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import pandas as pd
from collections import Counter
import json
import random
df = pd.read_csv("original.csv")
print(df)
"""
for field in ["target", "severe_toxicity", "obscene", "identity_attack", "insult", "threat"]:
print("\n\n", field)
num_greater = 0
for val in df[field]:
if val >= 0.5:
num_greater += 1
print(num_greater, len(df[field]), f"{num_greater/len(df[field])*100:.2f}%")
"""
rows = [{'text': row['comment_text'].strip(),
'label': 1 if row['target'] >= 0.5 else 0,
'label_text': "toxic" if row['target'] >= 0.5 else "not toxic",
} for idx, row in df.iterrows()]
random.seed(42)
random.shuffle(rows)
num_test = 50000
splits = {'test': rows[0:num_test], 'train': rows[num_test:]}
print("Train:", len(splits['train']))
print("Test:", len(splits['test']))
num_labels = Counter()
for row in splits['test']:
num_labels[row['label']] += 1
print(num_labels)
for split in ['train', 'test']:
with open(f'{split}.jsonl', 'w') as fOut:
for row in splits[split]:
fOut.write(json.dumps(row)+"\n") |