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model_train.log

model_train.log 290 KB
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  1. DEBUG:matplotlib:$HOME=/Users/tanghaojie
    2. 

  2. DEBUG:matplotlib:matplotlib data path /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data
    3. 

  3. DEBUG:matplotlib:loaded rc file /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
    4. 

  4. DEBUG:matplotlib:matplotlib version 2.2.2
    5. 

  5. DEBUG:matplotlib:interactive is False
    6. 

  6. DEBUG:matplotlib:platform is darwin
    7. 

  7. 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'idlelib', 'idlelib.run', 'linecache', 'tokenize', 'token', 'queue', 'threading', 'time', 'traceback', 'tkinter', '_tkinter', 'tkinter.constants', 'idlelib.autocomplete', 'string', '_string', 'idlelib.autocomplete_w', 'platform', 'subprocess', 'signal', '_posixsubprocess', 'select', 'selectors', 'math', 'idlelib.multicall', 'idlelib.config', 'configparser', 'idlelib.hyperparser', 'idlelib.pyparse', 'idlelib.calltips', 'inspect', 'ast', '_ast', 'dis', 'opcode', '_opcode', 'textwrap', 'idlelib.calltip_w', 'idlelib.debugger_r', 'idlelib.debugger', 'bdb', 'fnmatch', 'idlelib.macosx', 'idlelib.scrolledlist', 'idlelib.windows', 'idlelib.debugobj_r', 'idlelib.rpc', 'pickle', 'struct', '_struct', '_compat_pickle', '_pickle', 'socket', '_socket', 'socketserver', 'idlelib.iomenu', 'shlex', 'tempfile', 'shutil', 'zlib', 'bz2', '_compression', '_bz2', 'lzma', '_lzma', 'pwd', 'grp', 'random', 'hashlib', '_hashlib', '_blake2', '_sha3', 'bisect', '_bisect', '_random', 'locale', 'idlelib.stackviewer', 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    8. 

  8. INFO:root:正在从数据库读取原始数据
    9. 

  9. DEBUG:matplotlib:$HOME=/Users/tanghaojie
    10. 

  10. DEBUG:matplotlib:matplotlib data path /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data
    11. 

  11. DEBUG:matplotlib:loaded rc file /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
    12. 

  12. DEBUG:matplotlib:matplotlib version 2.2.2
    13. 

  13. DEBUG:matplotlib:interactive is False
    14. 

  14. DEBUG:matplotlib:platform is darwin
    15. 

  15. 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'pandas.plotting._compat', 'pandas.plotting._tools', 'pandas.plotting._core', 'pandas.plotting._converter', 'matplotlib', 'matplotlib.cbook', 'matplotlib.cbook.deprecation', 'matplotlib.cbook._backports', 'matplotlib.compat', 'matplotlib.compat.subprocess', 'matplotlib.rcsetup', 'matplotlib.testing', 'matplotlib.fontconfig_pattern', 'pyparsing', 'matplotlib.colors', 'matplotlib._color_data', 'cycler', 'matplotlib._version']
    16. 

  16. INFO:root:正在从数据库读取原始数据
    17. 

  17. INFO:root:正在对原始数据进行数据扩增
    18. 

  18. INFO:root:正在统计原始数据的标签类型
    19. 

  19. INFO:root:正在制作词表
    20. 

  20. INFO:root:正在获取词向量
    21. 

  21. INFO:root:开始训练基础分类器
    22. 

  22. INFO:root:初始分类器准确率为0.508833922261484
    23. 

  23. INFO:root:开始第1次重训练
    24. 

  24. INFO:root:开始第2次重训练
    25. 

  25. INFO:root:开始第3次重训练
    26. 

  26. INFO:root:开始第4次重训练
    27. 

  27. INFO:root:开始第5次重训练
    28. 

  28. INFO:root:开始第6次重训练
    29. 

  29. INFO:root:开始第7次重训练
    30. 

  30. INFO:root:开始第8次重训练
    31. 

  31. INFO:root:训练完成，测试集准确率为0.508833922261484
    32. 

  32. DEBUG:matplotlib:$HOME=/Users/tanghaojie
    33. 

  33. DEBUG:matplotlib:matplotlib data path /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data
    34. 

  34. DEBUG:matplotlib:loaded rc file /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
    35. 

  35. DEBUG:matplotlib:matplotlib version 2.2.2
    36. 

  36. DEBUG:matplotlib:interactive is False
    37. 

  37. DEBUG:matplotlib:platform is darwin
    38. 

  38. 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'pandas.plotting._compat', 'pandas.plotting._tools', 'pandas.plotting._core', 'pandas.plotting._converter', 'matplotlib', 'matplotlib.cbook', 'matplotlib.cbook.deprecation', 'matplotlib.cbook._backports', 'matplotlib.compat', 'matplotlib.compat.subprocess', 'matplotlib.rcsetup', 'matplotlib.testing', 'matplotlib.fontconfig_pattern', 'pyparsing', 'matplotlib.colors', 'matplotlib._color_data', 'cycler', 'matplotlib._version']
    39. 

