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.gitignore vendored
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*.o
.DS_Store
.token
env/
geval/

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from sklearn.naive_bayes import MultinomialNB
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.preprocessing import LabelEncoder
from sklearn.pipeline import Pipeline
with open('train/in.tsv') as f:
data_train_X = f.readlines()
with open('train/expected.tsv') as f:
data_train_Y = f.readlines()
with open('dev-0/in.tsv') as f:
data_dev_X = f.readlines()
with open('test-A/in.tsv') as f:
data_test_X = f.readlines()
data_train_Y = LabelEncoder().fit_transform(data_train_Y)
model = Pipeline(steps=[('tfidf', TfidfVectorizer()),('bayes', MultinomialNB())])
clf = model.fit(data_train_X, data_train_Y)
with open('train/out.tsv', 'w') as writer:
for result in clf.predict(data_train_X):
writer.write(str(result) + '\n')
with open('dev-0/out.tsv', 'w') as writer:
for result in clf.predict(data_dev_X):
writer.write(str(result) + '\n')
with open('test-A/out.tsv', 'w') as writer:
for result in clf.predict(data_test_X):
writer.write(str(result) + '\n')

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from transformers import BertTokenizer, BertForSequenceClassification, TrainingArguments, Trainer
import random
import torch
with open('train/in.tsv') as f:
data_train_X = f.readlines()
with open('train/expected.tsv') as f:
data_train_Y = f.readlines()
with open('dev-0/in.tsv') as f:
data_dev_X = f.readlines()
with open('test-A/in.tsv') as f:
data_test_X = f.readlines()
class CustomDataset(torch.utils.data.Dataset):
def __init__(self, encodings, labels=None):
self.encodings = encodings
self.labels = labels
def __getitem__(self, idx):
item = {key: torch.tensor(val[idx]) for key, val in self.encodings.items()}
if self.labels:
item["labels"] = torch.tensor(self.labels[idx])
return item
def __len__(self):
return len(self.encodings["input_ids"])
data_train = list(zip(data_train_X, data_train_Y))
data_train = random.sample(data_train, 50000)
tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
train_X = tokenizer([text[0] for text in data_train], truncation=True, padding=True)
train_Y = [int(text[1]) for text in data_train]
train_dataset = CustomDataset(train_X, train_Y)
model = BertForSequenceClassification.from_pretrained("bert-base-uncased", num_labels=2)
training_args = TrainingArguments("model")
trainer = Trainer(
model=model, args=training_args, train_dataset=train_dataset)
trainer.train()

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from transformers import BertTokenizer, BertForSequenceClassification, TrainingArguments, Trainer
import random
import torch
import numpy as np
with open('train/in.tsv') as f:
data_train_X = f.readlines()
with open('train/expected.tsv') as f:
data_train_Y = f.readlines()
with open('dev-0/in.tsv') as f:
data_dev_X = f.readlines()
with open('test-A/in.tsv') as f:
data_test_X = f.readlines()
class CustomDataset(torch.utils.data.Dataset):
def __init__(self, encodings, labels=None):
self.encodings = encodings
self.labels = labels
def __getitem__(self, idx):
item = {key: torch.tensor(val[idx]) for key, val in self.encodings.items()}
if self.labels:
item["labels"] = torch.tensor(self.labels[idx])
return item
def __len__(self):
return len(self.encodings["input_ids"])
tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
model_path = "model/checkpoint-18500"
model = BertForSequenceClassification.from_pretrained(model_path, num_labels=2)
trainer = Trainer(model)
with open('train/out.tsv', 'w') as writer:
train_encodings = tokenizer(data_train_X, truncation=True, padding=True)
train_dataset = CustomDataset(train_encodings)
raw_pred, _, _ = trainer.predict(train_dataset)
for result in np.argmax(raw_pred, axis=1):
writer.write(str(result) + '\n')
with open('dev-0/out.tsv', 'w') as writer:
dev_encodings = tokenizer(data_dev_X, truncation=True, padding=True)
dev_dataset = CustomDataset(dev_encodings)
raw_pred, _, _ = trainer.predict(dev_dataset)
for result in np.argmax(raw_pred, axis=1):
writer.write(str(result) + '\n')
with open('test-A/out.tsv', 'w') as writer:
test_encodings = tokenizer(data_test_X, truncation=True, padding=True)
test_dataset = CustomDataset(test_encodings)
raw_pred, _, _ = trainer.predict(test_dataset)
for result in np.argmax(raw_pred, axis=1):
writer.write(str(result) + '\n')

