257 KiB
257 KiB
Podejście softmax z embeddingami na przykładzie NER
import numpy as np
import gensim
import torch
import pandas as pd
import seaborn as sns
from sklearn.model_selection import train_test_split
from datasets import load_dataset
from torchtext.vocab import Vocab
from collections import Counter
from sklearn.datasets import fetch_20newsgroups
# https://scikit-learn.org/0.19/datasets/twenty_newsgroups.html
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics import accuracy_score
from tqdm.notebook import tqdm
import torch
from torchcrf import CRF/media/kuba/ssdsam/anaconda3/lib/python3.8/site-packages/gensim/similarities/__init__.py:15: UserWarning: The gensim.similarities.levenshtein submodule is disabled, because the optional Levenshtein package <https://pypi.org/project/python-Levenshtein/> is unavailable. Install Levenhstein (e.g. `pip install python-Levenshtein`) to suppress this warning. warnings.warn(msg)
dataset = load_dataset("conll2003")Reusing dataset conll2003 (/home/kuba/.cache/huggingface/datasets/conll2003/conll2003/1.0.0/40e7cb6bcc374f7c349c83acd1e9352a4f09474eb691f64f364ee62eb65d0ca6)
def build_vocab(dataset):
counter = Counter()
for document in dataset:
counter.update(document)
return Vocab(counter, specials=['<unk>', '<pad>', '<bos>', '<eos>'])vocab = build_vocab(dataset['train']['tokens'])dataset['train']['tokens'][['EU', 'rejects', 'German', 'call', 'to', 'boycott', 'British', 'lamb', '.'],
['Peter', 'Blackburn'],
['BRUSSELS', '1996-08-22'],
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'scientists',
'determine',
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'committee',
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'veterinary',
'officials',
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'.'],
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'health',
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'advice',
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'to',
'mad',
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'.'],
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'imports',
'.'],
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'$',
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'almost',
'$',
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'Thursday',
'at',
'an',
'auction',
'of',
'some',
'of',
'the',
'late',
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'restaurant',
'paid',
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'pounds',
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'"',
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'"',
',',
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'a',
'piece',
'of',
'London',
'hotel',
'stationery',
'in',
'late',
'1966',
'.'],
['At',
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'the',
'English',
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'Nottingham',
'he',
'threw',
'the',
'sheet',
'of',
'paper',
'into',
'the',
'audience',
',',
'where',
'it',
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'retrieved',
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'a',
'fan',
'.'],
['Buyers',
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'items',
'that',
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'girlfriend',
'Kathy',
'Etchingham',
',',
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')',
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['Moscow',
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['Numerous',
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['The',
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['They',
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['Zhirinovsky', 'visited', 'Iraq', 'twice', 'in', '1995', '.'],
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['PRESS', 'DIGEST', '-', 'Iraq', '-', 'Aug', '22', '.'],
['BAGHDAD', '1996-08-22'],
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['THAWRA'],
