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| ### model | |
| model_name_or_path: THUDM/glm-4-9b-chat-1m | |
| ### method | |
| stage: sft | |
| do_train: true | |
| finetuning_type: lora | |
| lora_target: all | |
| # quantization_bit: 4 # use 4-bit QLoRA | |
| loraplus_lr_ratio: 16.0 # use LoRA+ with lambda=16.0 | |
| # use_unsloth: true # use UnslothAI's LoRA optimization for 2x faster training | |
| upcast_layernorm: true | |
| ### dataset | |
| dataset: alpaca_mgtv_p1 | |
| template: glm4 | |
| cutoff_len: 4096 | |
| max_samples: 25000 | |
| overwrite_cache: true | |
| preprocessing_num_workers: 16 | |
| ### output | |
| output_dir: saves/glm-4-9b/lora/sft_bf16_p1_full | |
| logging_steps: 10 | |
| save_steps: 175 | |
| 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: 4.0 | |
| 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: 175 | |
| report_to: wandb | |
| run_name: glm-4-9b_p1_full # optional | |