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Upload llama3_lora_sft.yaml with huggingface_hub

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+ ### model
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+ model_name_or_path: /root/paddlejob/workspace/env_run/output/output/mistral-7b-inst-v0.3
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+
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+ ### method
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+ stage: sft
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+ do_train: true
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+ finetuning_type: full
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+
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+ ### dataset
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+ dataset: alpaca_en_demo_52k
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+ template: mistral
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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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+
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+ ### output
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+ output_dir: saves/llama3-8b/lora/sft
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+ logging_steps: 1
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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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+
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+ ### train
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+ per_device_train_batch_size: 1
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+ gradient_accumulation_steps: 8
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+ learning_rate: 2.0e-5
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+ num_train_epochs: 3.0
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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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+
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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