![Squid Game Dataset](SquidGame.jpg) # 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!