  39. INFO:root:正在从数据库读取原始数据
    40. 

  40. INFO:root:正在对原始数据进行数据扩增
    41. 

  41. INFO:root:正在统计原始数据的标签类型
    42. 

  42. INFO:root:正在制作词表
    43. 

  43. INFO:root:正在获取词向量
    44. 

  44. INFO:root:开始训练基础分类器
    45. 

  45. INFO:root:初始分类器准确率为0.5275
    46. 

  46. INFO:root:开始第1次重训练
    47. 

  47. INFO:root:开始第2次重训练
    48. 

  48. INFO:root:开始第3次重训练
    49. 

  49. INFO:root:开始第4次重训练
    50. 

  50. INFO:root:开始第5次重训练
    51. 

  51. INFO:root:开始第6次重训练
    52. 

  52. INFO:root:开始第7次重训练
    53. 

  53. INFO:root:开始第8次重训练
    54. 

  54. INFO:root:训练完成，测试集准确率为0.52625
    55. 

  55. DEBUG:matplotlib:$HOME=/Users/tanghaojie
    56. 

  56. DEBUG:matplotlib:matplotlib data path /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data
    57. 

  57. DEBUG:matplotlib:loaded rc file /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
    58. 

  58. DEBUG:matplotlib:matplotlib version 2.2.2
    59. 

  59. DEBUG:matplotlib:interactive is False
    60. 

  60. DEBUG:matplotlib:platform is darwin
    61. 

  61. 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'tensorflow.python.keras.optimizer_v2.optimizer_v2', 'tensorflow.python.keras.optimizer_v2.learning_rate_schedule', 'tensorflow.python.training.training_ops', 'tensorflow.python.training.gen_training_ops', 'tensorflow.python.keras.optimizer_v2.adagrad', 'tensorflow.python.keras.optimizer_v2.adam', 'tensorflow.python.keras.optimizer_v2.adamax', 'tensorflow.python.keras.optimizer_v2.ftrl', 'tensorflow.python.keras.optimizer_v2.gradient_descent', 'tensorflow.python.keras.optimizer_v2.nadam', 'tensorflow.python.keras.optimizer_v2.rmsprop', 'tensorflow.python.keras.utils.io_utils', 'h5py', 'h5py._errors', 'h5py._hl', 'h5py._hl.compat', 'h5py.version', 'h5py.h5', 'h5py.defs', 'h5py._objects', 'h5py._conv', 'h5py.h5r', 'h5py.h5t', 'h5py.utils', 'h5py.h5py_warnings', 'h5py.h5z', 'h5py.h5a', 'h5py.h5s', 'h5py.h5p', 'h5py.h5ac', 'h5py._proxy', 'h5py.h5d', 'h5py.h5ds', 'h5py.h5f', 'h5py.h5g', 'h5py.h5i', 'h5py.h5fd', 'h5py.h5pl', 'h5py._hl.filters', 'h5py._hl.base', 'h5py._hl.files', 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'tensorflow.python.keras.utils.data_utils', 'multiprocessing.dummy', 'multiprocessing.dummy.connection', 'tensorflow.python.keras.engine.training_utils', 'tensorflow.python.framework.composite_tensor_utils', 'tensorflow.python.keras.saving.hdf5_format', 'tensorflow.python.keras.saving.model_config', 'yaml', 'yaml.error', 'yaml.tokens', 'yaml.events', 'yaml.nodes', 'yaml.loader', 'yaml.reader', 'yaml.scanner', 'yaml.parser', 'yaml.composer', 'yaml.constructor', 'yaml.resolver', 'yaml.dumper', 'yaml.emitter', 'yaml.serializer', 'yaml.representer', 'yaml.cyaml', 'yaml._yaml', 'tensorflow.python.keras.utils.conv_utils', 'tensorflow.python.keras.saving.save', 'tensorflow.python.keras.saving.saved_model.save', 'tensorflow.python.keras.saving.saved_model.network_serialization', 'tensorflow.python.keras.utils.layer_utils', 'tensorflow.python.keras.engine.sequential', 'tensorflow.python.keras.layers', 'tensorflow.python.keras.engine.base_preprocessing_layer', 'tensorflow.python.keras.engine.training_generator', 'tensorflow.python.keras.layers.preprocessing', 'tensorflow.python.keras.layers.preprocessing.normalization_v1', 'tensorflow.python.keras.engine.base_preprocessing_layer_v1', 'tensorflow.python.keras.layers.preprocessing.normalization', 'tensorflow.python.keras.layers.preprocessing.text_vectorization_v1', 'tensorflow.python.keras.layers.preprocessing.text_vectorization', 'tensorflow.python.keras.layers.advanced_activations', 