| cutoff_len: 1024 | |
| dataset: Central-SheungWan | |
| dataset_dir: data | |
| ddp_timeout: 180000000 | |
| do_train: true | |
| finetuning_type: freeze | |
| flash_attn: auto | |
| fp16: true | |
| freeze_trainable_layers: 2 | |
| freeze_trainable_modules: all | |
| gradient_accumulation_steps: 8 | |
| learning_rate: 5.0e-05 | |
| logging_steps: 5 | |
| lr_scheduler_type: cosine | |
| max_grad_norm: 1.0 | |
| max_samples: 10000 | |
| model_name_or_path: shenzhi-wang/Llama3-8B-Chinese-Chat | |
| num_train_epochs: 3.0 | |
| optim: adamw_torch | |
| output_dir: saves/LLaMA3-8B-Chinese-Chat/freeze/train_2024-05-30-09-37-42 | |
| packing: true | |
| per_device_train_batch_size: 1 | |
| plot_loss: true | |
| preprocessing_num_workers: 16 | |
| report_to: none | |
| save_steps: 100 | |
| stage: pt | |
| template: llama3 | |
| warmup_steps: 0 | |