Mortal Training Checkpoint โ€” 298k Steps

โš ๏ธ WARNING: This model is NOT recommended for use in ranked matches.


Overview

A trained checkpoint of Mortal, an AI for Japanese Riichi Mahjong powered by deep reinforcement learning. This is a hanchan (south round) model.

Model

  • Base framework: Mortal (by Equim)
  • Checkpoint: mortal_298k.pth (298,000 steps)
  • Architecture: ResNet with 192 channels, 40 blocks
  • Game type: 4-player hanchan (south round)

Dataset

Training data sourced from Tenhou high-level 4-player hanchan games (2025โ€“2026), stored under dataset/4p_hanchan/.

Note: dataset/4p_tonpuu/ (east round data) is included in the repository but was not used for training this model.

Performance

  • AI similarity: 83%โ€“92% on mjai.ekyu.moe
  • Mahjong Soul: Average S+ level on MAKA test

Usage

  1. Clone the Mortal repository and follow its setup instructions.
  2. Place mortal_298k.pth at the path specified by state_file in config.toml.
  3. Adjust paths in config.toml to match your local environment.
  4. Refer to Mortal's documentation for inference and training details.

Configuration

See config.toml for the full training configuration. All paths are set to /path/to/ placeholders โ€” replace them with your actual local paths before use.

License

This project is licensed under AGPL-3.0, consistent with Mortal.

The dataset consists of game logs from Tenhou. Please respect Tenhou's terms of service when using this data.

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