'tensorflow.python.keras.layers.convolutional', 'tensorflow.python.keras.activations', 'tensorflow.python.keras.layers.pooling', 'tensorflow.python.keras.layers.core', 'tensorflow.python.keras.layers.dense_attention', 'tensorflow.python.keras.layers.embeddings', 'tensorflow.python.keras.layers.local', 'tensorflow.python.keras.layers.merge', 'tensorflow.python.keras.layers.noise', 'tensorflow.python.keras.layers.normalization', 'tensorflow.python.keras.layers.normalization_v2', 'tensorflow.python.keras.layers.kernelized', 'tensorflow.python.keras.layers.recurrent', 'tensorflow.python.keras.layers.recurrent_v2', 'tensorflow.python.keras.layers.convolutional_recurrent', 'tensorflow.python.keras.layers.cudnn_recurrent', 'tensorflow.python.keras.layers.wrappers', 'tensorflow.python.keras.layers.rnn_cell_wrapper_v2', 'tensorflow.python.ops.rnn_cell_wrapper_impl', 'tensorflow.python.keras.layers.serialization', 'tensorflow.python.keras.engine.training', 'tensorflow.python.keras.engine.training_arrays', 'tensorflow.python.keras.engine.training_distributed', 'tensorflow.python.keras.engine.partial_batch_padding_handler', 'tensorflow.python.keras.engine.training_eager', 'tensorflow.python.keras.mixed_precision.experimental.loss_scale_optimizer', 'tensorflow.python.keras.engine.training_v2', 'tensorflow.python.keras.engine.data_adapter', 'pandas', 'pytz', 'pytz.exceptions', 'pytz.lazy', 'pytz.tzinfo', 'pytz.tzfile', 'dateutil', 'dateutil._version', 'pandas.compat', 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'pandas.plotting._compat', 'pandas.plotting._tools', 'pandas.plotting._core', 'pandas.plotting._converter', 'matplotlib', 'matplotlib.cbook', 'matplotlib.cbook.deprecation', 'matplotlib.cbook._backports', 'matplotlib.compat', 'matplotlib.compat.subprocess', 'matplotlib.rcsetup', 'matplotlib.testing', 'matplotlib.fontconfig_pattern', 'pyparsing', 'matplotlib.colors', 'matplotlib._color_data', 'cycler', 'matplotlib._version']
    62. 

  62. INFO:root:正在从数据库读取原始数据
    63. 

  63. INFO:root:正在对原始数据进行数据扩增
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  64. INFO:root:正在统计原始数据的标签类型
    65. 

  65. INFO:root:正在制作词表
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  66. INFO:root:正在获取词向量
    67. 

  67. INFO:root:开始训练基础分类器
    68. 

  68. INFO:root:初始分类器准确率为0.4748322147651007
    69. 

  69. INFO:root:开始第1次重训练
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  83. INFO:root:开始第15次重训练
    84. 

  84. INFO:root:训练完成，测试集准确率为0.27348993288590606
    85. 

  85. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    86. 

  86. DEBUG:h5py._conv:Creating converter from 7 to 5
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  87. DEBUG:h5py._conv:Creating converter from 5 to 7
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  88. DEBUG:h5py._conv:Creating converter from 7 to 5
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  89. DEBUG:h5py._conv:Creating converter from 5 to 7
    90. 

  90. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
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  91. DEBUG:h5py._conv:Creating converter from 7 to 5
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  92. DEBUG:h5py._conv:Creating converter from 5 to 7
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  93. DEBUG:h5py._conv:Creating converter from 7 to 5
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  94. DEBUG:h5py._conv:Creating converter from 5 to 7
    95. 

  95. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    96. 