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'party',
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['-',
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'fair',
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'be',
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'in',
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['IRAQ'],
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'Gulf',
'.'],
['PRESS', 'DIGEST', '-', 'Lebanon', '-', 'Aug', '22', '.'],
['BEIRUT', '1996-08-22'],
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'stories',
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['AN-NAHAR'],
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'.'],
['-',
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'Hariri',
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'threats',
'do',
'no',
'serve',
'peace',
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['AS-SAFIR'],
['-',
'Parliament',
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'Berri',
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'Israel',
'is',
'preparing',
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'war',
'against',
'Syria',
'and',
'Lebanon',
'.'],
['-', 'Parliamentary', 'battle', 'in', 'Beirut', '..'],
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['AL-ANWAR'],
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['AD-DIYAR'],
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['CME', 'live', 'and', 'feeder', 'cattle', 'calls', 'range', 'mixed', '.'],
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'some',
'bull',
'spreading',
',',
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['1996-08-22'],
['KinderCare',
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'Centers',
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'on',
'Thursday',
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'a',
'debt',
'buyback',
'would',
'mean',
'an',
'extraordinary',
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'$',
'1.2',
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'fiscal',
'1997',
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'the',
'quarter',
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'10-3/8',
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'2001',
'.'],
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'chief',
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['RESEARCH', 'ALERT', '-', 'Lehman', 'starts', 'SNET', '.'],
['--',
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'analyst',
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'started',
'Southern',
'New',
'England',
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'office',
'said',
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['--',
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'$',
'45',
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'$',
'3.09',
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'earnings',
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['--',
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'38-1/2',
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'.'],
['--', 'E.', 'Auchard', ',', 'Wall', 'Street', 'bureau', ',', '212-859-1736'],
['Gateway', 'Data', 'Sciences', 'Q2', 'net', 'rises', '.'],
['PHOENIX', '1996-08-22'],
['Summary', 'of', 'Consolidated', 'Financial', 'Data'],
['(', 'In', 'Thousands', ',', 'except', 'per', 'share', 'data', ')'],
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['Jul', '31', ',', 'Jul', '31', ',', 'Jul', '31', ',', 'Jul', '31', ','],
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['Income', 'Statement', 'Data', ':'],
['Total',
'Revenue',
'$',
'10,756',
'$',
'13,102',
'$',
'7,961',
'$',
'5,507'],
['Software', 'Revenue', '2,383', '1,558', '1,086', '1,074'],
['Services', 'Revenue', '1,154', '692', '624', '465'],
['Operating', 'Income', '906', '962', '599', '515'],
['Net', 'Income', '821', '512', '565', '301'],
