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# Muk-Jji-Bba Dataset (SquidGame Series)
**Note**: Please do not use this dataset for training purposes.
## Overview
The "Muk-Jji-Bba" dataset is the first in the SquidGame series, designed to evaluate whether models can understand human behavior. This dataset specifically focuses on the game of Muk-Jji-Bba, a variation of Rock-Paper-Scissors widely played in Korea.
### How Muk-Jji-Bba Works:
- The attacker tries to match their gesture with the defender’s to win the game.
- If both players show the same gesture in the next round, the attacker wins.
- If the attacker’s next gesture loses to the defender’s, the roles switch, and the defender becomes the new attacker.
- If the attacker’s next gesture beats the defender’s, the attacker keeps their role and the game continues.
The dataset includes 4 rounds per situation. If there is no winner in the final round, the result is a "Tie." The model must choose between Player A (1), Player B (2), or Tie (3).
The labels are evenly distributed across the three possible outcomes.
## Model Performance
| Model | Accuracy | F1 Score |
|------------|-------|-------|
| Llama 3.1 (instruct)-8b | 0.8083 | 0.8121 |
| Llama 3-8b | 0.775 | 0.7781 |
| Solar-10.7b | 0.7541 | 0.7592 |
| Qwen-8b | 0.7833 | 0.7877 |
| **Yi-9b-chat (Top)** | **0.8395** | **0.8426** |
## About the Labels
The labels in the dataset represent the correct outcome for each round:
- Player A wins (1)
- Player B wins (2)
- Tie (3)
The labels are evenly distributed among the three outcomes to ensure balance.
## Stay Tuned
Look forward to the next series in the SquidGame dataset!
(Evaluation code will be uploaded soon.)
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