  96. DEBUG:h5py._conv:Creating converter from 7 to 5
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  97. DEBUG:h5py._conv:Creating converter from 5 to 7
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  98. DEBUG:h5py._conv:Creating converter from 7 to 5
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  99. DEBUG:h5py._conv:Creating converter from 5 to 7
    100. 

  100. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    101. 

  101. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
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  102. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    103. 

  103. INFO:root:正在从数据库读取原始数据
    104. 

  104. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    105. 

  105. INFO:root:正在从数据库读取原始数据
    106. 

  106. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    107. 

  107. INFO:root:正在从数据库读取原始数据
    108. 

  108. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    109. 

  109. INFO:root:正在统计原始数据的标签类型
    110. 

  110. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    111. 

  111. INFO:root:正在统计原始数据的标签类型
    112. 

  112. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    113. 

  113. INFO:root:正在统计原始数据的标签类型
    114. 

  114. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    115. 

  115. INFO:root:正在从数据库读取原始数据
    116. 

  116. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    117. 

  117. INFO:root:正在统计原始数据的标签类型
    118. 

  118. INFO:root:正在制作词表
    119. 

  119. INFO:root:正在获取词向量
    120. 

  120. INFO:root:开始训练基础分类器
    121. 

  121. INFO:root:初始分类器准确率为0.6
    122. 

  122. INFO:root:开始第1次重训练
    123. 

  123. INFO:root:开始第2次重训练
    124. 

  124. INFO:root:开始第3次重训练
    125. 

  125. INFO:root:训练完成，测试集准确率为0.7
    126. 

  126. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    127. 

  127. INFO:root:正在从数据库读取原始数据
    128. 

  128. INFO:root:正在统计原始数据的标签类型
    129. 

  129. INFO:root:正在制作词表
    130. 

  130. INFO:root:正在获取词向量
    131. 

  131. INFO:root:开始训练基础分类器
    132. 

  132. INFO:root:初始分类器准确率为0.41346153846153844
    133. 

  133. INFO:root:开始第1次重训练
    134. 

  134. INFO:root:开始第2次重训练
    135. 

  135. INFO:root:训练完成，测试集准确率为0.34615384615384615
    136. 

  136. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    137. 

  137. INFO:root:正在从数据库读取原始数据
    138. 

  138. INFO:root:正在统计原始数据的标签类型
    139. 

  139. INFO:root:正在制作词表
    140. 

  140. INFO:root:正在获取词向量
    141. 

  141. INFO:root:开始训练基础分类器
    142. 

  142. INFO:root:初始分类器准确率为0.41346153846153844
    143. 

  143. INFO:root:开始第1次重训练
    144. 

  144. INFO:root:开始第2次重训练
    145. 

  145. INFO:root:训练完成，测试集准确率为0.34615384615384615
    146. 

  146. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    147. 

  147. INFO:root:正在从数据库读取原始数据
    148. 

  148. INFO:root:正在统计原始数据的标签类型
    149. 

  149. INFO:root:正在制作词表
    150. 

  150. INFO:root:正在获取词向量
    151. 

  151. INFO:root:开始训练基础分类器
    152. 

  152. INFO:root:初始分类器准确率为0.41346153846153844
    153. 

  153. INFO:root:开始第1次重训练
    154. 

  154. INFO:root:开始第2次重训练
    155. 

  155. INFO:root:训练完成，测试集准确率为0.34615384615384615
    156. 

  156. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    157. 

  157. INFO:root:正在从数据库读取原始数据
    158. 

  158. INFO:root:正在统计原始数据的标签类型
    159. 

  159. INFO:root:正在制作词表
    160. 

  160. INFO:root:正在获取词向量
    161. 

  161. INFO:root:开始训练基础分类器
    162. 

  162. INFO:root:初始分类器准确率为0.46464646464646464
    163. 

  163. INFO:root:开始第1次重训练
    164. 

  164. INFO:root:开始第2次重训练
    165. 

  165. INFO:root:开始第3次重训练
    166. 

  166. INFO:root:开始第4次重训练
    167. 

  167. INFO:root:开始第5次重训练
    168. 

  168. INFO:root:开始第6次重训练
    169. 

  169. INFO:root:开始第7次重训练
    170. 

  170. INFO:root:开始第8次重训练
    171. 

  171. INFO:root:开始第9次重训练
    172. 

  172. INFO:root:训练完成，测试集准确率为0.29292929292929293
    173. 

  173. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    174. 