['Earnings', 'Per', 'Share', '0.31', '0.34', '0.19', '0.20'],
['Jul', '31', ',', '1996', 'Jan', '31', ',', '1996'],
['Balance', 'Sheet', 'Data', ':'],
['Working', 'Capital', '$', '5,755', '(', '$', '881', ')'],
['Cash', 'and', 'Cash', 'Equivalents', '2,386', '93'],
['Total', 'Assets', '14,196', '7,138'],
['Shareholders', "'", 'Equity', '5,951', '(', '1,461', ')'],
['Greek',
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'light',
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'election',
'.'],
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'chooses',
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'its',
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'secretary',
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'told',
'reporters',
'on',
'Thursday',
'.'],
['Prime',
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'Simitis',
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'cabinet',
'meeting',
'later',
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'said',
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'.'],
['--',
'Dimitris',
'Kontogiannis',
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'+301',
'3311812-4'],
['PRESS', 'DIGEST', '-', 'France', '-', 'Le', 'Monde', 'Aug', '22', '.'],
['PARIS', '1996-08-22'],
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'23',
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['FRONT', 'PAGE'],
['--',
'Africans',
'seeking',
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'or',
'obtain',
'work',
'and',
'residence',
'rights',
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'insufficient',
'as',
'hunger',
'strike',
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'49th',
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'Wednesday',
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'.'],
['--',
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'nationalist',
'movement',
'announces',
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'of',
'truce',
'after',
'last',
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"'s",
'attacks',
'.'],
['BUSINESS', 'PAGES'],
['--',
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'factories',
'points',
'up',
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'industry',
'crisis',
',',
'with',
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'manufacturers',
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'competition',
'and',
'failure',
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'general',
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['--', 'Paris', 'Newsroom', '+33', '1', '42', '21', '53', '81'],
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'(',
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['--', 'Oslo', 'newsroom', '+47', '22', '42', '50', '41'],
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['HELSINKI', '1996-08-22'],
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'goals',
'in',
'45',
'internationals',
',',
'has',
'been',
'recalled',
'by',
'Switzerland',
'for',
'the',
'World',
'Cup',
'qualifier',
'against',
'Azerbaijan',
'in',
'Baku',
'on',
'August',
'31',
'.'],
['Knup',
'was',
'overlooked',
'by',
'Artur',
'Jorge',
'for',
'the',
'European',
'championship',
'finals',
'earlier',
'this',
'year',
'.'],
['But',
'new',
'coach',
'Rolf',
'Fringer',
'is',
'clearly',
'a',
'Knup',
'fan',
'and',
'included',
'him',
'in',
'his',
'19-man',
'squad',
'on',
'Thursday',
'.'],
['Switzerland',
'failed',
'to',
'progress',
'beyond',
'the',
'opening',
'group',
'phase',
'in',
'Euro',
'96',
'.'],
['Squad', ':'],
['Goalkeepers',
'-',
'Marco',
'Pascolo',
'(',
'Cagliari',
')',
',',
'Pascal',
'Zuberbuehler',
'(',
'Grasshoppers',
')',
'.'],
['Defenders',
'-',
'Stephane',
'Henchoz',
'(',
'Hamburg',
')',
',',
'Marc',
'Hottiger',
'(',
'Everton',
')',
',',
'Yvan',
'Quentin',
'(',
'Sion',
')',
',',
'Ramon',
'Vega',
'(',
'Cagliari',
')',
'Raphael',
'Wicky',
