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jarib/spacy-nlpl-report.txt

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Evaluating NLPL vectors for Spacy
Raw
spacy-nlpl-report.txt
=========
Model 0
=========
Path: data/vectors-all/11-100
Vectors
-------
Algorithm: Gensim Continuous Skipgram
Corpus : Norsk Aviskorpus + NoWaC + NBDigital (lemmatized=False, case preserved=True, tokens=3028545953)
URL : http://vectors.nlpl.eu/repository/11/100.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=4480046
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.532 86.734 87.253 86.993 94.617 100.000
90.355 89.247 89.408 89.327 96.446 100.000
89.914 89.653 89.707 89.680 96.361 100.000
90.173 89.928 89.767 89.847 96.427 100.000
90.593 88.889 89.048 88.969 96.641 100.000
90.581 88.611 88.929 88.769 96.646 100.000
89.569 89.467 89.467 89.467 96.210 100.000
89.274 89.408 89.408 89.408 96.076 100.000
90.267 88.949 89.108 89.028 96.564 100.000
88.150 88.590 88.749 88.670 95.462 100.000
90.543 89.121 89.228 89.175 96.638 100.000
90.593 88.989 88.989 88.989 96.616 100.000
90.638 88.439 88.809 88.623 96.624 100.000
88.635 89.348 89.348 89.348 95.870 100.000
90.618 89.241 89.348 89.294 96.613 100.000
Best
----
Path: data/vectors-all/11-100/training/model-best
Size: 2282 MB
UAS NER P. NER R. NER F. Tag % Token %
90.618 89.241 89.348 89.294 96.613 100.000
Evaluate
--------
Time 3.59 s
Words 30034
Words/s 8373
TOK 100.00
POS 96.01
UAS 90.48
LAS 88.16
NER P 85.24
NER R 86.73
NER F 85.98
=========
Model 1
=========
Path: data/vectors-all/11-104
Vectors
-------
Algorithm: Gensim Continuous Skipgram
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/104.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1728100
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.376 86.499 86.655 86.577 94.609 100.000
90.460 89.701 89.647 89.674 96.342 100.000
89.909 89.844 89.467 89.655 96.276 100.000
90.185 90.030 89.707 89.868 96.298 100.000
90.753 89.256 88.989 89.122 96.501 100.000
90.731 88.836 88.570 88.702 96.495 100.000
89.583 90.102 89.886 89.994 96.191 100.000
89.201 89.946 89.946 89.946 96.109 100.000
90.538 89.682 89.467 89.575 96.356 100.000
88.048 88.889 89.048 88.969 95.582 100.000
90.679 89.202 88.989 89.095 96.397 100.000
90.578 89.162 89.108 89.135 96.482 100.000
90.823 88.989 88.510 88.749 96.526 100.000
88.802 89.433 89.647 89.540 95.881 100.000
90.596 89.222 89.168 89.195 96.402 100.000
Best
----
Path: data/vectors-all/11-104/training/model-best
Size: 890 MB
UAS NER P. NER R. NER F. Tag % Token %
90.596 89.222 89.168 89.195 96.402 100.000
Evaluate
--------
Time 3.57 s
Words 30034
Words/s 8423
TOK 100.00
POS 95.83
UAS 90.43
LAS 88.08
NER P 84.94
NER R 86.30
NER F 85.61
=========
Model 2
=========
Path: data/vectors-all/11-120
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/120.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2551820
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.002 84.852 85.817 85.332 94.677 100.000
90.260 89.181 89.288 89.234 96.424 100.000
89.723 89.892 89.946 89.919 96.342 100.000
90.012 89.826 89.826 89.826 96.424 100.000
90.568 88.432 88.749 88.590 96.537 100.000
90.637 87.798 88.270 88.033 96.531 100.000
89.413 90.078 90.186 90.132 96.282 100.000
89.132 90.000 89.946 89.973 96.166 100.000
90.344 88.605 89.348 88.975 96.520 100.000
88.055 87.908 88.749 88.326 95.607 100.000
90.301 88.757 89.288 89.021 96.556 100.000
90.507 88.452 88.929 88.690 96.531 100.000
90.607 87.738 88.211 87.974 96.528 100.000
88.842 89.511 89.886 89.698 96.005 100.000
90.390 88.757 89.288 89.021 96.605 100.000
Best
----
Path: data/vectors-all/11-120/training/model-best
Size: 1307 MB
UAS NER P. NER R. NER F. Tag % Token %
90.390 88.757 89.288 89.021 96.605 100.000
Evaluate
--------
Time 3.56 s
Words 30034
Words/s 8432
TOK 100.00
POS 95.79
UAS 90.40
LAS 88.14
NER P 85.88
NER R 86.44
NER F 86.16
=========
Model 3
=========
Path: data/vectors-all/11-77
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : Norsk Aviskorpus + NoWaC + NBDigital (lemmatized=False, case preserved=True, tokens=3028545953)
URL : http://vectors.nlpl.eu/repository/11/77.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=4480046
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.988 85.409 86.176 85.791 94.280 100.000
90.085 89.307 89.467 89.387 96.375 100.000
89.662 89.442 89.228 89.335 96.210 100.000
89.904 89.002 89.108 89.055 96.350 100.000
90.710 87.947 88.211 88.079 96.591 100.000
90.813 87.798 88.270 88.033 96.624 100.000
89.255 89.136 88.869 89.002 96.029 100.000
88.937 88.418 88.630 88.524 95.876 100.000
90.290 88.809 88.809 88.809 96.474 100.000
87.782 88.602 88.390 88.496 95.163 100.000
90.552 88.723 88.989 88.856 96.506 100.000
90.721 88.319 88.689 88.504 96.602 100.000
90.859 88.021 88.390 88.205 96.616 100.000
88.530 88.909 88.749 88.829 95.525 100.000
90.642 88.889 89.048 88.969 96.564 100.000
Best
----
Path: data/vectors-all/11-77/training/model-best
Size: 2282 MB
UAS NER P. NER R. NER F. Tag % Token %
90.642 88.889 89.048 88.969 96.564 100.000
Evaluate
--------
Time 3.58 s
Words 30034
Words/s 8396
TOK 100.00
POS 95.76
UAS 90.15
LAS 87.75
NER P 85.20
NER R 86.01
NER F 85.60
=========
Model 4
=========
Path: data/vectors-all/11-92
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/92.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2551819
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.017 84.979 85.996 85.485 93.964 100.000
90.179 89.767 89.767 89.767 96.320 100.000
89.597 89.946 89.946 89.946 96.139 100.000
89.826 89.653 89.707 89.680 96.249 100.000
90.846 88.302 88.091 88.197 96.454 100.000
90.880 87.995 87.732 87.863 96.463 100.000
89.398 89.628 89.467 89.548 96.040 100.000
89.117 89.069 88.749 88.909 95.862 100.000
90.343 89.448 89.288 89.368 96.334 100.000
87.958 87.582 88.211 87.895 95.080 100.000
90.486 89.202 88.989 89.095 96.402 100.000
90.699 88.422 88.211 88.316 96.465 100.000
90.886 86.941 87.253 87.097 96.495 100.000
88.635 88.657 88.869 88.763 95.654 100.000
90.689 88.789 88.630 88.709 96.438 100.000
Best
----
Path: data/vectors-all/11-92/training/model-best
Size: 1307 MB
UAS NER P. NER R. NER F. Tag % Token %
90.689 88.789 88.630 88.709 96.438 100.000
Evaluate
--------
Time 3.58 s
Words 30034
Words/s 8379
TOK 100.00
POS 95.74
UAS 90.44
LAS 88.09
NER P 85.01
NER R 84.77
NER F 84.89
=========
Model 5
=========
Path: data/vectors-all/11-127
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/127.zip
Vectors : dimensions=50, window=5, iterations=5, vocab size=2551820
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.105 85.401 86.116 85.757 94.022 100.000
90.034 88.228 88.809 88.518 96.320 100.000
89.571 88.710 88.869 88.789 96.073 100.000
89.784 88.657 88.869 88.763 96.183 100.000
90.263 86.506 87.852 87.173 96.443 100.000
90.304 86.514 87.911 87.207 96.416 100.000
89.296 88.730 89.048 88.889 96.007 100.000
88.887 89.213 89.587 89.400 95.772 100.000
90.230 88.256 89.048 88.651 96.336 100.000
87.882 87.685 88.630 88.155 95.242 100.000
90.259 88.671 89.467 89.068 96.339 100.000
90.343 87.154 88.510 87.827 96.413 100.000
90.349 86.506 87.852 87.173 96.449 100.000
88.517 88.585 89.168 88.876 95.623 100.000
90.296 88.166 89.168 88.664 96.367 100.000
Best
----
Path: data/vectors-all/11-127/training/model-best
Size: 820 MB
UAS NER P. NER R. NER F. Tag % Token %
90.296 88.166 89.168 88.664 96.367 100.000
Evaluate
--------
Time 3.58 s
Words 30034
Words/s 8393
TOK 100.00
POS 95.75
UAS 90.21
LAS 87.81
NER P 84.70
NER R 85.57
NER F 85.13
=========
Model 6
=========
Path: data/vectors-all/11-81
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus + NoWaC + NBDigital (lemmatized=False, case preserved=True, tokens=3028545953)
URL : http://vectors.nlpl.eu/repository/11/81.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=4428648
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.188 85.875 86.595 86.234 94.595 100.000
90.281 88.929 88.929 88.929 96.430 100.000
89.942 89.102 89.048 89.075 96.336 100.000
90.170 89.301 89.408 89.354 96.394 100.000
90.750 88.763 88.869 88.816 96.534 100.000
90.768 88.790 89.108 88.949 96.619 100.000
89.527 89.269 89.108 89.188 96.213 100.000
89.281 90.030 89.707 89.868 96.035 100.000
90.304 88.696 88.749 88.723 96.463 100.000
87.992 87.612 88.031 87.821 95.481 100.000
90.504 88.802 88.749 88.776 96.526 100.000
90.613 88.323 88.270 88.297 96.602 100.000
90.704 88.763 88.869 88.816 96.616 100.000
88.727 88.544 88.809 88.676 95.862 100.000
90.568 88.683 88.630 88.656 96.528 100.000
Best
----
Path: data/vectors-all/11-81/training/model-best
Size: 2256 MB
UAS NER P. NER R. NER F. Tag % Token %
90.568 88.683 88.630 88.656 96.528 100.000
Evaluate
--------
Time 3.46 s
Words 30034
Words/s 8672
TOK 100.00
POS 95.97
UAS 90.26
LAS 87.85
NER P 85.26
NER R 86.88
NER F 86.06
=========
Model 7
=========
Path: data/vectors-all/11-102
Vectors
-------
Algorithm: Gensim Continuous Skipgram
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/102.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2551819
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.205 84.917 85.577 85.246 94.642 100.000
90.476 89.578 88.989 89.282 96.416 100.000