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certifi==2021.5.30
chardet==4.0.0
click==8.0.1
datasets==1.8.0
dill==0.3.4
filelock==3.0.12
fsspec==2021.6.0
huggingface-hub==0.0.8
idna==2.10
joblib==1.0.1
keyboard==0.13.5
multiprocess==0.70.12.2
numpy==1.20.2
packaging==20.9
pandas==1.2.4
pyarrow==3.0.0
pynput==1.7.3
pyobjc==7.2
pyobjc-core==7.2
pyobjc-framework-Accessibility==7.2
pyobjc-framework-Accounts==7.2
pyobjc-framework-AddressBook==7.2
pyobjc-framework-AdServices==7.2
pyobjc-framework-AdSupport==7.2
pyobjc-framework-AppleScriptKit==7.2
pyobjc-framework-AppleScriptObjC==7.2
pyobjc-framework-ApplicationServices==7.2
pyobjc-framework-AppTrackingTransparency==7.2
pyobjc-framework-AuthenticationServices==7.2
pyobjc-framework-AutomaticAssessmentConfiguration==7.2
pyobjc-framework-Automator==7.2
pyobjc-framework-AVFoundation==7.2
pyobjc-framework-AVKit==7.2
pyobjc-framework-BusinessChat==7.2
pyobjc-framework-CalendarStore==7.2
pyobjc-framework-CallKit==7.2
pyobjc-framework-CFNetwork==7.2
pyobjc-framework-ClassKit==7.2
pyobjc-framework-CloudKit==7.2
pyobjc-framework-Cocoa==7.2
pyobjc-framework-Collaboration==7.2
pyobjc-framework-ColorSync==7.2
pyobjc-framework-Contacts==7.2
pyobjc-framework-ContactsUI==7.2
pyobjc-framework-CoreAudio==7.2
pyobjc-framework-CoreAudioKit==7.2
pyobjc-framework-CoreBluetooth==7.2
pyobjc-framework-CoreData==7.2
pyobjc-framework-CoreHaptics==7.2
pyobjc-framework-CoreLocation==7.2
pyobjc-framework-CoreMedia==7.2
pyobjc-framework-CoreMediaIO==7.2
pyobjc-framework-CoreMIDI==7.2
pyobjc-framework-CoreML==7.2
pyobjc-framework-CoreMotion==7.2
pyobjc-framework-CoreServices==7.2
pyobjc-framework-CoreSpotlight==7.2
pyobjc-framework-CoreText==7.2
pyobjc-framework-CoreWLAN==7.2
pyobjc-framework-CryptoTokenKit==7.2
pyobjc-framework-DeviceCheck==7.2
pyobjc-framework-DictionaryServices==7.2
pyobjc-framework-DiscRecording==7.2
pyobjc-framework-DiscRecordingUI==7.2
pyobjc-framework-DiskArbitration==7.2
pyobjc-framework-DVDPlayback==7.2
pyobjc-framework-EventKit==7.2
pyobjc-framework-ExceptionHandling==7.2
pyobjc-framework-ExecutionPolicy==7.2
pyobjc-framework-ExternalAccessory==7.2
pyobjc-framework-FileProvider==7.2
pyobjc-framework-FileProviderUI==7.2
pyobjc-framework-FinderSync==7.2
pyobjc-framework-FSEvents==7.2
pyobjc-framework-GameCenter==7.2
pyobjc-framework-GameController==7.2
pyobjc-framework-GameKit==7.2
pyobjc-framework-GameplayKit==7.2
pyobjc-framework-ImageCaptureCore==7.2
pyobjc-framework-IMServicePlugIn==7.2
pyobjc-framework-InputMethodKit==7.2
pyobjc-framework-InstallerPlugins==7.2
pyobjc-framework-InstantMessage==7.2
pyobjc-framework-Intents==7.2
