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modelscope--ms-swift/examples/train/rlhf/dpo/lora.sh
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# 24GiB
# It is recommended to use padding_free. For more details, please refer to:
# https://github.com/modelscope/ms-swift/blob/main/examples/train/padding_free/dpo.sh
CUDA_VISIBLE_DEVICES=0 \
swift rlhf \
--rlhf_type dpo \
--model Qwen/Qwen2.5-7B-Instruct \
--tuner_type lora \
--dataset hjh0119/shareAI-Llama3-DPO-zh-en-emoji \
--load_from_cache_file true \
--split_dataset_ratio 0.01 \
--torch_dtype bfloat16 \
--num_train_epochs 1 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--learning_rate 1e-4 \
--lora_rank 8 \
--lora_alpha 32 \
--target_modules all-linear \
--gradient_accumulation_steps 16 \
--eval_steps 50 \
--save_steps 50 \
--save_total_limit 2 \
--logging_steps 5 \
--max_length 2048 \
--output_dir output \
--warmup_ratio 0.05 \
--dataloader_num_workers 4 \
--rpo_alpha 0.1 \
--dataset_num_proc 4