90.028 90.006 89.467 89.736 96.320 100.000
90.482 89.572 88.929 89.249 96.454 100.000
90.898 88.902 88.689 88.796 96.580 100.000
90.895 88.822 88.450 88.636 96.619 100.000
89.764 89.850 89.527 89.688 96.240 100.000
89.452 89.215 89.108 89.162 96.095 100.000
90.555 89.123 88.749 88.936 96.487 100.000
87.969 87.389 88.330 87.857 95.544 100.000
90.700 88.842 88.630 88.736 96.515 100.000
90.831 87.828 88.091 87.959 96.583 100.000
90.993 88.929 88.450 88.689 96.646 100.000
88.983 88.829 88.989 88.909 95.942 100.000
90.876 88.616 88.510 88.563 96.602 100.000
Best
----
Path: data/vectors-all/11-102/training/model-best
Size: 1307 MB
UAS NER P. NER R. NER F. Tag % Token %
90.876 88.616 88.510 88.563 96.602 100.000
Evaluate
--------
Time 3.56 s
Words 30034
Words/s 8440
TOK 100.00
POS 96.00
UAS 90.14
LAS 87.82
NER P 85.63
NER R 86.44
NER F 86.04
=========
Model 8
=========
Path: data/vectors-all/11-134
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/134.zip
Vectors : dimensions=300, window=5, iterations=5, vocab size=1487994
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.338 85.809 85.398 85.603 93.216 100.000
89.505 88.359 87.672 88.014 95.774 100.000
89.185 88.133 87.552 87.841 95.555 100.000
89.328 88.193 87.612 87.902 95.667 100.000
90.096 87.890 87.732 87.811 95.953 100.000
90.090 87.284 87.493 87.388 95.939 100.000
88.852 88.413 87.672 88.041 95.423 100.000
88.318 88.034 87.612 87.822 95.168 100.000
89.702 88.097 87.253 87.673 95.772 100.000
87.053 87.613 87.193 87.403 94.376 100.000
89.854 88.373 87.792 88.082 95.802 100.000
89.902 88.429 88.270 88.350 95.911 100.000
90.201 86.830 87.193 87.011 95.936 100.000
87.562 87.605 87.552 87.579 94.902 100.000
89.816 88.755 88.330 88.542 95.870 100.000
Best
----
Path: data/vectors-all/11-134/training/model-best
Size: 1904 MB
UAS NER P. NER R. NER F. Tag % Token %
89.816 88.755 88.330 88.542 95.870 100.000
Evaluate
--------
Time 3.50 s
Words 30034
Words/s 8585
TOK 100.00
POS 95.39
UAS 90.08
LAS 87.51
NER P 83.17
NER R 82.51
NER F 82.84
=========
Model 9
=========
Path: data/vectors-all/11-112
Vectors
-------
Algorithm: fastText Continuous Bag-of-Words
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/112.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2551820
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.655 83.453 83.603 83.528 94.230 100.000
90.056 88.655 88.390 88.523 96.391 100.000
89.702 88.949 88.630 88.789 96.221 100.000
89.875 88.496 88.390 88.443 96.367 100.000
90.586 87.104 87.313 87.209 96.559 100.000
90.657 87.276 87.433 87.354 96.567 100.000
89.378 87.634 87.792 87.713 96.112 100.000
89.056 86.881 87.193 87.037 95.955 100.000
90.183 88.722 88.510 88.616 96.438 100.000
87.473 86.555 86.296 86.425 95.240 100.000
90.327 88.676 88.570 88.623 96.476 100.000
90.531 87.343 87.552 87.448 96.583 100.000
90.618 87.104 87.313 87.209 96.600 100.000
88.526 86.718 87.133 86.925 95.700 100.000
90.356 88.702 88.330 88.516 96.559 100.000
Best
----
Path: data/vectors-all/11-112/training/model-best
Size: 1307 MB
UAS NER P. NER R. NER F. Tag % Token %
90.356 88.702 88.330 88.516 96.559 100.000
Evaluate
--------
Time 3.43 s
Words 30034
Words/s 8761
TOK 100.00
POS 95.80
UAS 90.26
LAS 88.05
NER P 84.79
NER R 84.91
NER F 84.85
=========
Model 10
=========
Path: data/vectors-all/11-94
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/94.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1728100
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.250 85.663 86.176 85.919 93.984 100.000
90.362 87.870 88.869 88.367 96.287 100.000
89.829 88.071 88.809 88.439 96.158 100.000
90.070 87.841 88.630 88.234 96.224 100.000
90.975 87.618 88.510 88.062 96.484 100.000
90.986 87.448 88.390 87.917 96.534 100.000
89.488 89.149 88.989 89.069 96.018 100.000
89.265 88.556 88.450 88.503 95.857 100.000
90.475 88.114 89.168 88.638 96.358 100.000
87.988 87.351 87.612 87.481 94.921 100.000
90.748 88.396 89.348 88.869 96.375 100.000
90.896 88.064 88.749 88.405 96.460 100.000
91.036 87.931 88.510 88.220 96.506 100.000
88.894 87.911 87.911 87.911 95.459 100.000
90.713 87.759 88.809 88.281 96.408 100.000
Best
----
Path: data/vectors-all/11-94/training/model-best
Size: 890 MB
UAS NER P. NER R. NER F. Tag % Token %
90.713 87.759 88.809 88.281 96.408 100.000
Evaluate
--------
Time 3.48 s
Words 30034
Words/s 8630
TOK 100.00
POS 95.73
UAS 90.43
LAS 88.07
NER P 85.32
NER R 84.69
NER F 85.00
=========
Model 11
=========
Path: data/vectors-all/11-99
Vectors
-------
Algorithm: Gensim Continuous Skipgram
Corpus : Norsk Aviskorpus + NoWaC + NBDigital (lemmatized=True, case preserved=True, tokens=3028545953)
URL : http://vectors.nlpl.eu/repository/11/99.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=4031460
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.162 85.072 84.919 84.996 93.336 100.000
89.523 87.762 87.552 87.657 95.988 100.000
89.132 87.808 87.493 87.650 95.711 100.000
89.298 88.235 87.971 88.103 95.854 100.000
90.017 87.822 87.612 87.717 96.084 100.000
90.101 88.094 87.672 87.882 96.161 100.000
88.809 88.549 88.390 88.470 95.678 100.000
88.361 88.464 88.570 88.517 95.481 100.000
89.694 87.650 87.493 87.571 96.070 100.000
87.320 87.351 87.612 87.481 94.587 100.000
89.918 87.861 87.493 87.676 96.092 100.000
89.832 88.129 87.971 88.050 96.103 100.000
90.159 88.189 88.031 88.110 96.128 100.000
88.115 88.053 88.211 88.132 95.144 100.000
89.796 88.204 88.151 88.177 96.112 100.000
Best
----
Path: data/vectors-all/11-99/training/model-best
Size: 2055 MB
UAS NER P. NER R. NER F. Tag % Token %
89.796 88.204 88.151 88.177 96.112 100.000
Evaluate
--------
Time 3.53 s
Words 30034
Words/s 8519
TOK 100.00
POS 95.41
UAS 89.82
LAS 87.36
NER P 84.47
NER R 84.84
NER F 84.65
=========
Model 12
=========
Path: data/vectors-all/11-122
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/122.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1728101
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.512 85.850 86.774 86.310 94.601 100.000
90.217 89.600 89.707 89.653 96.427 100.000
89.853 89.247 89.408 89.327 96.287 100.000
89.958 89.587 89.587 89.587 96.342 100.000
90.639 87.803 88.749 88.274 96.523 100.000
90.730 87.953 88.689 88.319 96.561 100.000
89.728 89.719 89.826 89.773 96.183 100.000
89.294 89.341 89.288 89.315 95.961 100.000
90.392 88.519 89.048 88.783 96.479 100.000
88.213 87.329 87.852 87.589 95.440 100.000
90.380 87.796 88.689 88.241 96.520 100.000
90.464 87.640 88.689 88.162 96.515 100.000
90.660 88.651 89.288 88.968 96.583 100.000
88.762 88.333 88.809 88.571 95.818 100.000
90.434 87.640 88.689 88.162 96.506 100.000
Best
----
Path: data/vectors-all/11-122/training/model-best
Size: 890 MB
UAS NER P. NER R. NER F. Tag % Token %
90.434 87.640 88.689 88.162 96.506 100.000
Evaluate
--------
Time 3.41 s
Words 30034
Words/s 8809
TOK 100.00
POS 95.78
UAS 90.23
LAS 87.80
NER P 84.33
NER R 85.13
NER F 84.73
=========
Model 13
=========
Path: data/vectors-all/11-80
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus + NoWaC + NBDigital (lemmatized=True, case preserved=True, tokens=3028545953)
URL : http://vectors.nlpl.eu/repository/11/80.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=3998140
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.153 84.944 85.757 85.348 93.446 100.000
89.932 88.386 88.809 88.597 95.889 100.000
89.513 89.294 89.348 89.321 95.744 100.000
89.596 88.862 89.288 89.075 95.892 100.000
90.281 87.149 87.253 87.201 96.101 100.000
90.297 87.500 87.552 87.526 96.084 100.000
89.098 89.088 89.408 89.247 95.662 100.000
88.770 88.968 89.288 89.128 95.497 100.000
90.096 88.439 88.809 88.623 95.991 100.000
87.119 88.285 88.390 88.337 94.677 100.000
90.001 88.517 88.570 88.543 96.032 100.000
90.307 87.560 87.612 87.586 96.073 100.000
90.284 87.560 87.612 87.586 96.131 100.000
88.004 89.062 89.168 89.115 95.190 100.000
90.138 87.933 88.091 88.012 96.087 100.000
Best
----
Path: data/vectors-all/11-80/training/model-best
Size: 2038 MB
UAS NER P. NER R. NER F. Tag % Token %
90.138 87.933 88.091 88.012 96.087 100.000
Evaluate
--------
Time 3.46 s
Words 30034
Words/s 8690
TOK 100.00
POS 95.37
UAS 89.75
LAS 87.26
NER P 83.30
NER R 85.06
NER F 84.17
=========
Model 14
=========
Path: data/vectors-all/11-101
Vectors
-------
Algorithm: Gensim Continuous Skipgram
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=True, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/101.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2239664
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.231 84.785 85.039 84.912 93.443 100.000
89.621 87.545 87.074 87.309 95.865 100.000
89.110 88.133 87.552 87.841 95.719 100.000
89.294 88.232 87.493 87.861 95.804 100.000
90.091 87.939 86.834 87.383 96.084 100.000
90.221 87.901 86.954 87.425 96.114 100.000
88.845 87.642 87.433 87.537 95.582 100.000
88.403 87.478 87.373 87.425 95.426 100.000
89.657 87.545 87.074 87.309 95.884 100.000
87.204 87.246 87.193 87.219 94.708 100.000
89.619 87.523 86.894 87.207 96.005 100.000
89.905 88.104 87.313 87.707 96.117 100.000
90.164 87.462 86.834 87.147 96.164 100.000
87.891 87.224 87.433 87.328 95.176 100.000
89.752 88.285 87.493 87.887 96.098 100.000
Best
----
Path: data/vectors-all/11-101/training/model-best