'(',
'Sion',
')',
'.'],
['Midfielders',
'-',
'Alexandre',
'Comisetti',
'(',
'Grasshoppers',
')',
',',
'Antonio',
'Esposito',
'(',
'Grasshoppers',
')',
',',
'Sebastien',
'Fournier',
'(',
'Stuttgart',
')',
',',
'Christophe',
'Ohrel',
'(',
'Lausanne',
')',
',',
'Patrick',
'Sylvestre',
'(',
'Sion',
')',
',',
'David',
'Sesa',
'(',
'Servette',
')',
',',
'Ciriaco',
'Sforza',
'(',
'Inter',
'Milan',
')',
'Murat',
'Yakin',
'(',
'Grasshoppers',
')',
'.'],
['Strikers',
'-',
'Kubilay',
'Turkyilmaz',
'(',
'Grasshoppers',
')',
',',
'Adrian',
'Knup',
'(',
'Galatasaray',
')',
',',
'Christophe',
'Bonvin',
'(',
'Sion',
')',
',',
'Stephane',
'Chapuisat',
'(',
'Borussia',
'Dortmund',
')',
'.'],
['ATHLETICS',
'-',
'IT',
"'S",
'A',
'RECORD',
'-',
'40,000',
'BEERS',
'ON',
'THE',
'HOUSE',
'.'],
['BRUSSELS', '1996-08-22'],
['Spectators',
'at',
'Friday',
"'s",
'Brussels',
'grand',
'prix',
'meeting',
'have',
'an',
'extra',
'incentive',
'to',
'cheer',
'on',
'the',
'athletes',
'to',
'world',
'record',
'performances',
'--',
'a',
'free',
'glass',
'of',
'beer',
'.'],
['A',
'Belgian',
'brewery',
'has',
'offered',
'to',
'pay',
'for',
'a',
'free',
'round',
'of',
'drinks',
'for',
'all',
'of',
'the',
'40,000',
'crowd',
'if',
'a',
'world',
'record',
'goes',
'at',
'the',
'meeting',
',',
'organisers',
'said',
'on',
'Thursday',
'.'],
['It',
'could',
'be',
'one',
'of',
'the',
'most',
'expensive',
'rounds',
'of',
'drinks',
'ever',
'.'],
['The', 'meeting', 'is', 'sold', 'out', 'already', '.'],
['Two',
'world',
'records',
'are',
'in',
'serious',
'danger',
'of',
'being',
'broken',
'at',
'the',
'meeting',
'--',
'the',
'women',
"'s",
'1,000',
'metres',
'and',
'the',
'men',
"'s",
'3,000',
'metres',
'.'],
['GOLF', '-', 'GERMAN', 'OPEN', 'FIRST', 'ROUND', 'SCORES', '.'],
['STUTTGART', ',', 'Germany', '1996-08-22'],
['Leading', 'first', 'round'],
['scores',
'in',
'the',
'German',
'Open',
'golf',
'championship',
'on',
'Thursday',
'(',
'Britain'],
['unless', 'stated', ')', ':'],
['62', 'Paul', 'Broadhurst'],
['63', 'Raymond', 'Russell'],
['64',
'David',
'J.',
'Russell',
',',
'Michael',
'Campbell',
'(',
'New',
'Zealand',
')',
',',
'Ian'],
['Woosnam',
',',
'Bernhard',
'Langer',
'(',
'Germany',
')',
',',
'Ronan',
'Rafferty',
',',
'Mats'],
['Lanner', '(', 'Sweden', ')', ',', 'Wayne', 'Riley', '(', 'Australia', ')'],
['65',
'Eamonn',
'Darcy',
'(',
'Ireland',
')',
',',
'Per',
'Nyman',
'(',
'Sweden',
')',
',',
'Russell',
'Claydon',
','],
['Mark',
'Roe',
',',
'Retief',
'Goosen',
'(',
'South',
'Africa',
')',
',',
'Carl',
'Suneson'],
['66',
'Stephen',
'Field',
',',
'Paul',
'Lawrie',
',',
'Ian',
'Pyman',
',',
'Max',
'Anglert'],
['(',
'Sweden',
')',
',',
'Miles',
'Tunnicliff',
',',
'Christian',
'Cevaer',
'(',
'France',
')',
','],
['Des',
'Smyth',
'(',
'Ireland',
')',
',',
'David',
'Carter',
',',
'Lee',
'Westwood',
',',
'Greg'],
['Chalmers',
'(',
'Australia',
')',
',',
'Miguel',
'Angel',
'Martin',
'(',
'Spain',
')',
','],
['Thomas',
'Bjorn',
'(',
'Denmark',
')',
',',
'Fernando',
'Roca',
'(',
'Spain',
')',
',',
'Derrick'],
['Cooper'],
['67',
'Jeff',
'Hawksworth',
',',
'Padraig',
'Harrington',
'(',
'Ireland',
')',
',',
'Michael'],
['Welch',
',',
'Thomas',
'Gogele',
'(',
'Germany',
')',
',',
'Paul',
'McGinley',
'(',
'Ireland',
')',
','],
['Gary',
'Orr',
',',
'Jose-Maria',
'Canizares',
'(',
'Spain',
')',
',',
'Michael',
'Jonzon'],
['(',
'Sweden',
')',
',',
'Paul',
'Eales',
',',
'David',
'Williams',
',',
'Andrew',
'Coltart',
','],
['Jonathan',
'Lomas',
',',
'Jose',
'Rivero',
'(',
'Spain',
')',
',',
'Robert',
'Karlsson'],
['(',
'Sweden',
')',
',',
'Marcus',
'Wills',
',',
'Pedro',
'Linhart',
'(',
'Spain',
')',
',',
'Jamie'],
['Spence',
',',
'Terry',
'Price',
'(',
'Australia',
')',
',',
'Juan',
'Carlos',
'Pinero',
'(',
'Spain',
')',
','],
['Mark', 'Mouland'],
['SOCCER',
'-',
'UEFA',
'REWARDS',
'THREE',
'COUNTRIES',
'FOR',
'FAIR',
'PLAY',
'.'],
['GENEVA', '1996-08-22'],
['Norway',
',',
'England',
'and',
'Sweden',
'were',
'rewarded',
