Summary of Changes

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This pull request updates the moe.sh script to optimize the configuration for a Megatron SFT (Supervised Fine-Tuning) job. The changes involve expanding the GPU resources used, redirecting the training dataset to a local file, and adjusting the frequency of evaluation and model saving. Additionally, it introduces integration with Weights & Biases for enhanced experiment tracking.

Highlights

• GPU Resource Allocation: The script now utilizes 4 CUDA devices (0,1,2,3) instead of 2, allowing for potentially faster or larger-scale training.
• Dataset Source Update: The dataset path has been changed from a Swift-specific reference to a local file system path: /root/autodl-tmp/swift_finetune_data/qwen3_finetune_self_cognition.jsonl.
• Training Interval Adjustments: The eval_interval and save_interval parameters have been significantly reduced from 200 to 5, leading to more frequent evaluation and checkpointing during training.
• Wandb Integration: A new argument --report_to wandb has been added, enabling integration with Weights & Biases for experiment tracking and reporting.

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