LLaMA-Factory/examples/train_lora/llama3_lora_pretrain.yaml

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### model
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model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
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### method
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stage: pt
do_train: true
finetuning_type: lora
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lora_target: all
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### dataset
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dataset: c4_demo
cutoff_len: 1024
max_samples: 1000
overwrite_cache: true
preprocessing_num_workers: 16
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### output
output_dir: saves/llama3-8b/lora/pretrain
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logging_steps: 10
save_steps: 500
plot_loss: true
overwrite_output_dir: true
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### train
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per_device_train_batch_size: 1
gradient_accumulation_steps: 8
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learning_rate: 1.0e-4
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num_train_epochs: 3.0
lr_scheduler_type: cosine
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warmup_ratio: 0.1
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bf16: true
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ddp_timeout: 180000000
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### eval
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val_size: 0.1
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per_device_eval_batch_size: 1
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eval_strategy: steps
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eval_steps: 500