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49 lines
1.1 KiB
YAML
49 lines
1.1 KiB
YAML
# Start HyperParallel FSDP2 full fine-tuning on Ascend NPU
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# Usage:
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# ASCEND_RT_VISIBLE_DEVICES=0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 accelerate launch \
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# --config_file examples/accelerate/fsdp2_config_qwen38.yaml \
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# src/train.py examples/ascend/qwen3_8_full_sft_hyper_fsdp2.yaml
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#
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# Note: Change both the visible-device list and `num_processes` for your hardware.
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### model
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model_name_or_path: Qwen/Qwen3.8-27B
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trust_remote_code: true
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use_v1_kernels: true
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flash_attn: fa2
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### method
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stage: sft
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do_train: true
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finetuning_type: full
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use_hyper_parallel: true
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### dataset
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dataset: alpaca_en_demo
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template: qwen3_8
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cutoff_len: 2048
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max_samples: 1000
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overwrite_cache: true
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preprocessing_num_workers: 16
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dataloader_num_workers: 4
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### output
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output_dir: saves/Qwen3.8-27B/full/sft
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logging_steps: 1
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save_steps: 500
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max_steps: 500
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plot_loss: true
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overwrite_output_dir: true
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save_only_model: false
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report_to: none # choices: [none, wandb, tensorboard, swanlab, mlflow]
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### train
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per_device_train_batch_size: 1
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gradient_accumulation_steps: 1
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learning_rate: 1.0e-5
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lr_scheduler_type: cosine
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warmup_ratio: 0.1
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bf16: true
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ddp_timeout: 1800
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resume_from_checkpoint: null
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