mirror of
https://github.com/hiyouga/LLaMA-Factory.git
synced 2025-08-02 03:32:50 +08:00
37 lines
1.0 KiB
Bash
37 lines
1.0 KiB
Bash
#!/bin/bash
|
|
|
|
CUDA_VISIBLE_DEVICES=0 python ../../../src/train_bash.py \
|
|
--stage sft \
|
|
--do_train \
|
|
--model_name_or_path meta-llama/Llama-2-7b-hf \
|
|
--dataset alpaca_gpt4_en,glaive_toolcall \
|
|
--dataset_dir ../../../data \
|
|
--template default \
|
|
--finetuning_type full \
|
|
--use_galore \
|
|
--galore_layerwise \
|
|
--galore_target mlp,self_attn \
|
|
--galore_scale 2.0 \
|
|
--galore_rank 128 \
|
|
--output_dir ../../../saves/LLaMA2-7B/galore/sft \
|
|
--overwrite_cache \
|
|
--overwrite_output_dir \
|
|
--cutoff_len 1024 \
|
|
--preprocessing_num_workers 16 \
|
|
--per_device_train_batch_size 1 \
|
|
--per_device_eval_batch_size 1 \
|
|
--gradient_accumulation_steps 1 \
|
|
--lr_scheduler_type cosine \
|
|
--logging_steps 10 \
|
|
--warmup_steps 20 \
|
|
--save_steps 100 \
|
|
--eval_steps 100 \
|
|
--evaluation_strategy steps \
|
|
--load_best_model_at_end \
|
|
--learning_rate 5e-5 \
|
|
--num_train_epochs 30.0 \
|
|
--max_samples 300 \
|
|
--val_size 0.1 \
|
|
--plot_loss \
|
|
--pure_bf16
|