Size: 1149 MB
UAS NER P. NER R. NER F. Tag % Token %
89.752 88.285 87.493 87.887 96.098 100.000
Evaluate
--------
Time 3.44 s
Words 30034
Words/s 8735
TOK 100.00
POS 95.37
UAS 90.10
LAS 87.64
NER P 83.50
NER R 84.11
NER F 83.81
=========
Model 15
=========
Path: data/vectors-all/11-132
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/132.zip
Vectors : dimensions=600, window=5, iterations=5, vocab size=1487995
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.307 83.600 84.500 84.048 93.783 100.000
89.725 87.761 87.971 87.866 95.988 100.000
89.200 87.821 88.031 87.926 95.873 100.000
89.507 88.225 88.330 88.278 95.878 100.000
90.111 87.359 88.091 87.723 96.073 100.000
90.185 87.574 88.151 87.862 96.109 100.000
88.919 87.843 88.211 88.026 95.733 100.000
88.704 88.221 88.749 88.484 95.571 100.000
89.962 87.314 87.732 87.522 96.095 100.000
87.441 86.283 86.954 86.617 94.921 100.000
89.947 87.433 87.852 87.642 96.095 100.000
90.058 87.448 87.971 87.709 96.114 100.000
90.310 87.634 88.211 87.921 96.161 100.000
88.188 88.260 88.630 88.444 95.322 100.000
90.000 87.567 88.091 87.828 96.092 100.000
Best
----
Path: data/vectors-all/11-132/training/model-best
Size: 3607 MB
UAS NER P. NER R. NER F. Tag % Token %
90.000 87.567 88.091 87.828 96.092 100.000
Evaluate
--------
Time 3.66 s
Words 30034
Words/s 8208
TOK 100.00
POS 95.44
UAS 89.69
LAS 87.22
NER P 83.31
NER R 84.77
NER F 84.03
=========
Model 16
=========
Path: data/vectors-all/11-131
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/131.zip
Vectors : dimensions=300, window=5, iterations=5, vocab size=1487995
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.184 83.452 84.500 83.973 93.457 100.000
89.692 87.426 87.792 87.608 95.857 100.000
89.296 87.034 87.971 87.500 95.697 100.000
89.410 87.411 88.091 87.750 95.813 100.000
90.102 86.572 87.193 86.881 96.046 100.000
90.250 86.512 87.133 86.822 96.106 100.000
89.006 87.722 88.510 88.114 95.632 100.000
88.667 88.862 88.809 88.836 95.475 100.000
89.840 87.619 88.091 87.854 95.917 100.000
87.278 87.620 87.672 87.646 94.584 100.000
89.941 87.300 88.031 87.664 95.972 100.000
90.050 86.366 87.193 86.778 95.977 100.000
90.258 86.002 86.774 86.387 96.155 100.000
88.147 88.418 88.630 88.524 95.157 100.000
89.986 87.418 88.151 87.783 95.996 100.000
Best
----
Path: data/vectors-all/11-131/training/model-best
Size: 1904 MB
UAS NER P. NER R. NER F. Tag % Token %
89.986 87.418 88.151 87.783 95.996 100.000
Evaluate
--------
Time 3.59 s
Words 30034
Words/s 8357
TOK 100.00
POS 95.36
UAS 89.70
LAS 87.29
NER P 83.79
NER R 85.13
NER F 84.45
=========
Model 17
=========
Path: data/vectors-all/11-76
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : Norsk Aviskorpus + NoWaC + NBDigital (lemmatized=True, case preserved=True, tokens=3028545953)
URL : http://vectors.nlpl.eu/repository/11/76.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=4031460
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.578 85.620 85.159 85.389 92.870 100.000
89.414 87.800 87.433 87.616 95.662 100.000
89.077 87.687 87.792 87.739 95.407 100.000
89.314 87.403 87.193 87.298 95.560 100.000
90.254 87.755 87.493 87.624 95.859 100.000
90.337 87.022 87.074 87.048 95.903 100.000
88.873 87.881 88.091 87.986 95.185 100.000
88.430 87.552 87.971 87.761 94.960 100.000
89.601 87.403 87.193 87.298 95.728 100.000
86.569 86.380 86.535 86.457 94.063 100.000
89.761 87.786 87.313 87.549 95.755 100.000
90.001 86.910 87.014 86.962 95.813 100.000
90.340 87.029 87.133 87.081 95.922 100.000
87.914 87.799 87.852 87.825 94.636 100.000
89.868 88.072 87.493 87.781 95.782 100.000
Best
----
Path: data/vectors-all/11-76/training/model-best
Size: 2055 MB
UAS NER P. NER R. NER F. Tag % Token %
89.868 88.072 87.493 87.781 95.782 100.000
Evaluate
--------
Time 3.58 s
Words 30034
Words/s 8379
TOK 100.00
POS 95.32
UAS 89.68
LAS 87.14
NER P 81.98
NER R 82.58
NER F 82.28
=========
Model 18
=========
Path: data/vectors-all/11-128
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/128.zip
Vectors : dimensions=300, window=5, iterations=5, vocab size=2551820
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.407 84.505 84.859 84.682 94.976 100.000
90.044 88.138 88.929 88.531 96.619 100.000
90.010 88.869 88.869 88.869 96.542 100.000
90.125 88.281 88.809 88.544 96.597 100.000
90.702 88.299 88.510 88.404 96.841 100.000
90.687 88.337 88.390 88.364 96.822 100.000
89.652 89.922 89.707 89.814 96.430 100.000
89.274 88.393 88.869 88.630 96.320 100.000
90.323 87.663 88.450 88.055 96.638 100.000
88.002 88.796 88.689 88.743 95.804 100.000
90.387 87.485 88.270 87.876 96.679 100.000
90.592 87.204 88.091 87.645 96.808 100.000
90.766 88.292 88.450 88.371 96.756 100.000
88.775 89.502 89.288 89.395 96.106 100.000
90.495 87.367 88.151 87.757 96.745 100.000
Best
----
Path: data/vectors-all/11-128/training/model-best
Size: 3254 MB
UAS NER P. NER R. NER F. Tag % Token %
90.495 87.367 88.151 87.757 96.745 100.000
Evaluate
--------
Time 3.65 s
Words 30034
Words/s 8238
TOK 100.00
POS 96.11
UAS 90.31
LAS 87.93
NER P 84.90
NER R 86.08
NER F 85.49
=========
Model 19
=========
Path: data/vectors-all/11-114
Vectors
-------
Algorithm: fastText Continuous Bag-of-Words
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/114.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1728101
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.787 83.393 83.543 83.468 94.206 100.000
89.855 88.748 88.270 88.509 96.397 100.000
89.424 88.896 88.630 88.762 96.175 100.000
89.637 89.002 88.630 88.816 96.284 100.000
90.399 88.041 87.672 87.856 96.520 100.000
90.536 88.242 88.031 88.137 96.556 100.000
89.229 88.715 88.450 88.583 96.038 100.000
88.677 88.589 88.270 88.429 95.909 100.000
90.108 88.422 88.211 88.316 96.512 100.000
87.587 88.175 87.911 88.043 95.264 100.000
90.257 88.635 88.211 88.422 96.512 100.000
90.343 87.695 87.433 87.564 96.474 100.000
90.643 88.729 88.570 88.649 96.572 100.000
88.292 88.316 88.211 88.263 95.673 100.000
90.391 87.830 87.672 87.751 96.501 100.000
Best
----
Path: data/vectors-all/11-114/training/model-best
Size: 890 MB
UAS NER P. NER R. NER F. Tag % Token %
90.391 87.830 87.672 87.751 96.501 100.000
Evaluate
--------
Time 3.42 s
Words 30034
Words/s 8777
TOK 100.00
POS 95.85
UAS 90.34
LAS 87.99
NER P 84.11
NER R 84.48
NER F 84.29
=========
Model 20
=========
Path: data/vectors-all/11-110
Vectors
-------
Algorithm: fastText Continuous Bag-of-Words
Corpus : Norsk Aviskorpus + NoWaC + NBDigital (lemmatized=False, case preserved=True, tokens=3028545953)
URL : http://vectors.nlpl.eu/repository/11/110.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=4428648
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.687 85.324 84.201 84.759 94.145 100.000
90.094 87.974 87.552 87.762 96.372 100.000
89.438 88.427 87.792 88.108 96.254 100.000
89.670 88.087 87.612 87.849 96.271 100.000
90.674 87.582 87.373 87.478 96.512 100.000
90.783 87.786 87.313 87.549 96.539 100.000
89.172 88.288 87.971 88.129 96.054 100.000
88.683 87.978 88.031 88.005 95.889 100.000
90.262 88.348 88.031 88.189 96.421 100.000
87.495 85.963 85.757 85.860 95.231 100.000
90.421 88.197 88.091 88.144 96.438 100.000
90.588 87.149 87.253 87.201 96.517 100.000
90.919 87.530 86.954 87.241 96.526 100.000
88.373 86.464 86.774 86.619 95.588 100.000
90.461 87.770 87.612 87.691 96.484 100.000
Best
----
Path: data/vectors-all/11-110/training/model-best
Size: 2256 MB
UAS NER P. NER R. NER F. Tag % Token %
90.461 87.770 87.612 87.691 96.484 100.000
Evaluate
--------
Time 3.58 s
Words 30034
Words/s 8389
TOK 100.00
POS 95.96
UAS 90.26
LAS 87.96
NER P 83.12
NER R 83.97
NER F 83.54
=========
Model 21
=========
Path: data/vectors-all/11-135
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/135.zip
Vectors : dimensions=600, window=5, iterations=5, vocab size=1487994
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.807 83.742 83.842 83.792 93.457 100.000
89.551 88.480 87.792 88.135 95.728 100.000
88.830 89.264 88.570 88.916 95.618 100.000
89.053 88.634 87.732 88.180 95.670 100.000
90.000 88.072 87.493 87.781 95.944 100.000
90.023 88.452 87.552 88.000 95.972 100.000
88.587 89.426 88.570 88.996 95.421 100.000
88.353 88.628 88.151 88.389 95.242 100.000
89.750 88.036 87.193 87.613 95.846 100.000
86.718 89.307 87.971 88.634 94.516 100.000
89.910 88.324 87.373 87.846 95.870 100.000
90.061 88.324 87.373 87.846 95.966 100.000
90.006 87.680 87.313 87.496 95.988 100.000
87.660 88.608 87.971 88.288 95.020 100.000
90.094 88.082 87.133 87.605 95.925 100.000
Best
----
Path: data/vectors-all/11-135/training/model-best
Size: 3607 MB
UAS NER P. NER R. NER F. Tag % Token %
90.094 88.082 87.133 87.605 95.925 100.000
Evaluate
--------
Time 3.68 s
Words 30034
Words/s 8169
TOK 100.00
POS 95.44
UAS 89.54
LAS 86.75
NER P 84.26
NER R 83.89
NER F 84.08
=========
Model 22
=========
Path: data/vectors-all/11-91
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=True, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/91.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2239664
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.582 85.731 85.577 85.654 92.577 100.000
89.377 89.078 87.852 88.460 95.563 100.000
88.803 88.620 87.612 88.113 95.349 100.000
