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import random
from datasets import Dataset, DatasetDict
import pandas as pd
# Load positive examples from 'Positives.txt'
with open('Positives.txt', 'r') as file:
positive_examples = [line.strip() for line in file.readlines()]
# Load negative examples from 'Negatives.txt'
with open('Negatives.txt', 'r') as file:
negative_examples = [line.strip() for line in file.readlines()]
# Shuffle and combine positive and negative examples
all_examples = [(example, 'POSITIVE') for example in positive_examples] + [(example, 'NEGATIVE') for example in negative_examples]
random.shuffle(all_examples)
# Convert to pandas DataFrame
df = pd.DataFrame(all_examples, columns=['text', 'label'])
# Split the dataset if desired (e.g., 80% train, 10% validation, 10% test)
train_size = int(0.8 * len(df))
val_size = int(0.1 * len(df))
train_examples = df[:train_size]
val_examples = df[train_size: train_size + val_size]
test_examples = df[train_size + val_size:]
# Save the dataset to CSV format with 'split' column
import csv
train_examples['split'] = 'train'
val_examples['split'] = 'validation'
test_examples['split'] = 'test'
with open('dataset_with_split.csv', 'w', newline='', encoding='utf-8') as csvfile:
csvwriter = csv.writer(csvfile)
csvwriter.writerow(['text', 'label', 'split']) # Write header
csvwriter.writerows(train_examples.values.tolist()) # Write train examples
csvwriter.writerows(val_examples.values.tolist()) # Write validation examples
csvwriter.writerows(test_examples.values.tolist()) # Write test examples
print("Dataset with 'split' column created successfully.")
# Load the dataset from the CSV file
dataset = Dataset.from_csv('dataset_with_split.csv')
# Create a DatasetDict object containing train, validation, and test datasets
datasets = DatasetDict({
'train': dataset.filter(lambda example: example['split'] == 'train'),
'validation': dataset.filter(lambda example: example['split'] == 'val'),
'test': dataset.filter(lambda example: example['split'] == 'test'),
})
# Optional: Define dataset metadata
dataset_info = {
"name": "img_intents",
"description": "A dataset of positive and negative examples",
"citation": "Provide the citation or source of the dataset",
"homepage": "Link to the dataset homepage",
}
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