train: change yaml
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@ -5,17 +5,18 @@ model_name_or_path: modelscope/Llama-2-7b-ms
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stage: sft
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do_train: true
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finetuning_type: lora
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lora_target: q_proj,v_proj
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lora_target: all
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### dataset
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dataset: alpaca_en
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template: llama2
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cutoff_len: 1024
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max_samples: 100000
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max_samples: 10000
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overwrite_cache: true
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preprocessing_num_workers: 16
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### output
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output_dir: ./saves/LLaMA2-7B/lora/train_24_8_13_10_02
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output_dir: ./saves/LLaMA2-7B/lora/train_24_8_13_13_16
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logging_steps: 3
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save_steps: 100
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plot_loss: true
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@ -24,15 +25,15 @@ overwrite_output_dir: true
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### train
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per_device_train_batch_size: 2
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gradient_accumulation_steps: 8
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learning_rate: 5.0e-05
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num_train_epochs: 10
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learning_rate: 1.0e-4
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num_train_epochs: 10.0
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lr_scheduler_type: cosine
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fp16: true
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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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max_grad_norm: 1.0
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warmup_steps: 0
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optim: adamw_torch
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report_to: none
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lora_rank: 8
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lora_alpha: 16
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lora_dropout: 0.1
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### eval
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val_size: 0.1
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per_device_eval_batch_size: 2
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eval_strategy: steps
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eval_steps: 500
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