aitech-eks-pub/cw/10_CRF_ODPOWIEDZI.ipynb
2021-05-26 12:43:49 +02:00

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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  'shun',
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  'lamb',
  'until',
  'scientists',
  'determine',
  'whether',
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  'cow',
  'disease',
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  ',',
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  'mutton',
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  '.'],
 ['Rare',
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  '$',
  '17,000',
  '.'],
 ['LONDON', '1996-08-22'],
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  'calming',
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  'sent',
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  '10-3/8',
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  'notes',
  'due',
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 ['RESEARCH', 'ALERT', '-', 'Lehman', 'starts', 'SNET', '.'],
 ['--',
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  'Blake',
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  'New',
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  'Wednesday',
  '.'],
 ['--', 'E.', 'Auchard', ',', 'Wall', 'Street', 'bureau', ',', '212-859-1736'],
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 ['Summary', 'of', 'Consolidated', 'Financial', 'Data'],
 ['(', 'In', 'Thousands', ',', 'except', 'per', 'share', 'data', ')'],
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 ['Jul', '31', ',', 'Jul', '31', ',', 'Jul', '31', ',', 'Jul', '31', ','],
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 ['Income', 'Statement', 'Data', ':'],
 ['Total',
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  '10,756',
  '$',
  '13,102',
  '$',
  '7,961',
  '$',
  '5,507'],
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 ['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', ')'],
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 ['PRESS', 'DIGEST', '-', 'France', '-', 'Le', 'Monde', 'Aug', '22', '.'],
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 ['--',
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  '11th',
  ','],
 ['Nilis', '42nd', ',', 'Cocu', '54th', ',', '67th', ')', '.'],
 ['Halftime', '1-2', '.'],
 ['Attendance', '8,000'],
 ['SOCCER', '-', 'DUTCH', 'FIRST', 'DIVISION', 'RESULT', '.'],
 ['AMSTERDAM', '1996-08-22'],
 ['Result', 'of', 'a', 'Dutch', 'first'],
 ['division', 'match', 'on', 'Thursday', ':'],
 ['NEC', 'Nijmegen', '1', 'PSV', 'Eindhoven', '4'],
 ['SOCCER', '-', 'SHARPSHOOTER', 'KNUP', 'BACK', 'IN', 'SWISS', 'SQUAD', '.'],
 ['GENEVA', '1996-08-22'],
 ['Galatasaray',
  'striker',
  'Adrian',
  'Knup',
  ',',
  'scorer',
  'of',
  '26',
  '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, f1
num_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 x
ff = 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)