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CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 \
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NPROC_PER_NODE=8 \
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swift rlhf \
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--rlhf_type grpo \
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--advantage_estimator rloo \
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--kl_in_reward true \
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--model Qwen/Qwen2.5-VL-3B-Instruct \
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--external_plugins examples/train/grpo/plugin/plugin.py \
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--reward_funcs external_r1v_acc format \
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--use_vllm true \
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--vllm_mode colocate \
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--vllm_gpu_memory_utilization 0.4 \
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--vllm_tensor_parallel_size 1 \
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--vllm_max_model_len 16384 \
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--tuner_type lora \
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--torch_dtype bfloat16 \
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--dataset 'AI-ModelScope/clevr_cogen_a_train' \
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--overlong_filter false \
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--epsilon 3e-4 \
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--epsilon_high 4e-4 \
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--max_completion_length 1024 \
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--num_train_epochs 1 \
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--per_device_train_batch_size 2 \
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--learning_rate 1e-6 \
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--gradient_accumulation_steps 4 \
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--eval_steps 1000 \
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--save_steps 1000 \
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--save_total_limit 10 \
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--sleep_level 1 \
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--offload_model true \
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--offload_optimizer true \
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--logging_steps 1 \
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--dataloader_num_workers 4 \
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--num_generations 16 \
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--temperature 1.0 \
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--system 'examples/train/grpo/prompt.txt' \
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--deepspeed zero2 \
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--log_completions true \
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--report_to tensorboard swanlab \
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--num_iterations 1 \
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--async_generate false \
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--beta 0.001 \
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--attn_impl flash_attention_2 \
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--padding_free true \
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--loss_type grpo
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