2018-08-01 17:47:30,576 : INFO : 'pattern' package not found; tag filters are not available for English
2018-08-01 17:47:30,601 : WARNING : consider setting layer size to a multiple of 4 for greater performance
2018-08-01 17:47:30,601 : INFO : collecting all words and their counts
2018-08-01 17:47:30,602 : INFO : PROGRESS: at sentence #0, processed 0 words, keeping 0 word types
2018-08-01 17:47:31,078 : INFO : PROGRESS: at sentence #10000, processed 167323 words, keeping 10775 word types
2018-08-01 17:47:31,597 : INFO : PROGRESS: at sentence #20000, processed 337953 words, keeping 14875 word types
2018-08-01 17:47:32,073 : INFO : PROGRESS: at sentence #30000, processed 504386 words, keeping 17929 word types
2018-08-01 17:47:32,591 : INFO : PROGRESS: at sentence #40000, processed 672677 words, keeping 20360 word types
2018-08-01 17:47:33,069 : INFO : PROGRESS: at sentence #50000, processed 838714 words, keeping 22384 word types
2018-08-01 17:47:33,625 : INFO : PROGRESS: at sentence #60000, processed 1007231 words, keeping 24214 word types
2018-08-01 17:47:34,148 : INFO : PROGRESS: at sentence #70000, processed 1176928 words, keeping 25953 word types
2018-08-01 17:47:34,699 : INFO : PROGRESS: at sentence #80000, processed 1347696 words, keeping 27344 word types
2018-08-01 17:47:35,232 : INFO : PROGRESS: at sentence #90000, processed 1515603 words, keeping 28654 word types
2018-08-01 17:47:35,757 : INFO : PROGRESS: at sentence #100000, processed 1684215 words, keeping 29798 word types
2018-08-01 17:47:36,257 : INFO : PROGRESS: at sentence #110000, processed 1851656 words, keeping 30972 word types
2018-08-01 17:47:36,706 : INFO : PROGRESS: at sentence #120000, processed 2019944 words, keeping 32061 word types
2018-08-01 17:47:37,224 : INFO : PROGRESS: at sentence #130000, processed 2186466 words, keeping 33055 word types
2018-08-01 17:47:37,744 : INFO : PROGRESS: at sentence #140000, processed 2350487 words, keeping 34025 word types
2018-08-01 17:47:38,269 : INFO : PROGRESS: at sentence #150000, processed 2517582 words, keeping 35054 word types
2018-08-01 17:47:38,839 : INFO : PROGRESS: at sentence #160000, processed 2681587 words, keeping 36016 word types
2018-08-01 17:47:39,358 : INFO : PROGRESS: at sentence #170000, processed 2845437 words, keeping 37059 word types
2018-08-01 17:47:39,872 : INFO : PROGRESS: at sentence #180000, processed 3008970 words, keeping 37928 word types
2018-08-01 17:47:40,415 : INFO : PROGRESS: at sentence #190000, processed 3166438 words, keeping 38880 word types
2018-08-01 17:47:40,900 : INFO : PROGRESS: at sentence #200000, processed 3321032 words, keeping 39764 word types
2018-08-01 17:47:41,390 : INFO : PROGRESS: at sentence #210000, processed 3477570 words, keeping 40675 word types
2018-08-01 17:47:41,818 : INFO : PROGRESS: at sentence #220000, processed 3630568 words, keeping 41398 word types
2018-08-01 17:47:42,305 : INFO : PROGRESS: at sentence #230000, processed 3779627 words, keeping 42077 word types
2018-08-01 17:47:42,775 : INFO : PROGRESS: at sentence #240000, processed 3937296 words, keeping 42819 word types
2018-08-01 17:47:43,264 : INFO : PROGRESS: at sentence #250000, processed 4093719 words, keeping 43498 word types
2018-08-01 17:47:43,714 : INFO : PROGRESS: at sentence #260000, processed 4242694 words, keeping 44153 word types
2018-08-01 17:47:44,092 : INFO : PROGRESS: at sentence #270000, processed 4380578 words, keeping 44840 word types
2018-08-01 17:47:44,510 : INFO : PROGRESS: at sentence #280000, processed 4524518 words, keeping 45453 word types
2018-08-01 17:47:44,952 : INFO : PROGRESS: at sentence #290000, processed 4662325 words, keeping 46050 word types
2018-08-01 17:47:44,965 : INFO : collected 46073 word types from a corpus of 4666151 raw words and 290278 sentences
2018-08-01 17:47:44,965 : INFO : Loading a fresh vocabulary
2018-08-01 17:47:45,204 : INFO : min_count=2 retains 31793 unique words (69% of original 46073, drops 14280)
2018-08-01 17:47:45,204 : INFO : min_count=2 leaves 4651871 word corpus (99% of original 4666151, drops 14280)
2018-08-01 17:47:45,371 : INFO : deleting the raw counts dictionary of 46073 items
2018-08-01 17:47:45,374 : INFO : sample=0.001 downsamples 38 most-common words
2018-08-01 17:47:45,375 : INFO : downsampling leaves estimated 3651068 word corpus (78.5% of prior 4651871)
2018-08-01 17:47:45,548 : INFO : estimated required memory for 31793 words and 50 dimensions: 28613700 bytes
2018-08-01 17:47:45,548 : INFO : resetting layer weights
2018-08-01 17:47:46,064 : INFO : training model with 3 workers on 31793 vocabulary and 50 features, using sg=0 hs=0 sample=0.001 negative=5 window=5
2018-08-01 17:47:46,068 : WARNING : train() called with an empty iterator (if not intended, be sure to provide a corpus that offers restartable iteration = an iterable).
