Muk-Jji-Bba Dataset - SquidGame Series 01
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 | Acc | F1 |
|---|---|---|
| Llama3.1-8b | 0.808 | 0.812 |
| Llama3-8b | 0.775 | 0.778 |
| Solar-10.7b | 0.754 | 0.759 |
| Qwen-8b | 0.783 | 0.788 |
| Yi-chat-9b (TOP) | 0.840 | 0.843 |
Models with fewer than 12 billion parameters were used due to GPU limitations. 😂
(Evaluation code will be uploaded soon.)
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!