wehub-resource-sync
37 lines
1.1 KiB
Bash
37 lines
1.1 KiB
Bash
# 80GiB * 2
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# NOTE: for swift>=3.12, you can use --fsdp fsdp2 instead of accelerate launch
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nproc_per_node=2
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CUDA_VISIBLE_DEVICES=0,1 \
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accelerate launch --config_file "./examples/train/multi-gpu/fsdp_qlora/fsdp_offload.json" \
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swift/cli/sft.py \
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--model Qwen/Qwen2.5-72B-Instruct \
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--tuner_type lora \
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--dataset 'swift/self-cognition#1000' \
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--torch_dtype bfloat16 \
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--num_train_epochs 1 \
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--per_device_train_batch_size 1 \
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--per_device_eval_batch_size 1 \
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--quant_bits 4 \
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--bnb_4bit_compute_dtype bfloat16 \
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--bnb_4bit_quant_storage bfloat16 \
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--learning_rate 1e-4 \
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--lora_rank 8 \
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--lora_alpha 32 \
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--gradient_checkpointing true \
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--weight_decay 0.1 \
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--target_modules all-linear \
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--gradient_accumulation_steps $(expr 16 / $nproc_per_node) \
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--eval_steps 100 \
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--save_steps 100 \
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--save_total_limit 2 \
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--logging_steps 5 \
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--max_length 2048 \
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--output_dir output \
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--system 'You are a helpful assistant.' \
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--warmup_ratio 0.05 \
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--dataloader_num_workers 4 \
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--model_author swift \
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--model_name swift-robot
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