  174. INFO:root:正在统计原始数据的标签类型
    175. 

  175. INFO:root:正在制作词表
    176. 

  176. INFO:root:正在获取词向量
    177. 

  177. INFO:root:开始训练基础分类器
    178. 

  178. INFO:root:初始分类器准确率为0.46464646464646464
    179. 

  179. INFO:root:开始第1次重训练
    180. 

  180. INFO:root:开始第2次重训练
    181. 

  181. INFO:root:开始第3次重训练
    182. 

  182. INFO:root:开始第4次重训练
    183. 

  183. INFO:root:开始第5次重训练
    184. 

  184. INFO:root:开始第6次重训练
    185. 

  185. INFO:root:开始第7次重训练
    186. 

  186. INFO:root:开始第8次重训练
    187. 

  187. INFO:root:开始第9次重训练
    188. 

  188. INFO:root:训练完成，测试集准确率为0.29292929292929293
    189. 

  189. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    190. 

  190. INFO:root:正在统计原始数据的标签类型
    191. 

  191. INFO:root:正在制作词表
    192. 

  192. INFO:root:正在获取词向量
    193. 

  193. INFO:root:开始训练基础分类器
    194. 

  194. INFO:root:初始分类器准确率为0.4748322147651007
    195. 

  195. INFO:root:开始第1次重训练
    196. 

  196. INFO:root:开始第2次重训练
    197. 

  197. INFO:root:开始第3次重训练
    198. 

  198. INFO:root:开始第4次重训练
    199. 

  199. INFO:root:开始第5次重训练
    200. 

  200. INFO:root:开始第6次重训练
    201. 

  201. INFO:root:开始第7次重训练
    202. 

  202. INFO:root:开始第8次重训练
    203. 

  203. INFO:root:开始第9次重训练
    204. 

  204. INFO:root:开始第10次重训练
    205. 

  205. INFO:root:开始第11次重训练
    206. 

  206. INFO:root:开始第12次重训练
    207. 

  207. INFO:root:开始第13次重训练
    208. 

  208. INFO:root:开始第14次重训练
    209. 

  209. INFO:root:开始第15次重训练
    210. 

  210. INFO:root:开始第16次重训练
    211. 

  211. INFO:root:开始第17次重训练
    212. 

  212. INFO:root:训练完成，测试集准确率为0.4429530201342282
    213. 

  213. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    214. 

  214. INFO:root:正在统计原始数据的标签类型
    215. 

  215. INFO:root:正在制作词表
    216. 

  216. INFO:root:正在获取词向量
    217. 

  217. INFO:root:开始训练基础分类器
    218. 

  218. INFO:root:初始分类器准确率为0.508833922261484
    219. 

  219. INFO:root:开始第1次重训练
    220. 

  220. INFO:root:开始第2次重训练
    221. 

  221. INFO:root:开始第3次重训练
    222. 

  222. INFO:root:开始第4次重训练
    223. 

  223. INFO:root:训练完成，测试集准确率为0.508833922261484
    224. 

  224. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    225. 

  225. INFO:root:正在从数据库读取原始数据
    226. 

  226. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    227. 

  227. INFO:root:正在从数据库读取原始数据
    228. 

  228. 09/06/2022 01:21:20 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
    229. 

  229. 09/06/2022 01:21:22 [INFO] data_processor: 正在从数据库读取原始数据
    230. 

  230. 09/06/2022 01:29:13 [INFO] data_processor: 正在对原始数据进行数据扩增
    231. 

  231. 09/06/2022 05:32:20 [INFO] data_processor: 正在统计原始数据的标签类型
    232. 

  232. 09/06/2022 05:32:20 [INFO] data_processor: 正在制作词表
    233. 

  233. 09/06/2022 05:32:20 [INFO] data_processor: 正在获取词向量
    234. 

  234. 09/06/2022 05:32:20 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
    235. 

  235. 09/06/2022 05:32:20 [INFO] bilstm_attention: pytorch 初始化
    236. 

  236. 09/06/2022 05:32:20 [INFO] bilstm_attention: 模型初始化
    237. 

  237. 09/06/2022 05:32:20 [INFO] bilstm_attention: 开始训练基础分类器
    238. 

  238. 09/06/2022 05:32:41 [INFO] bilstm_attention: 初始分类器accuracy为0.5275
    239. 

  239. 09/06/2022 05:32:41 [INFO] bilstm_attention: 初始分类器召回率为0.2619166666666666
    240. 

