MuSL

Results

Training hyperparameters

• learning_rate: 1e-05
• train_batch_size: 4
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• total_train_batch_size: 32
• total_eval_batch_size: 64
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3.0

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 2.16.0
• Tokenizers 0.21.1

Citation Information

@misc{ke2025musl,
      title={Mutual-Supervised Learning for Sequential-to-Parallel Code Translation}, 
      author={Changxin Ke and Rui Zhang and Shuo Wang and Li Ding and Guangli Li and Yuanbo Wen and Shuoming Zhang and Ruiyuan Xu and Jin Qin and Jiaming Guo and Chenxi Wang and Ling Li and Qi Guo and Yunji Chen},
      year={2025},
      eprint={2506.11153},
      archivePrefix={arXiv},
      primaryClass={cs.SE},
      url={https://arxiv.org/abs/2506.11153}, 
}