89.124 88.848 87.732 88.287 95.473 100.000
89.717 87.833 86.834 87.331 95.796 100.000
89.872 87.636 86.954 87.293 95.824 100.000
88.469 88.459 87.612 88.034 95.157 100.000
88.003 88.087 87.612 87.849 94.924 100.000
89.357 88.494 87.911 88.202 95.610 100.000
86.585 87.485 87.433 87.459 94.069 100.000
89.707 88.459 87.612 88.034 95.703 100.000
89.693 87.795 86.954 87.372 95.793 100.000
89.977 88.089 87.193 87.639 95.799 100.000
87.566 88.334 87.911 88.122 94.554 100.000
89.694 87.923 87.133 87.526 95.736 100.000
Best
----
Path: data/vectors-all/11-91/training/model-best
Size: 1149 MB
UAS NER P. NER R. NER F. Tag % Token %
89.694 87.923 87.133 87.526 95.736 100.000
Evaluate
--------
Time 3.44 s
Words 30034
Words/s 8740
TOK 100.00
POS 95.34
UAS 89.78
LAS 87.23
NER P 83.69
NER R 83.02
NER F 83.35
=========
Model 23
=========
Path: data/vectors-all/11-103
Vectors
-------
Algorithm: Gensim Continuous Skipgram
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/103.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1487994
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.676 84.258 84.560 84.409 93.169 100.000
89.413 89.230 88.749 88.989 95.829 100.000
89.213 87.097 87.253 87.175 95.654 100.000
89.334 88.882 88.510 88.696 95.772 100.000
90.021 87.793 87.373 87.582 95.939 100.000
90.184 87.545 87.074 87.309 95.963 100.000
88.927 87.485 87.433 87.459 95.459 100.000
88.361 88.448 87.971 88.209 95.341 100.000
89.777 88.182 87.971 88.077 95.895 100.000
87.089 86.209 86.415 86.312 94.592 100.000
89.867 87.590 87.433 87.511 95.873 100.000
90.022 87.553 87.133 87.343 95.944 100.000
90.217 88.399 87.552 87.974 96.029 100.000
87.858 88.608 87.971 88.288 95.034 100.000
90.023 87.463 87.253 87.358 95.903 100.000
Best
----
Path: data/vectors-all/11-103/training/model-best
Size: 768 MB
UAS NER P. NER R. NER F. Tag % Token %
90.023 87.463 87.253 87.358 95.903 100.000
Evaluate
--------
Time 3.41 s
Words 30034
Words/s 8803
TOK 100.00
POS 95.31
UAS 89.78
LAS 87.25
NER P 84.45
NER R 84.33
NER F 84.39
=========
Model 24
=========
Path: data/vectors-all/11-95
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : NoWaC (lemmatized=True, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/95.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1199274
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.346 82.656 81.568 82.108 92.574 100.000
89.379 86.301 85.577 85.938 95.495 100.000
88.785 85.360 84.440 84.898 95.256 100.000
89.097 85.844 84.919 85.379 95.374 100.000
89.843 86.783 86.056 86.418 95.733 100.000
89.923 85.860 85.398 85.629 95.769 100.000
88.499 86.809 85.458 86.128 95.042 100.000
88.021 86.659 85.518 86.084 94.845 100.000
89.490 85.989 85.577 85.783 95.574 100.000
86.353 84.151 84.201 84.176 93.970 100.000
89.669 87.772 86.774 87.271 95.640 100.000
89.817 87.304 86.415 86.857 95.711 100.000
89.985 85.817 85.458 85.637 95.785 100.000
87.243 85.646 85.697 85.672 94.477 100.000
89.720 87.485 86.595 87.038 95.667 100.000
Best
----
Path: data/vectors-all/11-95/training/model-best
Size: 619 MB
UAS NER P. NER R. NER F. Tag % Token %
89.720 87.485 86.595 87.038 95.667 100.000
Evaluate
--------
Time 3.39 s
Words 30034
Words/s 8866
TOK 100.00
POS 95.27
UAS 89.61
LAS 86.99
NER P 79.36
NER R 79.88
NER F 79.62
=========
Model 25
=========
Path: data/vectors-all/11-111
Vectors
-------
Algorithm: fastText Continuous Bag-of-Words
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=True, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/111.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2239665
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
83.944 82.074 81.927 82.001 92.344 100.000
89.262 87.500 86.715 87.106 95.580 100.000
88.797 87.795 86.954 87.372 95.336 100.000
89.070 87.651 86.655 87.150 95.459 100.000
89.623 87.651 87.074 87.361 95.837 100.000
89.759 87.492 87.074 87.283 95.857 100.000
88.511 88.424 87.313 87.865 95.171 100.000
87.991 87.983 87.193 87.586 94.875 100.000
89.301 86.951 86.535 86.743 95.566 100.000
86.128 87.083 85.937 86.506 93.912 100.000
89.398 87.124 86.655 86.889 95.580 100.000
89.643 86.943 86.475 86.709 95.777 100.000
89.871 87.500 86.715 87.106 95.898 100.000
87.404 87.923 87.133 87.526 94.477 100.000
89.465 87.297 86.774 87.035 95.662 100.000
Best
----
Path: data/vectors-all/11-111/training/model-best
Size: 1149 MB
UAS NER P. NER R. NER F. Tag % Token %
89.465 87.297 86.774 87.035 95.662 100.000
Evaluate
--------
Time 3.45 s
Words 30034
Words/s 8709
TOK 100.00
POS 95.21
UAS 89.70
LAS 87.19
NER P 83.88
NER R 82.65
NER F 83.26
=========
Model 26
=========
Path: data/vectors-all/11-129
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/129.zip
Vectors : dimensions=600, window=5, iterations=5, vocab size=2551820
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.817 85.867 86.535 86.200 95.171 100.000
90.257 87.850 88.270 88.060 96.794 100.000
90.018 88.375 89.168 88.770 96.709 100.000
90.188 87.945 88.630 88.286 96.748 100.000
90.852 87.455 88.031 87.742 96.866 100.000
90.913 87.396 87.971 87.683 96.816 100.000
89.631 89.922 90.245 90.084 96.630 100.000
89.405 89.618 89.886 89.752 96.441 100.000
90.624 87.196 88.031 87.612 96.789 100.000
87.982 89.386 89.707 89.546 95.961 100.000
90.744 86.469 87.193 86.830 96.822 100.000
90.868 86.722 87.552 87.135 96.835 100.000
90.789 87.158 87.732 87.444 96.846 100.000
88.774 89.672 89.886 89.779 96.293 100.000
90.826 86.469 87.193 86.830 96.835 100.000
Best
----
Path: data/vectors-all/11-129/training/model-best
Size: 6175 MB
UAS NER P. NER R. NER F. Tag % Token %
90.826 86.469 87.193 86.830 96.835 100.000
Evaluate
--------
Time 3.69 s
Words 30034
Words/s 8141
TOK 100.00
POS 96.24
UAS 90.48
LAS 88.16
NER P 84.73
NER R 85.35
NER F 85.04
=========
Model 27
=========
Path: data/vectors-all/11-93
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/93.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1487994
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.385 84.796 84.440 84.618 92.623 100.000
89.282 88.394 87.971 88.182 95.588 100.000
88.621 88.492 87.433 87.959 95.346 100.000
88.926 88.775 88.031 88.401 95.470 100.000
89.811 86.771 86.355 86.563 95.837 100.000
89.852 86.928 86.355 86.641 95.895 100.000
88.126 88.620 87.612 88.113 95.198 100.000
87.847 88.767 87.493 88.125 95.009 100.000
89.296 87.387 87.074 87.230 95.654 100.000
86.524 87.750 86.595 87.169 93.995 100.000
89.508 86.407 86.355 86.381 95.708 100.000
89.701 86.607 86.296 86.451 95.761 100.000
89.805 87.184 86.715 86.949 95.920 100.000
87.399 88.239 87.552 87.894 94.653 100.000
89.670 86.923 86.715 86.818 95.766 100.000
Best
----
Path: data/vectors-all/11-93/training/model-best
Size: 768 MB
UAS NER P. NER R. NER F. Tag % Token %
89.670 86.923 86.715 86.818 95.766 100.000
Evaluate
--------
Time 3.43 s
Words 30034
Words/s 8744
TOK 100.00
POS 95.20
UAS 89.78
LAS 87.20
NER P 81.53
NER R 80.76
NER F 81.14
=========
Model 28
=========
Path: data/vectors-all/11-79
Vectors
-------
Algorithm: Global Vectors
Corpus : Norsk Aviskorpus + NoWaC + NBDigital (lemmatized=False, case preserved=True, tokens=3028545953)
URL : http://vectors.nlpl.eu/repository/11/79.zip
Vectors : dimensions=100, window=15, iterations=25, vocab size=4480047
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.631 84.444 84.141 84.293 94.008 100.000
89.532 86.456 86.715 86.585 96.131 100.000
89.306 86.575 86.834 86.705 95.939 100.000
89.419 86.575 86.834 86.705 96.051 100.000
90.244 86.837 87.253 87.045 96.356 100.000
90.252 86.853 87.373 87.112 96.361 100.000
88.999 86.266 86.834 86.549 95.862 100.000
88.587 86.623 87.193 86.907 95.741 100.000
89.787 86.437 86.954 86.695 96.175 100.000
86.993 85.714 86.535 86.123 95.130 100.000
89.893 86.464 86.774 86.619 96.293 100.000
90.209 86.718 87.133 86.925 96.364 100.000
90.444 87.112 87.373 87.242 96.391 100.000
87.922 86.310 86.774 86.541 95.525 100.000
90.037 86.643 86.954 86.798 96.339 100.000
Best
----
Path: data/vectors-all/11-79/training/model-best
Size: 2282 MB
UAS NER P. NER R. NER F. Tag % Token %
90.037 86.643 86.954 86.798 96.339 100.000
Evaluate
--------
Time 3.55 s
Words 30034
Words/s 8470
TOK 100.00
POS 95.64
UAS 90.06
LAS 87.60
NER P 84.39
NER R 84.33
NER F 84.36
=========
Model 29
=========
Path: data/vectors-all/11-109
Vectors
-------
Algorithm: fastText Continuous Bag-of-Words
Corpus : Norsk Aviskorpus + NoWaC + NBDigital (lemmatized=True, case preserved=True, tokens=3028545953)
URL : http://vectors.nlpl.eu/repository/11/109.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=3998140
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.257 82.145 82.047 82.096 92.484 100.000
89.317 85.851 86.056 85.953 95.645 100.000
88.850 86.201 86.355 86.278 95.412 100.000
89.033 86.106 86.415 86.260 95.516 100.000
89.895 86.186 85.877 86.031 95.914 100.000
89.903 86.615 86.355 86.485 95.939 100.000
88.497 86.252 86.355 86.304 95.248 100.000
87.933 85.970 86.176 86.073 94.976 100.000
89.546 86.418 86.056 86.237 95.752 100.000
86.561 85.331 85.637 85.484 94.025 100.000
89.647 87.079 86.715 86.897 95.777 100.000
89.813 86.350 85.937 86.143 95.887 100.000
90.056 86.040 85.937 85.988 95.977 100.000
87.627 86.149 86.355 86.252 94.606 100.000