'for',
'their',
'fair',
'play',
'on',
'Thursday',
'with',
'an',
'additional',
'place',
'in',
'the',
'1997-98',
'UEFA',
'Cup',
'competition',
'.'],
['Norway',
'headed',
'the',
'UEFA',
'Fair',
'Play',
'rankings',
'for',
'1995-96',
'with',
'8.62',
'points',
',',
'ahead',
'of',
'England',
'with',
'8.61',
'and',
'Sweden',
'8.57',
'.'],
['The',
'rankings',
'are',
'based',
'on',
'a',
'formula',
'that',
'takes',
'into',
'account',
'many',
'factors',
'including',
'red',
'and',
'yellow',
'cards',
',',
'and',
'coaching',
'and',
'spectators',
"'",
'behaviour',
'at',
'matches',
'played',
'at',
'an',
'international',
'level',
'by',
'clubs',
'and',
'national',
'teams',
'.'],
['Only',
'the',
'top',
'three',
'countries',
'are',
'allocated',
'additional',
'places',
'.'],
['The', 'UEFA', 'Fair', 'Play', 'rankings', 'are', ':', '1', '.'],
['Norway', '8.62', 'points'],
['2.', 'England', '8.61'],
['3.', 'Sweden', '8.57'],
['4.', 'Faroe', 'Islands', '8.56'],
['5.', 'Wales', '8.54'],
['6.', 'Estonia', '8.52'],
['7.', 'Ireland', '8.45'],
['8.', 'Belarus', '8.39'],
['9.', 'Iceland', '8.35'],
['10.', 'Netherlands', '8.30'],
['10.', 'Denmark', '8.30'],
['10.', 'Germany', '8.30'],
['13.', 'Scotland', '8.29'],
['13.', 'Latvia', '8.29'],
['15.', 'Moldova', '8.24'],
['16.', 'Yugoslavia', '8.22'],
['16.', 'Belgium', '8.22'],
['18.', 'Luxembourg', '8.20'],
['19.', 'France', '8.18'],
['20.', 'Israel', '8.17'],
['21.', 'Switzerland', '8.15'],
['21.', 'Slovakia', '8.15'],
['23.', 'Poland', '8.12'],
['23.', 'Portugal', '8.12'],
['25.', 'Georgia', '8.10'],
['26.', 'Ukraine', '8.09'],
['26.', 'Spain', '8.09'],
['26.', 'Finland', '8.09'],
['29.', 'Macedonia', '8.07'],
['30.', 'Lithuania', '8.06'],
['31.', 'Austria', '8.05'],
['32.', 'Russia', '8.03'],
['33.', 'Romania', '8.02'],
['33.', 'Turkey', '8.02'],
['35.', 'Hungary', '7.98'],
['36.', 'Czech', 'Republic', '7.95'],
['37.', 'Greece', '7.89'],
['37.', 'Northern', 'Ireland', '7.89'],
['39.', 'Italy', '7.85'],
['40.', 'Cyprus', '7.83'],
['41.', 'Armenia', '7.80'],
['42.', 'Slovenia', '7.77'],
['43.', 'Croatia', '7.75'],
['44.', 'Bulgaria', '7.73'],
['45.', 'Malta', '7.40'],
['CRICKET',
'-',
'POLICE',
'COMMANDOS',
'ON',
'HAND',
'FOR',
'AUSTRALIANS',
"'",
'FIRST',
'MATCH',
'.'],
['COLOMBO', '1996-08-22'],
['Armed',
'police',
'commandos',
'patrolled',
'the',
'ground',
'when',
'Australia',
'opened',
'their',
'short',
'tour',
'of',
'Sri',
'Lanka',
'with',
'a',
'five-run',
'win',
'over',
'the',
'country',
"'s",
'youth',
'team',
'on',
'Thursday',
'.'],
['Australia',
',',
'in',
'Sri',
'Lanka',
'for',
'a',
'limited',
'overs',
'tournament',
'which',
'also',
'includes',
'India',
'and',
'Zimbabwe',
',',
'have',
'been',
'promised',
'the',
'presence',
'of',
'commandos',
',',
'sniffer',
'dogs',
'and',
'plainclothes',
'policemen',
'to',
'ensure',
'the',
'tournament',
'is',
'trouble-free',
'.'],
['They',
'are',
'making',
'their',
'first',
'visit',
'to',
'the',
'island',
'since',
'boycotting',
'a',
'World',
'Cup',
'fixture',
'in',
'February',
'because',
'of',
'fears',
'over',
'ethnic',
'violence',
'.'],
['Australia',
',',
'batting',
'first',
'in',
'Thursday',
"'s",
'the',
'warm-up',
'match',
',',
'scored',
'251',
'for',
'seven',
'from',
'their',
'50',
'overs',
'.'],
['Ricky',
'Ponting',
'led',
'the',
'way',
'with',
'100',
'off',
'119',
'balls',
'with',
'two',
'sixes',
'and',
'nine',
'fours',
'before',
'retiring',
'.'],
['The', 'youth', 'side', 'replied', 'with', '246', 'for', 'seven', '.'],
...]len(vocab.itos)23627
vocab['on']15
def data_process(dt):
return [ torch.tensor([vocab['<bos>']] +[vocab[token] for token in document ] + [vocab['<eos>']], dtype = torch.long) for document in dt]def labels_process(dt):
return [ torch.tensor([0] + document + [0], dtype = torch.long) for document in dt]
