Update parquet files

.gitattributes

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README.md

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-# BBC News Topic Classification
-
-Dataset on [BBC News Topic Classification](https://www.kaggle.com/yufengdev/bbc-text-categorization/data): 2225 articles, each labeled under one of 5 categories: business, entertainment, politics, sport or tech.

SetFit--bbc-news/json-test.parquet

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+size 1365469

SetFit--bbc-news/json-train.parquet

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+oid sha256:1e87b3dace0e47a9ff50d13303bc93924ad7b3a3e4733cb05dc207aba4e31185
+size 1727169

prepare.py

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-import pandas as pd
-from collections import Counter
-import json
-import random
-
-
-df = pd.read_csv("bbc-text.csv")
-df.fillna('', inplace=True)
-print(df)
-
-label2id = {label: idx for idx, label in enumerate(df['category'].unique())}
-
-rows = [{'text': row['text'].strip(),
-                    'label': label2id[row['category']],
-                    'label_text': row['category'],
-                    } for idx, row in df.iterrows()]
-
-random.seed(42)
-random.shuffle(rows)
-
-num_test = 1000
-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")