89.828 86.951 86.535 86.743 95.848 100.000
Best
----
Path: data/vectors-all/11-109/training/model-best
Size: 2038 MB
UAS NER P. NER R. NER F. Tag % Token %
89.828 86.951 86.535 86.743 95.848 100.000
Evaluate
--------
Time 3.59 s
Words 30034
Words/s 8374
TOK 100.00
POS 95.23
UAS 89.71
LAS 87.27
NER P 82.47
NER R 81.92
NER F 82.19
=========
Model 30
=========
Path: data/vectors-all/11-130
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/130.zip
Vectors : dimensions=50, window=5, iterations=5, vocab size=1487995
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.487 85.042 84.381 84.710 92.911 100.000
89.574 87.133 87.133 87.133 95.591 100.000
88.988 87.957 87.852 87.904 95.467 100.000
89.217 87.470 87.313 87.391 95.555 100.000
89.958 87.019 86.655 86.837 95.824 100.000
90.050 86.766 86.715 86.740 95.884 100.000
88.488 87.658 87.133 87.395 95.319 100.000
88.107 88.079 87.552 87.815 95.086 100.000
89.636 86.516 86.774 86.645 95.673 100.000
86.682 86.033 85.518 85.774 94.225 100.000
89.771 86.483 86.535 86.509 95.755 100.000
89.864 86.639 86.535 86.587 95.788 100.000
90.117 86.619 86.774 86.697 95.895 100.000
87.389 86.426 86.116 86.271 94.779 100.000
89.824 86.655 86.655 86.655 95.758 100.000
Best
----
Path: data/vectors-all/11-130/training/model-best
Size: 485 MB
UAS NER P. NER R. NER F. Tag % Token %
89.824 86.655 86.655 86.655 95.758 100.000
Evaluate
--------
Time 3.38 s
Words 30034
Words/s 8876
TOK 100.00
POS 95.32
UAS 89.60
LAS 87.05
NER P 81.69
NER R 82.29
NER F 81.99
=========
Model 31
=========
Path: data/vectors-all/11-124
Vectors
-------
Algorithm: fastText Skipgram
Corpus : NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/124.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1356633
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.837 82.349 83.483 82.912 94.302 100.000
90.065 85.179 85.637 85.407 96.282 100.000
89.637 86.923 86.715 86.818 96.153 100.000
89.878 86.423 86.475 86.449 96.188 100.000
90.373 85.858 86.834 86.343 96.410 100.000
90.462 85.740 86.715 86.224 96.465 100.000
89.524 87.050 86.894 86.972 96.070 100.000
89.164 86.715 86.715 86.715 95.840 100.000
90.160 86.190 86.655 86.422 96.323 100.000
87.852 84.375 85.637 85.001 95.272 100.000
90.190 85.900 86.774 86.335 96.339 100.000
90.353 85.655 86.475 86.063 96.410 100.000
90.579 84.593 85.757 85.171 96.427 100.000
88.656 86.347 86.296 86.321 95.612 100.000
90.301 86.154 87.133 86.641 96.402 100.000
Best
----
Path: data/vectors-all/11-124/training/model-best
Size: 699 MB
UAS NER P. NER R. NER F. Tag % Token %
90.301 86.154 87.133 86.641 96.402 100.000
Evaluate
--------
Time 3.41 s
Words 30034
Words/s 8806
TOK 100.00
POS 95.79
UAS 90.22
LAS 87.76
NER P 84.18
NER R 85.35
NER F 84.76
=========
Model 32
=========
Path: data/vectors-all/11-121
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/121.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1487995
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.958 83.983 85.039 84.508 93.136 100.000
89.463 86.420 86.834 86.627 95.747 100.000
88.906 86.556 87.074 86.814 95.563 100.000
89.180 86.651 87.014 86.832 95.648 100.000
89.846 86.837 87.253 87.045 95.920 100.000
89.938 86.350 87.074 86.710 95.909 100.000
88.614 86.837 87.253 87.045 95.437 100.000
88.415 87.143 87.612 87.377 95.256 100.000
89.575 86.382 87.313 86.845 95.829 100.000
87.049 86.213 87.193 86.700 94.491 100.000
89.729 86.536 87.313 86.923 95.859 100.000
89.724 86.207 86.774 86.490 95.876 100.000
89.950 85.994 86.715 86.353 95.936 100.000
87.853 88.218 88.270 88.244 94.971 100.000
89.740 86.377 86.894 86.635 95.826 100.000
Best
----
Path: data/vectors-all/11-121/training/model-best
Size: 768 MB
UAS NER P. NER R. NER F. Tag % Token %
89.740 86.377 86.894 86.635 95.826 100.000
Evaluate
--------
Time 3.35 s
Words 30034
Words/s 8955
TOK 100.00
POS 95.32
UAS 89.84
LAS 87.37
NER P 81.80
NER R 82.87
NER F 82.33
=========
Model 33
=========
Path: data/vectors-all/11-113
Vectors
-------
Algorithm: fastText Continuous Bag-of-Words
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/113.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1487995
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.198 82.842 82.346 82.593 92.163 100.000
89.056 87.432 86.595 87.011 95.412 100.000
88.717 87.167 86.176 86.669 95.171 100.000
88.807 87.417 86.475 86.943 95.303 100.000
89.813 86.590 86.176 86.383 95.725 100.000
89.855 86.470 86.056 86.263 95.755 100.000
88.338 86.470 86.056 86.263 94.993 100.000
87.731 86.582 86.116 86.349 94.732 100.000
89.123 87.326 86.595 86.959 95.459 100.000
86.205 86.917 85.877 86.394 93.676 100.000
89.237 87.243 86.355 86.797 95.547 100.000
89.699 86.679 86.056 86.366 95.678 100.000
89.958 86.538 86.176 86.357 95.793 100.000
87.165 87.130 86.296 86.711 94.389 100.000
89.546 87.009 86.176 86.590 95.637 100.000
Best
----
Path: data/vectors-all/11-113/training/model-best
Size: 768 MB
UAS NER P. NER R. NER F. Tag % Token %
89.546 87.009 86.176 86.590 95.637 100.000
Evaluate
--------
Time 3.46 s
Words 30034
Words/s 8693
TOK 100.00
POS 95.12
UAS 89.70
LAS 87.25
NER P 81.61
NER R 82.14
NER F 81.87
=========
Model 34
=========
Path: data/vectors-all/11-116
Vectors
-------
Algorithm: fastText Continuous Bag-of-Words
Corpus : NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/116.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1356633
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.438 80.904 80.371 80.636 94.217 100.000
90.048 88.097 87.253 87.673 96.287 100.000
89.521 86.936 86.415 86.675 95.996 100.000
89.856 87.538 87.014 87.275 96.172 100.000
90.653 86.030 86.236 86.133 96.424 100.000
90.734 85.979 86.236 86.107 96.512 100.000
89.192 85.612 85.817 85.714 95.958 100.000
88.851 85.161 85.518 85.339 95.846 100.000
90.173 87.019 86.655 86.837 96.287 100.000
87.459 84.796 84.440 84.618 95.281 100.000
90.253 86.923 86.715 86.818 96.317 100.000
90.660 86.871 86.715 86.792 96.449 100.000
90.668 85.689 85.996 85.842 96.520 100.000
88.519 84.707 84.859 84.783 95.662 100.000
90.431 86.467 86.415 86.441 96.397 100.000
Best
----
Path: data/vectors-all/11-116/training/model-best
Size: 699 MB
UAS NER P. NER R. NER F. Tag % Token %
90.431 86.467 86.415 86.441 96.397 100.000
Evaluate
--------
Time 3.58 s
Words 30034
Words/s 8396
TOK 100.00
POS 95.73
UAS 89.86
LAS 87.43
NER P 82.16
NER R 83.24
NER F 82.69
=========
Model 35
=========
Path: data/vectors-all/11-133
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/133.zip
Vectors : dimensions=50, window=5, iterations=5, vocab size=1487994
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.537 83.524 83.124 83.323 92.248 100.000
89.156 86.520 87.193 86.855 95.286 100.000
88.428 87.808 87.493 87.650 95.146 100.000
88.914 85.859 86.475 86.166 95.193 100.000
89.853 86.480 86.894 86.687 95.618 100.000
89.938 86.480 86.894 86.687 95.621 100.000
88.304 86.535 86.535 86.535 94.946 100.000
87.858 86.073 86.176 86.124 94.686 100.000
89.343 86.215 86.834 86.524 95.371 100.000
86.389 86.511 86.355 86.433 93.687 100.000
89.442 86.472 86.834 86.653 95.451 100.000
89.706 86.071 86.535 86.303 95.588 100.000
90.086 86.096 86.715 86.404 95.673 100.000
87.427 87.230 87.074 87.152 94.222 100.000
89.656 86.147 86.715 86.430 95.533 100.000
Best
----
Path: data/vectors-all/11-133/training/model-best
Size: 485 MB
UAS NER P. NER R. NER F. Tag % Token %
89.656 86.147 86.715 86.430 95.533 100.000
Evaluate
--------
Time 3.56 s
Words 30034
Words/s 8432
TOK 100.00
POS 95.13
UAS 89.53
LAS 86.96
NER P 81.30
NER R 81.12
NER F 81.21
=========
Model 36
=========
Path: data/vectors-all/11-106
Vectors
-------
Algorithm: Gensim Continuous Skipgram
Corpus : NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/106.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1356632
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.333 84.552 85.817 85.180 94.505 100.000
90.271 86.098 86.355 86.226 96.413 100.000
89.907 87.463 87.253 87.358 96.265 100.000
90.023 86.691 86.535 86.613 96.364 100.000
90.628 86.293 86.655 86.474 96.564 100.000
90.699 85.918 86.535 86.225 96.597 100.000
89.579 88.144 88.091 88.117 96.147 100.000
89.271 88.316 88.211 88.263 96.062 100.000
90.232 86.073 86.176 86.124 96.424 100.000
88.039 86.853 87.373 87.112 95.440 100.000
90.394 86.388 86.595 86.491 96.463 100.000
90.585 86.020 86.535 86.277 96.526 100.000
90.775 85.901 86.415 86.158 96.676 100.000
88.764 87.978 88.031 88.005 95.818 100.000
90.573 86.139 86.655 86.396 96.517 100.000
Best
----
Path: data/vectors-all/11-106/training/model-best
Size: 699 MB
UAS NER P. NER R. NER F. Tag % Token %
90.573 86.139 86.655 86.396 96.517 100.000
Evaluate
--------
Time 3.54 s
Words 30034
Words/s 8484
TOK 100.00
POS 95.79
UAS 89.84
LAS 87.45
NER P 83.24
NER R 84.33
NER F 83.78
=========
Model 37
=========
Path: data/vectors-all/11-96
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/96.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1356632
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
86.090 84.086 84.740 84.411 94.036 100.000
90.101 86.516 86.774 86.645 96.144 100.000
89.915 86.201 86.355 86.278 95.996 100.000
90.023 86.635 86.894 86.764 96.098 100.000
90.561 86.049 85.637 85.843 96.314 100.000