2018-08-01 17:47:46,070 : INFO : worker thread finished; awaiting finish of 2 more threads
2018-08-01 17:47:46,070 : INFO : worker thread finished; awaiting finish of 1 more threads
2018-08-01 17:47:46,070 : INFO : worker thread finished; awaiting finish of 0 more threads
2018-08-01 17:47:46,071 : INFO : EPOCH - 1 : training on 0 raw words (0 effective words) took 0.0s, 0 effective words/s
2018-08-01 17:47:46,073 : WARNING : EPOCH - 1 : supplied example count (0) did not equal expected count (290278)
2018-08-01 17:47:46,076 : WARNING : train() called with an empty iterator (if not intended, be sure to provide a corpus that offers restartable iteration = an iterable).
2018-08-01 17:47:46,076 : INFO : worker thread finished; awaiting finish of 2 more threads
2018-08-01 17:47:46,076 : INFO : worker thread finished; awaiting finish of 1 more threads
2018-08-01 17:47:46,076 : INFO : worker thread finished; awaiting finish of 0 more threads
2018-08-01 17:47:46,076 : INFO : EPOCH - 2 : training on 0 raw words (0 effective words) took 0.0s, 0 effective words/s
2018-08-01 17:47:46,077 : WARNING : EPOCH - 2 : supplied example count (0) did not equal expected count (290278)
2018-08-01 17:47:46,078 : WARNING : train() called with an empty iterator (if not intended, be sure to provide a corpus that offers restartable iteration = an iterable).
2018-08-01 17:47:46,079 : INFO : worker thread finished; awaiting finish of 2 more threads
2018-08-01 17:47:46,079 : INFO : worker thread finished; awaiting finish of 1 more threads
2018-08-01 17:47:46,080 : INFO : worker thread finished; awaiting finish of 0 more threads
2018-08-01 17:47:46,080 : INFO : EPOCH - 3 : training on 0 raw words (0 effective words) took 0.0s, 0 effective words/s
2018-08-01 17:47:46,080 : WARNING : EPOCH - 3 : supplied example count (0) did not equal expected count (290278)
2018-08-01 17:47:46,082 : WARNING : train() called with an empty iterator (if not intended, be sure to provide a corpus that offers restartable iteration = an iterable).
2018-08-01 17:47:46,083 : INFO : worker thread finished; awaiting finish of 2 more threads
2018-08-01 17:47:46,083 : INFO : worker thread finished; awaiting finish of 1 more threads
2018-08-01 17:47:46,083 : INFO : worker thread finished; awaiting finish of 0 more threads
2018-08-01 17:47:46,083 : INFO : EPOCH - 4 : training on 0 raw words (0 effective words) took 0.0s, 0 effective words/s
2018-08-01 17:47:46,084 : WARNING : EPOCH - 4 : supplied example count (0) did not equal expected count (290278)
2018-08-01 17:47:46,085 : WARNING : train() called with an empty iterator (if not intended, be sure to provide a corpus that offers restartable iteration = an iterable).
2018-08-01 17:47:46,086 : INFO : worker thread finished; awaiting finish of 2 more threads
2018-08-01 17:47:46,086 : INFO : worker thread finished; awaiting finish of 1 more threads
2018-08-01 17:47:46,086 : INFO : worker thread finished; awaiting finish of 0 more threads
2018-08-01 17:47:46,086 : INFO : EPOCH - 5 : training on 0 raw words (0 effective words) took 0.0s, 0 effective words/s
2018-08-01 17:47:46,087 : WARNING : EPOCH - 5 : supplied example count (0) did not equal expected count (290278)
2018-08-01 17:47:46,087 : INFO : training on a 0 raw words (0 effective words) took 0.0s, 0 effective words/s
2018-08-01 17:47:46,087 : WARNING : under 10 jobs per worker: consider setting a smaller `batch_words' for smoother alpha decay
2018-08-01 17:47:46,089 : INFO : storing 31793x50 projection weights into E:\word2VecPython\w2v.dat
2018-08-01 17:47:50,389 : INFO : saving Word2Vec object under E:\word2VecPython\model.dat, separately None
2018-08-01 17:47:50,389 : INFO : not storing attribute vectors_norm
2018-08-01 17:47:50,391 : INFO : not storing attribute cum_table
2018-08-01 17:47:50,619 : INFO : saved E:\word2VecPython\model.dat