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# model args
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model: Qwen/Qwen2.5-7B-Instruct
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torch_dtype: bfloat16
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tuner_type: lora
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lora_rank: 8
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lora_alpha: 32
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target_modules: all-linear
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# dataset args
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dataset:
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- 'AI-ModelScope/alpaca-gpt4-data-zh#500'
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- 'AI-ModelScope/alpaca-gpt4-data-en#500'
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- 'swift/self-cognition#500'
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split_dataset_ratio: 0.0
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max_length: 2048
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system: 'You are a helpful assistant.'
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model_author: swift
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model_name: swift-bot
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# training args
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num_train_epochs: 1
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per_device_train_batch_size: 1
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per_device_eval_batch_size: 1
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learning_rate: 1e-4
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gradient_accumulation_steps: 8
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eval_steps: 50
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save_steps: 50
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save_total_limit: 2
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logging_steps: 5
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output_dir: output
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warmup_ratio: 0.05
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dataloader_num_workers: 4
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dataset_num_proc: 4
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deepspeed: zero2
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