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### model
model_name_or_path: Qwen/Qwen2.5-3B-Instruct
### method
stage: sft
do_train: true
finetuning_type: lora
lora_target: all
### dataset
dataset: alpaca_mgtv_p2
template: qwen
cutoff_len: 8192
max_samples: 25000
overwrite_cache: true
preprocessing_num_workers: 16
### output
output_dir: saves/Qwen2.5-3B-Instruct
logging_steps: 5
save_steps: 35
plot_loss: true
# overwrite_output_dir: true
### train
per_device_train_batch_size: 16
gradient_accumulation_steps: 8
learning_rate: 1.0e-4
num_train_epochs: 2.0
lr_scheduler_type: cosine
warmup_ratio: 0.1
bf16: true
ddp_timeout: 180000000
### eval
val_size: 0.1
per_device_eval_batch_size: 1
eval_strategy: steps
eval_steps: 35
# report_to: wandb
report_to: none
run_name: Qwen2.5-3B-Instruct_lora_sft
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