pyobjc-framework-IOSurface==7.2
pyobjc-framework-iTunesLibrary==7.2
pyobjc-framework-KernelManagement==7.2
pyobjc-framework-LatentSemanticMapping==7.2
pyobjc-framework-LaunchServices==7.2
pyobjc-framework-libdispatch==7.2
pyobjc-framework-LinkPresentation==7.2
pyobjc-framework-LocalAuthentication==7.2
pyobjc-framework-MapKit==7.2
pyobjc-framework-MediaAccessibility==7.2
pyobjc-framework-MediaLibrary==7.2
pyobjc-framework-MediaPlayer==7.2
pyobjc-framework-MediaToolbox==7.2
pyobjc-framework-Metal==7.2
pyobjc-framework-MetalKit==7.2
pyobjc-framework-MetalPerformanceShaders==7.2
pyobjc-framework-MetalPerformanceShadersGraph==7.2
pyobjc-framework-MLCompute==7.2
pyobjc-framework-ModelIO==7.2
pyobjc-framework-MultipeerConnectivity==7.2
pyobjc-framework-NaturalLanguage==7.2
pyobjc-framework-NetFS==7.2
pyobjc-framework-Network==7.2
pyobjc-framework-NetworkExtension==7.2
pyobjc-framework-NotificationCenter==7.2
pyobjc-framework-OpenDirectory==7.2
pyobjc-framework-OSAKit==7.2
pyobjc-framework-OSLog==7.2
pyobjc-framework-PassKit==7.2
pyobjc-framework-PencilKit==7.2
pyobjc-framework-Photos==7.2
pyobjc-framework-PhotosUI==7.2
pyobjc-framework-PreferencePanes==7.2
pyobjc-framework-PushKit==7.2
pyobjc-framework-Quartz==7.2
pyobjc-framework-QuickLookThumbnailing==7.2
pyobjc-framework-ReplayKit==7.2
pyobjc-framework-SafariServices==7.2
pyobjc-framework-SceneKit==7.2
pyobjc-framework-ScreenSaver==7.2
pyobjc-framework-ScreenTime==7.2
pyobjc-framework-ScriptingBridge==7.2
pyobjc-framework-SearchKit==7.2
pyobjc-framework-Security==7.2
pyobjc-framework-SecurityFoundation==7.2
pyobjc-framework-SecurityInterface==7.2
pyobjc-framework-ServiceManagement==7.2
pyobjc-framework-Social==7.2
pyobjc-framework-SoundAnalysis==7.2
pyobjc-framework-Speech==7.2
pyobjc-framework-SpriteKit==7.2
pyobjc-framework-StoreKit==7.2
pyobjc-framework-SyncServices==7.2
pyobjc-framework-SystemConfiguration==7.2
pyobjc-framework-SystemExtensions==7.2
pyobjc-framework-UniformTypeIdentifiers==7.2
pyobjc-framework-UserNotifications==7.2
pyobjc-framework-UserNotificationsUI==7.2
pyobjc-framework-VideoSubscriberAccount==7.2
pyobjc-framework-VideoToolbox==7.2
pyobjc-framework-Virtualization==7.2
pyobjc-framework-Vision==7.2
pyobjc-framework-WebKit==7.2
pyparsing==2.4.7
python-dateutil==2.8.1
pytz==2021.1
PyYAML==5.4.1
regex==2021.4.4
requests==2.25.1
sacremoses==0.0.45
scikit-learn==0.24.2
scipy==1.6.3
six==1.16.0
sklearn==0.0
threadpoolctl==2.1.0
tokenizers==0.10.3
torch==1.9.0
tqdm==4.49.0
transformers==4.7.0
typing-extensions==3.10.0.0
urllib3==1.26.5
xxhash==2.0.2

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