| # config for https://github.com/hiyouga/LLaMA-Factory | |
| ### model | |
| model_name_or_path: Qwen/Qwen2-7B-Instruct | |
| ### method | |
| stage: sft | |
| do_train: true | |
| finetuning_type: lora | |
| lora_target: all | |
| ### dataset | |
| dataset_dir: data | |
| dataset: llm-complex-reasoning-train-qwen2-72b-instruct-correct,Infinity-Instruct-0625 | |
| template: qwen | |
| cutoff_len: 2048 | |
| max_samples: 128000 | |
| overwrite_cache: false | |
| preprocessing_num_workers: 8 | |
| # deepspeed: ./LLaMA-Factory/examples/deepspeed/ds_z2_config.json | |
| ### output | |
| output_dir: output/qwen2-7b-instruct/sft-lora | |
| logging_steps: 5 | |
| save_steps: 300 | |
| plot_loss: true | |
| overwrite_output_dir: true | |
| ### train | |
| per_device_train_batch_size: 8 | |
| gradient_accumulation_steps: 8 | |
| learning_rate: 5.0e-5 | |
| 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: 4 | |
| eval_strategy: steps | |
| eval_steps: 100 | |