README.md

Dataset Scripts

divide.py

divide.py is a script designed to split a JSONL file into two separate files based on the approximate token count of a specified text field. It detects the appropriate text field from the input JSONL and uses the median token count as a threshold to categorize the entries into "short" and "long".

Usage

To use divide.py, run the following command in your terminal:

python divide.py --input <input_jsonl_path> --short_out <output_short_jsonl_path> --long_out <output_long_jsonl_path>

• --input: Path to the input JSONL file (required).
• --short_out: Path to the output JSONL file for short entries (default: short.jsonl).
• --long_out: Path to the output JSONL file for long entries (default: long.jsonl).

ratio.py

ratio.py is a script that creates datasets with specified positive and negative sample ratios from two JSONL files containing positive and negative samples. It randomly samples from the provided datasets to create a new dataset based on the defined configuration.

Usage

To use ratio.py, simply run the script:

python ratio.py

This script will read from positive/positive.jsonl and negative/negative.jsonl, and create datasets based on the configurations defined in the script. The output files will be named dataset_{name}.jsonl for each configuration.

Dataset Configurations

The following configurations are available in the script:

• 1_1: 2000 total samples with a 1:1 positive to negative ratio.
• 1_5: 1200 total samples with a 1:5 positive to negative ratio.
• 5_1: 1200 total samples with a 5:1 positive to negative ratio.

extract_members.py

extract_members.py is a script that extracts members and non-members from a JSONL file based on the label field. It reads from python_sample.jsonl, where a label of 1 indicates a member and a label of 0 indicates a non-member. The script outputs two separate JSONL files: one for members and one for non-members.

Usage

To use extract_members.py, run the following command in your terminal:

python extract_members.py

This script will read from dataset/python_sample.jsonl and create the following output files:

• dataset/member.jsonl: Contains all entries with label equal to 1.
• dataset/non-member.jsonl: Contains all entries with label equal to 0.

Output

After running the script, you will see a message indicating the number of extracted members and non-members.