Readme.md

Dataset README

Overview

This repository contains JSONL datasets: train.jsonl and test.jsonl. These datasets have been filtered to remove potentially harmful or inappropriate content from the original LIMA, respectively.

Dataset Files

• train_no_safety.jsonl: A cleaned version of the original training dataset with all safety-related queries removed.
• test_no_harmful.jsonl: A cleaned version of the original test dataset with harmful queries identified and removed.

File Format

Both datasets are stored in the JSON Lines format, where each line is a separate JSON object. The structure of each JSON object is as follows:

{
    "conversations": [
        "A text string representing a query or conversation.",
        ...
    ],
    "source": "Additional metadata about the conversation (optional)."
}

• conversations: This field is an array containing one or more text strings, each representing a query or part of a conversation.
• source: This optional field can include metadata about the source of the conversation, though it may be empty or omitted.

Cleaning Process

For train_no_safety.jsonl

1. Initial Dataset: The initial dataset train.jsonl contained some queries flagged as related to safety concerns.
2. Filtering: Queries containing phrases or keywords indicative of safety issues were removed. Examples include questions about illegal activities, harmful behaviors, and other inappropriate content.
3. Output: The resulting dataset, new train.jsonl, contains only non-safety-related queries.

For test_no_harmful.jsonl

1. Initial Dataset: The initial dataset test.jsonl included some harmful or inappropriate queries.
2. Filtering: Harmful queries were identified and removed based on a predefined set of keywords and phrases. These keywords were selected to filter out content that could be offensive, inappropriate, or dangerous.
3. Output: The resulting dataset, new test.jsonl, includes only non-harmful queries, ensuring safer content for testing purposes.

Data Volume Description

After filtering out harmful queries, the following are the details regarding the data volume:

• Original Training Set: 1030
• Filtered Training Set：1015
• Original Test Set: 300
• Filtered Test Set: 287

Keywords Used for Filtering

Safety-related Keywords (for train dataset)

Some of the keywords or phrases that led to the removal of entries include:

• "curse words"
• "cheat on my husband"
• "rob a convenience store"
• "hurting myself"
• "get a friend to have sex"
• "be trusted"
• "get a fake ID"
• "relationship without your parents knowing"
• "physically flirt"
• "lazy college student"
• "married boyfriend"
• "flip someone off"
• "bullet made from ice"
• "hire a hitman"
• "Hitler writes a second book"

Harmful Keywords (for test dataset)

Keywords or phrases considered harmful or inappropriate were removed. Examples include:

• "Killing a puppy"
• "Does Crimea belong to Russia"
• "Prove that every set is countable" (as part of mathematical impossibilities)
• "Show me the address"
• "alternative treatment ideas for COVID-19"
• "ISIS"
• "Joe Biden cheat"
• "Help me get revenge"
• "slip something into that poor dog's food"
• "commit suicide"

These are only examples, and the actual filtering process might have included additional patterns based on the nature of the data.