  240. 09/06/2022 05:32:41 [INFO] bilstm_attention: 初始分类器precision为0.14285416666666667
    241. 

  241. 09/06/2022 05:32:41 [INFO] bilstm_attention: 初始分类器f1_score为0.1802682066489447
    242. 

  242. 09/06/2022 05:32:44 [INFO] bilstm_attention: 开始第1次重训练
    243. 

  243. 09/06/2022 05:33:08 [INFO] bilstm_attention: 开始第2次重训练
    244. 

  244. 09/06/2022 05:33:45 [INFO] bilstm_attention: 开始第3次重训练
    245. 

  245. 09/06/2022 05:34:41 [INFO] bilstm_attention: 开始第4次重训练
    246. 

  246. 09/06/2022 05:35:35 [INFO] bilstm_attention: 开始第5次重训练
    247. 

  247. 09/06/2022 05:37:21 [INFO] bilstm_attention: 训练完成，测试集Accuracy为0.52625
    248. 

  248. 09/06/2022 05:37:21 [INFO] bilstm_attention: 训练完成，测试集召回率为0.2606666666666666
    249. 

  249. 09/06/2022 05:37:21 [INFO] bilstm_attention: 训练完成，测试集Precision为0.13772916666666668
    250. 

  250. 09/06/2022 05:37:21 [INFO] bilstm_attention: 训练完成，测试集f1_score为0.17813833651907454
    251. 

  251. 09/06/2022 05:37:21 [INFO] data_processor: 正在从数据库读取原始数据
    252. 

  252. 09/06/2022 05:42:46 [INFO] data_processor: 正在对原始数据进行数据扩增
    253. 

  253. 09/06/2022 08:59:18 [INFO] data_processor: 正在统计原始数据的标签类型
    254. 

  254. 09/06/2022 08:59:18 [INFO] data_processor: 正在制作词表
    255. 

  255. 09/06/2022 08:59:18 [INFO] data_processor: 正在获取词向量
    256. 

  256. 09/06/2022 08:59:18 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
    257. 

  257. 09/06/2022 08:59:18 [INFO] bilstm_attention: pytorch 初始化
    258. 

  258. 09/06/2022 08:59:18 [INFO] bilstm_attention: 模型初始化
    259. 

  259. 09/06/2022 08:59:18 [INFO] bilstm_attention: 开始训练基础分类器
    260. 

  260. 09/06/2022 08:59:33 [INFO] bilstm_attention: 初始分类器accuracy为0.508833922261484
    261. 

  261. 09/06/2022 08:59:33 [INFO] bilstm_attention: 初始分类器召回率为0.2719521604938271
    262. 

  262. 09/06/2022 08:59:33 [INFO] bilstm_attention: 初始分类器precision为0.1481770833333333
    263. 

  263. 09/06/2022 08:59:33 [INFO] bilstm_attention: 初始分类器f1_score为0.18484307301677788
    264. 

  264. 09/06/2022 08:59:36 [INFO] bilstm_attention: 开始第1次重训练
    265. 

  265. 09/06/2022 09:00:06 [INFO] bilstm_attention: 开始第2次重训练
    266. 

  266. 09/06/2022 09:00:37 [INFO] bilstm_attention: 开始第3次重训练
    267. 

  267. 09/06/2022 09:01:08 [INFO] bilstm_attention: 开始第4次重训练
    268. 

  268. 09/06/2022 09:01:44 [INFO] bilstm_attention: 开始第5次重训练
    269. 

  269. 09/06/2022 09:02:24 [INFO] bilstm_attention: 开始第6次重训练
    270. 

  270. 09/06/2022 09:03:08 [INFO] bilstm_attention: 开始第7次重训练
    271. 

  271. 09/06/2022 09:04:33 [INFO] bilstm_attention: 训练完成，测试集Accuracy为0.508833922261484
    272. 

  272. 09/06/2022 09:04:33 [INFO] bilstm_attention: 训练完成，测试集召回率为0.2717592592592592
    273. 

  273. 09/06/2022 09:04:33 [INFO] bilstm_attention: 训练完成，测试集Precision为0.14042245370370368
    274. 

  274. 09/06/2022 09:04:33 [INFO] bilstm_attention: 训练完成，测试集f1_score为0.18221373733188662
    275. 

  275. 09/06/2022 09:04:33 [INFO] data_processor: 正在从数据库读取原始数据
    276. 

  276. 09/06/2022 09:10:11 [INFO] data_processor: 正在对原始数据进行数据扩增
    277.