90.615 86.315 86.056 86.185 96.347 100.000
89.427 86.176 86.176 86.176 95.857 100.000
89.160 87.815 87.552 87.684 95.717 100.000
90.316 86.114 86.475 86.294 96.309 100.000
87.621 86.826 86.774 86.800 94.979 100.000
90.528 86.823 86.355 86.589 96.271 100.000
90.637 86.394 85.877 86.134 96.284 100.000
90.765 86.506 85.937 86.220 96.361 100.000
88.631 87.207 86.894 87.050 95.382 100.000
90.605 86.590 86.176 86.383 96.290 100.000
Best
----
Path: data/vectors-all/11-96/training/model-best
Size: 699 MB
UAS NER P. NER R. NER F. Tag % Token %
90.605 86.590 86.176 86.383 96.290 100.000
Evaluate
--------
Time 3.61 s
Words 30034
Words/s 8326
TOK 100.00
POS 95.79
UAS 90.29
LAS 88.00
NER P 80.01
NER R 80.54
NER F 80.28
=========
Model 38
=========
Path: data/vectors-all/11-84
Vectors
-------
Algorithm: Global Vectors
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/84.zip
Vectors : dimensions=100, window=15, iterations=25, vocab size=2551820
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.227 83.682 83.782 83.732 93.901 100.000
89.621 86.166 86.475 86.320 96.155 100.000
89.081 86.285 86.595 86.440 96.038 100.000
89.407 86.404 86.715 86.559 96.103 100.000
89.958 86.285 86.595 86.440 96.328 100.000
90.018 85.595 86.056 85.825 96.331 100.000
88.806 86.853 87.373 87.112 95.925 100.000
88.477 86.830 87.193 87.011 95.807 100.000
89.776 86.345 86.655 86.499 96.202 100.000
86.864 86.141 86.296 86.218 95.037 100.000
89.853 86.551 86.655 86.603 96.279 100.000
90.031 86.013 86.116 86.065 96.320 100.000
90.116 85.467 85.518 85.492 96.353 100.000
87.956 86.207 86.774 86.490 95.464 100.000
89.976 86.209 86.415 86.312 96.323 100.000
Best
----
Path: data/vectors-all/11-84/training/model-best
Size: 1307 MB
UAS NER P. NER R. NER F. Tag % Token %
89.976 86.209 86.415 86.312 96.323 100.000
Evaluate
--------
Time 3.60 s
Words 30034
Words/s 8346
TOK 100.00
POS 95.56
UAS 89.67
LAS 87.21
NER P 83.19
NER R 84.77
NER F 83.97
=========
Model 39
=========
Path: data/vectors-all/11-119
Vectors
-------
Algorithm: fastText Skipgram
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=True, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/119.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2239665
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.225 84.766 85.577 85.170 93.306 100.000
89.569 86.817 87.493 87.154 95.917 100.000
89.285 87.986 88.091 88.038 95.714 100.000
89.351 86.690 87.313 87.001 95.837 100.000
90.125 86.485 87.313 86.897 96.090 100.000
90.188 86.509 87.493 86.998 96.087 100.000
88.989 88.270 88.270 88.270 95.659 100.000
88.790 87.634 87.792 87.713 95.401 100.000
89.711 86.207 86.774 86.490 95.920 100.000
87.163 87.008 87.373 87.190 94.570 100.000
89.816 86.123 86.535 86.328 95.999 100.000
89.969 85.918 86.535 86.225 96.081 100.000
90.134 86.493 87.373 86.931 96.106 100.000
88.293 87.866 87.971 87.919 95.094 100.000
89.968 85.977 86.595 86.285 96.027 100.000
Best
----
Path: data/vectors-all/11-119/training/model-best
Size: 1149 MB
UAS NER P. NER R. NER F. Tag % Token %
89.968 85.977 86.595 86.285 96.027 100.000
Evaluate
--------
Time 3.51 s
Words 30034
Words/s 8559
TOK 100.00
POS 95.55
UAS 89.74
LAS 87.17
NER P 84.38
NER R 85.42
NER F 84.90
=========
Model 40
=========
Path: data/vectors-all/11-126
Vectors
-------
Algorithm: fastText Skipgram
Corpus : NBDigital (lemmatized=False, case preserved=True, tokens=813922111)
URL : http://vectors.nlpl.eu/repository/11/126.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2390584
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.517 83.504 83.004 83.253 94.022 100.000
89.911 86.197 85.577 85.886 95.966 100.000
89.518 86.518 85.637 86.075 95.873 100.000
89.892 86.292 85.518 85.903 95.950 100.000
90.174 85.620 85.518 85.569 96.120 100.000
90.225 85.749 85.338 85.543 96.131 100.000
89.113 86.928 86.355 86.641 95.788 100.000
88.694 86.933 85.996 86.462 95.618 100.000
90.036 86.498 85.877 86.186 95.974 100.000
87.601 84.934 84.680 84.807 95.048 100.000
89.974 86.024 85.458 85.740 96.051 100.000
90.126 85.851 85.697 85.774 96.090 100.000
90.310 85.646 85.338 85.492 96.144 100.000
88.405 85.757 85.398 85.577 95.429 100.000
89.986 86.109 85.697 85.903 96.065 100.000
Best
----
Path: data/vectors-all/11-126/training/model-best
Size: 1221 MB
UAS NER P. NER R. NER F. Tag % Token %
89.986 86.109 85.697 85.903 96.065 100.000
Evaluate
--------
Time 3.64 s
Words 30034
Words/s 8262
TOK 100.00
POS 95.63
UAS 89.79
LAS 87.37
NER P 79.94
NER R 81.63
NER F 80.78
=========
Model 41
=========
Path: data/vectors-all/11-86
Vectors
-------
Algorithm: Global Vectors
Corpus : Norsk Aviskorpus (lemmatized=False, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/86.zip
Vectors : dimensions=100, window=15, iterations=25, vocab size=1728101
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.610 83.442 84.440 83.938 93.863 100.000
89.268 85.748 86.056 85.902 96.114 100.000
88.806 87.815 87.552 87.684 95.961 100.000
89.051 86.055 86.415 86.235 96.070 100.000
89.994 86.174 86.535 86.354 96.304 100.000
90.134 86.182 86.595 86.388 96.312 100.000
88.641 87.590 87.433 87.511 95.832 100.000
88.313 86.328 86.535 86.432 95.651 100.000
89.583 85.434 85.996 85.714 96.213 100.000
86.804 85.791 85.637 85.714 94.963 100.000
89.741 85.383 85.996 85.689 96.232 100.000
90.098 85.884 86.296 86.090 96.265 100.000
90.085 85.765 86.176 85.970 96.309 100.000
87.729 85.740 85.996 85.868 95.393 100.000
89.932 85.561 86.176 85.868 96.240 100.000
Best
----
Path: data/vectors-all/11-86/training/model-best
Size: 890 MB
UAS NER P. NER R. NER F. Tag % Token %
89.932 85.561 86.176 85.868 96.240 100.000
Evaluate
--------
Time 3.56 s
Words 30034
Words/s 8434
TOK 100.00
POS 95.50
UAS 89.76
LAS 87.26
NER P 83.47
NER R 84.26
NER F 83.86
=========
Model 42
=========
Path: data/vectors-all/11-123
Vectors
-------
Algorithm: fastText Skipgram
Corpus : NoWaC (lemmatized=True, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/123.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1199275
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.813 83.343 83.244 83.293 93.106 100.000
89.418 86.203 85.996 86.099 95.708 100.000
89.018 85.963 85.757 85.860 95.462 100.000
89.211 85.920 85.817 85.868 95.599 100.000
90.055 85.842 85.996 85.919 95.867 100.000
90.125 85.714 85.458 85.586 95.889 100.000
88.556 85.680 85.577 85.629 95.357 100.000
88.263 85.492 85.338 85.415 95.198 100.000
89.562 85.817 85.817 85.817 95.799 100.000
86.574 84.872 85.278 85.075 94.428 100.000
89.864 85.424 85.577 85.501 95.832 100.000
89.956 85.382 85.637 85.509 95.854 100.000
90.177 85.894 85.637 85.766 95.895 100.000
87.849 85.757 85.757 85.757 94.949 100.000
89.906 85.621 85.877 85.748 95.851 100.000
Best
----
Path: data/vectors-all/11-123/training/model-best
Size: 619 MB
UAS NER P. NER R. NER F. Tag % Token %
89.906 85.621 85.877 85.748 95.851 100.000
Evaluate
--------
Time 3.56 s
Words 30034
Words/s 8430
TOK 100.00
POS 95.30
UAS 89.60
LAS 87.05
NER P 80.73
NER R 81.85
NER F 81.29
=========
Model 43
=========
Path: data/vectors-all/11-83
Vectors
-------
Algorithm: Global Vectors
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377) + NoWaC (lemmatized=True, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/83.zip
Vectors : dimensions=100, window=15, iterations=25, vocab size=2239665
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
83.620 83.155 83.603 83.378 92.596 100.000
88.792 85.415 85.518 85.467 95.604 100.000
88.538 85.425 85.937 85.680 95.305 100.000
88.674 85.561 85.817 85.689 95.440 100.000
89.459 85.179 85.637 85.407 95.774 100.000
89.582 84.932 85.338 85.134 95.826 100.000
88.071 85.068 85.577 85.322 95.146 100.000
87.657 85.484 85.637 85.561 94.924 100.000
88.772 85.800 86.056 85.928 95.623 100.000
86.188 84.748 85.458 85.101 93.973 100.000
88.970 85.221 85.577 85.399 95.744 100.000
89.255 85.033 85.338 85.185 95.728 100.000
89.614 84.670 85.278 84.973 95.851 100.000
87.078 85.357 85.817 85.586 94.694 100.000
89.086 85.315 85.877 85.595 95.780 100.000
Best
----
Path: data/vectors-all/11-83/training/model-best
Size: 1149 MB
UAS NER P. NER R. NER F. Tag % Token %
89.086 85.315 85.877 85.595 95.780 100.000
Evaluate
--------
Time 3.60 s
Words 30034
Words/s 8342
TOK 100.00
POS 95.09
UAS 89.18
LAS 86.56
NER P 80.56
NER R 81.56
NER F 81.06
=========
Model 44
=========
Path: data/vectors-all/11-108
Vectors
-------
Algorithm: Gensim Continuous Skipgram
Corpus : NBDigital (lemmatized=False, case preserved=True, tokens=813922111)
URL : http://vectors.nlpl.eu/repository/11/108.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2390583
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.813 82.153 82.645 82.399 94.145 100.000
89.759 86.875 86.355 86.615 96.164 100.000
89.467 85.954 85.697 85.826 96.013 100.000
89.548 86.495 86.236 86.365 96.090 100.000
90.240 85.509 85.458 85.483 96.298 100.000
90.244 85.500 85.398 85.449 96.334 100.000
89.215 85.851 85.697 85.774 95.892 100.000
88.911 86.219 86.116 86.168 95.733 100.000
89.989 86.361 85.637 85.998 96.191 100.000
87.596 85.006 85.159 85.082 95.152 100.000
90.105 85.835 85.218 85.526 96.246 100.000
90.185 85.526 85.218 85.372 96.304 100.000
90.379 85.227 85.278 85.253 96.295 100.000
