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run_sft.sh
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run_sft.sh
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CUDA_VISIBLE_DEVICES=0,1 torchrun --nproc_per_node 2 supervised_finetuning.py \
--model_type auto \
--model_name_or_path Qwen/Qwen1.5-0.5B-Chat \
--train_file_dir ./data/finetune \
--validation_file_dir ./data/finetune \
--per_device_train_batch_size 4 \
--per_device_eval_batch_size 4 \
--do_train \
--do_eval \
--template_name qwen \
--use_peft True \
--max_train_samples 1000 \
--max_eval_samples 10 \
--model_max_length 4096 \
--num_train_epochs 1 \
--learning_rate 2e-5 \
--warmup_ratio 0.05 \
--weight_decay 0.05 \
--logging_strategy steps \
--logging_steps 10 \
--eval_steps 50 \
--evaluation_strategy steps \
--save_steps 500 \
--save_strategy steps \
--save_total_limit 13 \
--gradient_accumulation_steps 1 \
--preprocessing_num_workers 4 \
--output_dir outputs-sft-qwen-v1 \
--overwrite_output_dir \
--ddp_timeout 30000 \
--logging_first_step True \
--target_modules all \
--lora_rank 8 \
--lora_alpha 16 \
--lora_dropout 0.05 \
--torch_dtype float16 \
--fp16 \
--device_map auto \
--report_to tensorboard \
--ddp_find_unused_parameters False \
--gradient_checkpointing True \
--cache_dir ./cache