46. 

  46.     deps:
    47. 

  47.     - path: data/embedding_matrix.npy
    48. 

  48.       md5: 020a1f7a624b27b0fbd78988ff8c4d18
    49. 

  49.       size: 312844928
    50. 

  50.     - path: src/model_training.py
    51. 

  51.       md5: a7dd32a47366efa91ee9a0774c002a35
    52. 

  52.       size: 3503
    53. 

  53.     outs:
    54. 

  54.     - path: models/toxicity_classifier.h5
    55. 

  55.       md5: 6bb1f60881846ff3cf7a49c698a96d52
    56. 

  56.       size: 157141360
    57. 

  57.     - path: plots/accuracy.jpg
    58. 

  58.       md5: 7a79387df9a2f7d0c56e678e0c005ce7
    59. 

  59.       size: 23104
    60. 

  60.     - path: plots/loss.jpg
    61. 

  61.       md5: ea87645887816df13421cc5705447571
    62. 

  62.       size: 18546
    63. 

  63.   model-evaluation:
    64. 

  64.     cmd: python3 src/model_evaluation.py
    65. 

  65.     deps:
    66. 

  66.     - path: data/processed_data/x_test.npy
    67. 

  67.       md5: 575e522a4e1d06801263c14d828431f1
    68. 

  68.       size: 6701733
    69. 

  69.     - path: data/processed_data/y_test.npy
    70. 

  70.       md5: eddd6c7205cf978eeaa1e4dbecf1c0e6
    71. 

  71.       size: 1787368
    72. 

  72.     - path: models/toxicity_classifier.h5
    73. 

  73.       md5: 6bb1f60881846ff3cf7a49c698a96d52
    74. 

  74.       size: 157141360
    75. 

  75.     - path: src/model_evaluation.py
    76. 

  76.       md5: 63e4850a9942339a7ca0a3d2acf5808d
    77. 

  77.       size: 756
    78.
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