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nproc_per_node=2
CUDA_VISIBLE_DEVICES=0,1 \
NPROC_PER_NODE=$nproc_per_node \
swift sft \
--model Qwen/Qwen2.5-1.5B \
--train_type full \
--dataset 'AI-ModelScope/alpaca-gpt4-data-zh#500' \
'AI-ModelScope/alpaca-gpt4-data-en#500' \
'swift/self-cognition' \
--torch_dtype bfloat16 \
--num_train_epochs 10 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--learning_rate 1e-5 \
--gradient_accumulation_steps $(expr 16 / $nproc_per_node) \
--eval_steps 200 \
--save_steps 200 \
--save_total_limit 2 \
--logging_steps 5 \
--max_length 2048 \
--output_dir output \
--system 'You are a helpful assistant.' \
--warmup_ratio 0.05 \
--dataloader_num_workers 4 \
--model_author swift \
--model_name swift-robot \
--deepspeed zero2
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