88.320 85.185 85.338 85.262 95.536 100.000
90.122 85.654 85.039 85.345 96.293 100.000
Best
----
Path: data/vectors-all/11-108/training/model-best
Size: 1221 MB
UAS NER P. NER R. NER F. Tag % Token %
90.122 85.654 85.039 85.345 96.293 100.000
Evaluate
--------
Time 3.44 s
Words 30034
Words/s 8741
TOK 100.00
POS 95.70
UAS 89.91
LAS 87.55
NER P 80.39
NER R 81.56
NER F 80.97
=========
Model 45
=========
Path: data/vectors-all/11-78
Vectors
-------
Algorithm: Global Vectors
Corpus : Norsk Aviskorpus + NoWaC + NBDigital (lemmatized=True, case preserved=True, tokens=3028545953)
URL : http://vectors.nlpl.eu/repository/11/78.zip
Vectors : dimensions=100, window=15, iterations=25, vocab size=4031461
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
83.392 84.201 83.244 83.720 92.725 100.000
89.076 86.205 85.637 85.920 95.464 100.000
88.510 86.852 86.176 86.512 95.281 100.000
88.812 86.334 85.817 86.074 95.349 100.000
89.494 86.007 85.338 85.671 95.730 100.000
89.579 85.207 84.800 85.003 95.763 100.000
88.040 86.449 85.518 85.981 95.037 100.000
87.433 86.780 85.637 86.205 94.924 100.000
89.154 86.980 86.355 86.667 95.569 100.000
85.785 86.209 84.919 85.559 94.055 100.000
89.230 86.534 85.757 86.144 95.626 100.000
89.501 85.930 85.159 85.543 95.769 100.000
89.484 86.059 85.338 85.697 95.807 100.000
86.967 86.650 85.458 86.050 94.658 100.000
89.443 85.697 84.979 85.337 95.634 100.000
Best
----
Path: data/vectors-all/11-78/training/model-best
Size: 2055 MB
UAS NER P. NER R. NER F. Tag % Token %
89.443 85.697 84.979 85.337 95.634 100.000
Evaluate
--------
Time 3.58 s
Words 30034
Words/s 8393
TOK 100.00
POS 95.06
UAS 89.19
LAS 86.55
NER P 81.86
NER R 82.22
NER F 82.04
=========
Model 46
=========
Path: data/vectors-all/11-85
Vectors
-------
Algorithm: Global Vectors
Corpus : Norsk Aviskorpus (lemmatized=True, case preserved=True, tokens=1527414377)
URL : http://vectors.nlpl.eu/repository/11/85.zip
Vectors : dimensions=100, window=15, iterations=25, vocab size=1487995
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
83.469 83.323 82.825 83.073 92.475 100.000
88.743 86.246 85.937 86.091 95.547 100.000
88.328 85.947 85.278 85.611 95.311 100.000
88.563 85.817 85.817 85.817 95.497 100.000
89.534 85.963 85.757 85.860 95.761 100.000
89.528 85.287 85.338 85.313 95.730 100.000
87.908 85.294 85.039 85.166 95.168 100.000
87.558 85.379 84.919 85.149 94.976 100.000
88.962 85.448 85.039 85.243 95.623 100.000
85.758 85.688 84.919 85.302 94.063 100.000
89.247 85.114 84.859 84.987 95.634 100.000
89.461 85.714 85.458 85.586 95.711 100.000
89.714 86.306 85.996 86.151 95.815 100.000
86.819 86.828 85.996 86.410 94.623 100.000
89.269 84.970 84.919 84.945 95.659 100.000
Best
----
Path: data/vectors-all/11-85/training/model-best
Size: 768 MB
UAS NER P. NER R. NER F. Tag % Token %
89.269 84.970 84.919 84.945 95.659 100.000
Evaluate
--------
Time 3.40 s
Words 30034
Words/s 8825
TOK 100.00
POS 95.08
UAS 89.27
LAS 86.68
NER P 81.94
NER R 82.65
NER F 82.29
=========
Model 47
=========
Path: data/vectors-all/11-105
Vectors
-------
Algorithm: Gensim Continuous Skipgram
Corpus : NoWaC (lemmatized=True, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/105.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1199274
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.528 83.717 82.765 83.238 93.378 100.000
89.316 86.041 85.577 85.809 95.637 100.000
88.921 86.344 85.518 85.929 95.475 100.000
89.045 86.566 85.996 86.280 95.591 100.000
90.122 85.783 85.218 85.500 95.950 100.000
90.224 85.809 85.398 85.603 95.966 100.000
88.631 86.353 85.577 85.963 95.366 100.000
88.347 86.518 85.637 86.075 95.135 100.000
89.552 85.602 85.039 85.320 95.684 100.000
86.928 86.068 85.398 85.731 94.535 100.000
89.826 85.353 84.740 85.045 95.796 100.000
90.005 85.663 85.099 85.380 95.961 100.000
90.196 85.552 85.398 85.475 95.944 100.000
87.623 85.982 85.159 85.568 94.982 100.000
89.906 85.181 84.620 84.899 95.884 100.000
Best
----
Path: data/vectors-all/11-105/training/model-best
Size: 619 MB
UAS NER P. NER R. NER F. Tag % Token %
89.906 85.181 84.620 84.899 95.884 100.000
Evaluate
--------
Time 3.42 s
Words 30034
Words/s 8792
TOK 100.00
POS 95.37
UAS 89.64
LAS 87.18
NER P 82.30
NER R 83.38
NER F 82.84
=========
Model 48
=========
Path: data/vectors-all/11-118
Vectors
-------
Algorithm: fastText Continuous Bag-of-Words
Corpus : NBDigital (lemmatized=False, case preserved=True, tokens=813922111)
URL : http://vectors.nlpl.eu/repository/11/118.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2390584
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.275 81.829 81.388 81.608 93.679 100.000
89.700 84.569 83.962 84.264 95.969 100.000
89.135 84.843 84.081 84.460 95.791 100.000
89.446 84.398 83.842 84.119 95.873 100.000
90.171 84.151 84.201 84.176 96.090 100.000
90.276 82.896 83.244 83.070 96.128 100.000
88.769 83.273 82.825 83.048 95.689 100.000
88.325 83.503 83.303 83.403 95.511 100.000
89.924 84.648 84.141 84.394 95.972 100.000
87.059 82.269 82.466 82.367 94.853 100.000
89.971 85.328 84.919 85.123 95.969 100.000
90.151 84.537 84.081 84.308 96.103 100.000
90.215 82.956 83.303 83.129 96.120 100.000
87.884 83.373 83.124 83.248 95.267 100.000
90.067 84.994 84.740 84.867 96.021 100.000
Best
----
Path: data/vectors-all/11-118/training/model-best
Size: 1221 MB
UAS NER P. NER R. NER F. Tag % Token %
90.067 84.994 84.740 84.867 96.021 100.000
Evaluate
--------
Time 3.61 s
Words 30034
Words/s 8330
TOK 100.00
POS 95.39
UAS 89.75
LAS 87.21
NER P 77.67
NER R 79.37
NER F 78.51
=========
Model 49
=========
Path: data/vectors-all/11-88
Vectors
-------
Algorithm: Global Vectors
Corpus : NoWaC (lemmatized=False, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/88.zip
Vectors : dimensions=100, window=15, iterations=25, vocab size=1356633
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.733 80.772 80.192 80.480 93.734 100.000
89.522 85.783 85.577 85.680 96.101 100.000
89.233 86.590 86.176 86.383 95.898 100.000
89.473 86.161 85.697 85.929 95.991 100.000
90.040 84.088 84.440 84.264 96.229 100.000
90.121 84.583 85.039 84.811 96.257 100.000
88.802 86.023 85.817 85.920 95.815 100.000
88.426 85.285 84.979 85.132 95.533 100.000
89.700 85.569 85.518 85.543 96.048 100.000
87.169 83.153 83.004 83.079 94.836 100.000
89.757 85.174 84.919 85.046 96.123 100.000
89.996 84.129 84.381 84.255 96.218 100.000
90.188 85.033 85.338 85.185 96.249 100.000
87.923 85.174 84.919 85.046 95.215 100.000
89.895 84.901 84.800 84.850 96.133 100.000
Best
----
Path: data/vectors-all/11-88/training/model-best
Size: 699 MB
UAS NER P. NER R. NER F. Tag % Token %
89.895 84.901 84.800 84.850 96.133 100.000
Evaluate
--------
Time 3.41 s
Words 30034
Words/s 8819
TOK 100.00
POS 95.43
UAS 89.51
LAS 86.98
NER P 81.40
NER R 82.94
NER F 82.17
=========
Model 50
=========
Path: data/vectors-all/11-98
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : NBDigital (lemmatized=False, case preserved=True, tokens=813922111)
URL : http://vectors.nlpl.eu/repository/11/98.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2390583
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
85.381 80.732 80.491 80.611 93.490 100.000
89.480 86.094 85.218 85.654 95.931 100.000
89.136 85.723 84.800 85.259 95.780 100.000
89.304 85.982 85.159 85.568 95.887 100.000
90.251 84.699 84.141 84.419 96.046 100.000
90.286 84.300 83.543 83.919 96.059 100.000
88.738 86.113 84.979 85.542 95.623 100.000
88.429 85.861 85.039 85.448 95.429 100.000
89.738 85.826 85.159 85.491 95.920 100.000
87.299 84.226 83.722 83.974 94.790 100.000
89.828 85.190 84.680 84.934 95.983 100.000
90.116 85.078 84.620 84.848 96.024 100.000
90.164 83.694 83.244 83.468 96.106 100.000
88.118 86.069 85.039 85.551 95.209 100.000
89.949 84.985 84.680 84.832 96.016 100.000
Best
----
Path: data/vectors-all/11-98/training/model-best
Size: 1221 MB
UAS NER P. NER R. NER F. Tag % Token %
89.949 84.985 84.680 84.832 96.016 100.000
Evaluate
--------
Time 3.57 s
Words 30034
Words/s 8404
TOK 100.00
POS 95.57
UAS 89.71
LAS 87.35
NER P 78.22
NER R 78.79
NER F 78.50
=========
Model 51
=========
Path: data/vectors-all/11-107
Vectors
-------
Algorithm: Gensim Continuous Skipgram
Corpus : NBDigital (lemmatized=True, case preserved=True, tokens=813922111)
URL : http://vectors.nlpl.eu/repository/11/107.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2187702
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.597 83.293 82.047 82.665 93.147 100.000
89.219 85.280 83.902 84.585 95.654 100.000
88.610 85.445 83.962 84.697 95.492 100.000
88.796 85.714 84.022 84.859 95.577 100.000
89.662 85.576 84.500 85.035 95.821 100.000
89.804 85.291 84.321 84.803 95.810 100.000
88.290 85.436 83.902 84.662 95.294 100.000
87.894 84.313 83.303 83.805 95.146 100.000
89.386 85.314 83.782 84.541 95.772 100.000
86.726 83.043 82.645 82.843 94.337 100.000
89.535 85.082 83.962 84.518 95.785 100.000
89.648 85.403 84.381 84.889 95.815 100.000
89.887 85.455 84.381 84.914 95.873 100.000
87.613 84.309 83.603 83.954 94.883 100.000
89.608 85.161 84.141 84.648 95.799 100.000
Best
----
Path: data/vectors-all/11-107/training/model-best
Size: 1119 MB
UAS NER P. NER R. NER F. Tag % Token %
