modelscope--ms-swift
wehub-resource-sync
43 行
1.4 KiB
Bash
43 行
1.4 KiB
Bash
# ZeRO3: 91.2s/it; 16 * 80GiB
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# Megatron-LM: 9.6s/it; 16 * 60GiB
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# Launch using Alibaba Cloud DLC
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# https://help.aliyun.com/zh/pai/user-guide/general-environment-variables
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# ref: https://github.com/modelscope/ms-swift/blob/main/examples/train/multi-node/dlc/train.sh
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PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' \
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NNODES=$WORLD_SIZE \
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NODE_RANK=$RANK \
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megatron sft \
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--model Qwen/Qwen3-30B-A3B-Base \
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--save_safetensors true \
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--dataset 'liucong/Chinese-DeepSeek-R1-Distill-data-110k-SFT' \
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--load_from_cache_file true \
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--split_dataset_ratio 0.01 \
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--pipeline_model_parallel_size 2 \
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--expert_model_parallel_size 8 \
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--moe_permute_fusion true \
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--moe_grouped_gemm true \
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--moe_shared_expert_overlap true \
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--moe_aux_loss_coeff 1e-3 \
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--micro_batch_size 1 \
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--global_batch_size 16 \
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--packing true \
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--recompute_granularity full \
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--recompute_method uniform \
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--recompute_num_layers 1 \
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--num_train_epochs 3 \
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--finetune true \
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--cross_entropy_loss_fusion true \
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--lr 1e-5 \
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--lr_warmup_fraction 0.05 \
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--min_lr 1e-6 \
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--output_dir megatron_output/Qwen3-30B-A3B-Base \
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--eval_steps 200 \
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--save_steps 200 \
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--max_length 8192 \
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--dataloader_num_workers 8 \
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--dataset_num_proc 8 \
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--no_save_optim true \
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--no_save_rng true \
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--sequence_parallel true \
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--attention_backend flash
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