chore: add lora sft and predict template yaml file
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### model
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model_name_or_path: ../../llm/baichuan
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### method
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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: all
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### dataset
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dataset: belle_1m
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template: baichuan
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cutoff_len: 1024
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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: ./results/lora_sft_2/Baichuan2-7B/Baichuan2_lora_sft_1_single_step500
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logging_steps: 3
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save_steps: 500
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plot_loss: true
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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: 1.0e-4
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num_train_epochs: 10.0
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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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max_steps: 500
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include_num_input_tokens_seen: true
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include_tokens_per_second: true
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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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### model
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model_name_or_path: ../../llm/baichuan
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### method
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do_predict: true
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### dataset
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eval_dataset: alpaca_gpt4_zh
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template: baichuan
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cutoff_len: 1024
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max_samples: 50
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overwrite_cache: true
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preprocessing_num_workers: 16
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include_tokens_per_second: true
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### output
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output_dir: ./results/inference/Baichuan2-7B/Baichuan2_predict_1
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overwrite_output_dir: true
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### eval
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per_device_eval_batch_size: 2
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predict_with_generate: true
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ddp_timeout: 180000000
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