89.608 85.161 84.141 84.648 95.799 100.000
Evaluate
--------
Time 3.59 s
Words 30034
Words/s 8364
TOK 100.00
POS 95.36
UAS 89.65
LAS 87.04
NER P 78.49
NER R 79.01
NER F 78.75
=========
Model 52
=========
Path: data/vectors-all/11-87
Vectors
-------
Algorithm: Global Vectors
Corpus : NoWaC (lemmatized=True, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/87.zip
Vectors : dimensions=100, window=15, iterations=25, vocab size=1199275
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
83.337 78.687 78.875 78.781 92.484 100.000
88.782 85.169 84.201 84.683 95.426 100.000
88.459 85.412 84.440 84.923 95.283 100.000
88.566 85.264 84.141 84.699 95.338 100.000
89.456 84.694 83.782 84.236 95.676 100.000
89.498 84.876 83.962 84.416 95.725 100.000
87.945 85.316 84.141 84.724 95.111 100.000
87.483 84.885 84.022 84.451 94.878 100.000
89.024 85.100 84.081 84.588 95.519 100.000
85.628 82.619 81.927 82.272 93.937 100.000
89.126 85.100 84.081 84.588 95.560 100.000
89.339 84.764 83.902 84.331 95.676 100.000
89.568 84.522 83.662 84.090 95.733 100.000
86.800 84.150 83.244 83.694 94.612 100.000
89.162 84.588 84.081 84.334 95.621 100.000
Best
----
Path: data/vectors-all/11-87/training/model-best
Size: 619 MB
UAS NER P. NER R. NER F. Tag % Token %
89.162 84.588 84.081 84.334 95.621 100.000
Evaluate
--------
Time 3.41 s
Words 30034
Words/s 8806
TOK 100.00
POS 94.89
UAS 88.91
LAS 86.22
NER P 79.30
NER R 79.59
NER F 79.45
=========
Model 53
=========
Path: data/vectors-all/11-125
Vectors
-------
Algorithm: fastText Skipgram
Corpus : NBDigital (lemmatized=True, case preserved=True, tokens=813922111)
URL : http://vectors.nlpl.eu/repository/11/125.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2187703
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.298 81.475 81.329 81.402 93.035 100.000
89.074 84.746 83.782 84.261 95.615 100.000
88.591 85.100 84.081 84.588 95.410 100.000
88.895 84.764 83.902 84.331 95.525 100.000
89.684 84.657 84.201 84.428 95.791 100.000
89.886 84.865 84.560 84.712 95.807 100.000
88.290 84.592 83.782 84.185 95.226 100.000
87.873 84.471 83.662 84.065 95.006 100.000
89.277 84.662 83.902 84.280 95.708 100.000
86.747 83.414 82.466 82.937 94.143 100.000
89.438 84.426 84.022 84.223 95.728 100.000
89.646 84.625 84.321 84.472 95.788 100.000
89.925 84.671 84.620 84.645 95.780 100.000
87.525 84.773 83.962 84.366 94.683 100.000
89.542 84.394 84.141 84.267 95.782 100.000
Best
----
Path: data/vectors-all/11-125/training/model-best
Size: 1119 MB
UAS NER P. NER R. NER F. Tag % Token %
89.542 84.394 84.141 84.267 95.782 100.000
Evaluate
--------
Time 3.41 s
Words 30034
Words/s 8809
TOK 100.00
POS 95.36
UAS 89.31
LAS 86.82
NER P 79.08
NER R 79.88
NER F 79.48
=========
Model 54
=========
Path: data/vectors-all/11-115
Vectors
-------
Algorithm: fastText Continuous Bag-of-Words
Corpus : NoWaC (lemmatized=True, case preserved=True, tokens=687209465)
URL : http://vectors.nlpl.eu/repository/11/115.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=1199275
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.149 80.179 80.610 80.394 92.245 100.000
89.082 85.568 85.159 85.363 95.453 100.000
88.719 85.852 85.338 85.594 95.231 100.000
88.863 85.843 85.278 85.560 95.330 100.000
89.866 84.270 84.321 84.296 95.692 100.000
89.886 84.072 84.022 84.047 95.752 100.000
88.436 85.800 85.697 85.749 95.045 100.000
87.845 84.648 84.800 84.723 94.787 100.000
89.336 84.805 84.500 84.652 95.516 100.000
86.324 81.942 82.825 82.381 93.803 100.000
89.624 83.883 83.782 83.832 95.563 100.000
89.714 84.110 84.261 84.185 95.640 100.000
90.034 83.952 83.902 83.927 95.782 100.000
87.290 83.661 83.962 83.811 94.329 100.000
89.658 83.962 83.962 83.962 95.571 100.000
Best
----
Path: data/vectors-all/11-115/training/model-best
Size: 619 MB
UAS NER P. NER R. NER F. Tag % Token %
89.658 83.962 83.962 83.962 95.571 100.000
Evaluate
--------
Time 3.41 s
Words 30034
Words/s 8813
TOK 100.00
POS 95.43
UAS 89.76
LAS 87.22
NER P 80.99
NER R 82.00
NER F 81.49
=========
Model 55
=========
Path: data/vectors-all/11-90
Vectors
-------
Algorithm: Global Vectors
Corpus : NBDigital (lemmatized=False, case preserved=True, tokens=813922111)
URL : http://vectors.nlpl.eu/repository/11/90.zip
Vectors : dimensions=100, window=15, iterations=25, vocab size=2390584
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.618 80.445 80.012 80.228 93.295 100.000
89.162 83.514 83.064 83.288 95.818 100.000
88.812 83.766 83.064 83.413 95.596 100.000
89.010 83.564 83.064 83.313 95.744 100.000
89.838 83.263 83.064 83.164 95.988 100.000
89.932 82.328 82.525 82.427 96.018 100.000
88.571 83.927 83.124 83.524 95.500 100.000
87.968 83.655 83.004 83.328 95.305 100.000
89.340 83.583 83.483 83.533 95.835 100.000
86.479 82.811 82.166 82.487 94.532 100.000
89.440 83.473 83.423 83.448 95.911 100.000
89.675 81.872 82.166 82.019 95.966 100.000
90.048 82.994 82.944 82.969 96.024 100.000
87.411 83.514 82.765 83.138 95.015 100.000
89.539 82.896 83.244 83.070 95.928 100.000
Best
----
Path: data/vectors-all/11-90/training/model-best
Size: 1221 MB
UAS NER P. NER R. NER F. Tag % Token %
89.539 82.896 83.244 83.070 95.928 100.000
Evaluate
--------
Time 3.46 s
Words 30034
Words/s 8689
TOK 100.00
POS 95.41
UAS 89.38
LAS 86.91
NER P 77.70
NER R 79.23
NER F 78.46
=========
Model 56
=========
Path: data/vectors-all/11-117
Vectors
-------
Algorithm: fastText Continuous Bag-of-Words
Corpus : NBDigital (lemmatized=True, case preserved=True, tokens=813922111)
URL : http://vectors.nlpl.eu/repository/11/117.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2187703
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
83.953 80.323 80.371 80.347 92.632 100.000
89.223 84.335 83.124 83.725 95.429 100.000
88.763 82.811 82.166 82.487 95.176 100.000
89.068 83.524 82.825 83.173 95.278 100.000
89.961 83.364 82.466 82.912 95.681 100.000
90.004 83.677 82.525 83.097 95.766 100.000
88.516 83.333 82.585 82.958 95.026 100.000
88.040 83.223 82.825 83.023 94.845 100.000
89.430 83.891 82.585 83.233 95.467 100.000
86.412 82.590 82.047 82.318 93.959 100.000
89.431 83.586 82.585 83.082 95.560 100.000
89.979 83.062 82.466 82.763 95.651 100.000
90.008 83.555 82.705 83.128 95.741 100.000
87.493 82.873 82.525 82.699 94.488 100.000
89.676 83.203 82.705 82.953 95.618 100.000
Best
----
Path: data/vectors-all/11-117/training/model-best
Size: 1119 MB
UAS NER P. NER R. NER F. Tag % Token %
89.676 83.203 82.705 82.953 95.618 100.000
Evaluate
--------
Time 3.56 s
Words 30034
Words/s 8428
TOK 100.00
POS 95.04
UAS 89.64
LAS 87.15
NER P 79.10
NER R 79.45
NER F 79.27
=========
Model 57
=========
Path: data/vectors-all/11-89
Vectors
-------
Algorithm: Global Vectors
Corpus : NBDigital (lemmatized=True, case preserved=True, tokens=813922111)
URL : http://vectors.nlpl.eu/repository/11/89.zip
Vectors : dimensions=100, window=15, iterations=25, vocab size=2187703
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
83.384 80.586 78.995 79.782 92.552 100.000
88.696 84.220 82.406 83.303 95.259 100.000
88.281 84.207 82.645 83.419 95.124 100.000
88.414 84.737 83.064 83.892 95.215 100.000
89.388 83.272 81.628 82.442 95.637 100.000
89.419 82.908 81.568 82.232 95.634 100.000
88.072 84.648 82.825 83.727 94.968 100.000
87.625 82.606 81.568 82.084 94.773 100.000
88.883 84.249 82.585 83.409 95.360 100.000
85.870 81.104 80.910 81.007 93.929 100.000
89.039 83.445 82.346 82.892 95.448 100.000
89.364 83.293 81.747 82.513 95.632 100.000
89.502 82.646 81.508 82.073 95.711 100.000
87.033 83.435 81.987 82.704 94.463 100.000
89.348 83.303 82.107 82.700 95.514 100.000
Best
----
Path: data/vectors-all/11-89/training/model-best
Size: 1119 MB
UAS NER P. NER R. NER F. Tag % Token %
89.348 83.303 82.107 82.700 95.514 100.000
Evaluate
--------
Time 3.61 s
Words 30034
Words/s 8321
TOK 100.00
POS 95.00
UAS 89.31
LAS 86.56
NER P 78.08
NER R 77.62
NER F 77.85
=========
Model 58
=========
Path: data/vectors-all/11-97
Vectors
-------
Algorithm: Gensim Continuous Bag-of-Words
Corpus : NBDigital (lemmatized=True, case preserved=True, tokens=813922111)
URL : http://vectors.nlpl.eu/repository/11/97.zip
Vectors : dimensions=100, window=5, iterations=5, vocab size=2187702
Training
--------
UAS NER P. NER R. NER F. Tag % Token %
84.284 80.097 79.473 79.784 92.621 100.000
89.024 82.244 82.047 82.145 95.264 100.000
88.451 83.043 82.645 82.843 95.168 100.000
88.873 82.342 82.047 82.194 95.212 100.000
89.775 83.273 82.825 83.048 95.547 100.000
89.822 82.952 82.406 82.678 95.538 100.000
88.276 83.273 82.825 83.048 95.006 100.000
87.792 84.027 83.423 83.724 94.724 100.000
89.338 82.645 82.645 82.645 95.330 100.000
86.425 82.874 82.825 82.849 93.981 100.000
89.375 82.515 82.466 82.490 95.399 100.000
89.680 82.353 82.107 82.230 95.525 100.000
89.919 82.711 82.166 82.438 95.580 100.000
87.356 83.433 83.184 83.308 94.444 100.000
89.472 82.074 81.927 82.001 95.445 100.000
Best
----
Path: data/vectors-all/11-97/training/model-best
Size: 1119 MB
UAS NER P. NER R. NER F. Tag % Token %
89.472 82.074 81.927 82.001 95.445 100.000
Evaluate
--------
Time 3.62 s
Words 30034
Words/s 8307
TOK 100.00
POS 95.10
UAS 89.26
LAS 86.67
NER P 77.35
NER R 77.92
NER F 77.63
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