train_tokens_ids = data_process(dataset['train']['tokens'])test_tokens_ids = data_process(dataset['test']['tokens'])validation_tokens_ids = data_process(dataset['validation']['tokens'])train_labels = labels_process(dataset['train']['ner_tags'])validation_labels = labels_process(dataset['validation']['ner_tags'])test_labels = labels_process(dataset['test']['ner_tags'])train_tokens_ids[0]tensor([ 2, 966, 22409, 238, 773, 9, 4588, 212, 7686, 4,
3])def get_scores(y_true, y_pred):
acc_score = 0
tp = 0
fp = 0
selected_items = 0
relevant_items = 0
for p,t in zip(y_pred, y_true):
if p == t:
acc_score +=1
if p > 0 and p == t:
tp +=1
if p > 0:
selected_items += 1
if t > 0 :
relevant_items +=1
if selected_items == 0:
precision = 1.0
else:
precision = tp / selected_items
if relevant_items == 0:
recall = 1.0
else:
recall = tp / relevant_items
if precision + recall == 0.0 :
f1 = 0.0
else:
f1 = 2* precision * recall / (precision + recall)
return precision, recall, f1num_tags = max([max(x) for x in dataset['train']['ner_tags'] ]) + 1 class FF(torch.nn.Module):
def __init__(self,):
super(FF, self).__init__()
self.emb = torch.nn.Embedding(23627,200)
self.fc1 = torch.nn.Linear(200,num_tags)
def forward(self, x):
x = self.emb(x)
x = self.fc1(x)
return xff = FF()model = CRF(num_tags)params = list(ff.parameters()) + list(model.parameters())
optimizer = torch.optim.Adam(params)def eval_model(dataset_tokens, dataset_labels):
Y_true = []
Y_pred = []
ff.eval()
model.eval()
for i in tqdm(range(len(dataset_labels))):
batch_tokens = dataset_tokens[i]
tags = list(dataset_labels[i].numpy())
emissions = ff(batch_tokens).unsqueeze(1)
Y_pred += model.decode(emissions)[0]
Y_true += tags
return get_scores(Y_true, Y_pred)
for i in range (5):
ff.train()
model.train()
for i in tqdm(range(len(train_labels))):
batch_tokens = train_tokens_ids[i]
tags = train_labels[i].unsqueeze(1)
emissions = ff(batch_tokens).unsqueeze(1)
optimizer.zero_grad()
loss = -model(emissions,tags )
loss.backward()
optimizer.step()
ff.eval()
model.eval()
print(eval_model(validation_tokens_ids, validation_labels))HBox(children=(FloatProgress(value=0.0, max=14041.0), HTML(value='')))
HBox(children=(FloatProgress(value=0.0, max=3250.0), HTML(value='')))
(0.7584134615384616, 0.5134255492270138, 0.6123241145075207)
HBox(children=(FloatProgress(value=0.0, max=3453.0), HTML(value='')))
(0.6854983091306942, 0.42480276134122286, 0.5245452469746555)
HBox(children=(FloatProgress(value=0.0, max=14041.0), HTML(value='')))
HBox(children=(FloatProgress(value=0.0, max=3250.0), HTML(value='')))
(0.7624765478424015, 0.7085900267348599, 0.734546330883239)
HBox(children=(FloatProgress(value=0.0, max=3453.0), HTML(value='')))
(0.6329741112349808, 0.629930966469428, 0.6314488724127278)
HBox(children=(FloatProgress(value=0.0, max=14041.0), HTML(value='')))
HBox(children=(FloatProgress(value=0.0, max=3250.0), HTML(value='')))
(0.7837289753071692, 0.7636870859002673, 0.7735782409042741)
HBox(children=(FloatProgress(value=0.0, max=3453.0), HTML(value='')))
(0.6449022346368715, 0.6830621301775148, 0.663433908045977)
HBox(children=(FloatProgress(value=0.0, max=14041.0), HTML(value='')))
HBox(children=(FloatProgress(value=0.0, max=3250.0), HTML(value='')))
(0.7943538861327664, 0.7817040567243985, 0.7879782061046341)
HBox(children=(FloatProgress(value=0.0, max=3453.0), HTML(value='')))
(0.6709526592635885, 0.7075936883629191, 0.6887862242755145)
HBox(children=(FloatProgress(value=0.0, max=14041.0), HTML(value='')))
HBox(children=(FloatProgress(value=0.0, max=3250.0), HTML(value='')))
(0.8190561682482688, 0.742415436475648, 0.7788549478690324)
HBox(children=(FloatProgress(value=0.0, max=3453.0), HTML(value='')))
(0.6873089700996677, 0.6375739644970414, 0.6615079618852722)
eval_model(validation_tokens_ids, validation_labels)HBox(children=(FloatProgress(value=0.0, max=3250.0), HTML(value='')))
(0.8190561682482688, 0.742415436475648, 0.7788549478690324)
eval_model(test_tokens_ids, test_labels)HBox(children=(FloatProgress(value=0.0, max=3453.0), HTML(value='')))
(0.6873089700996677, 0.6375739644970414, 0.6615079618852722)