add examples
Former-commit-id: 8cdf64adc2c8e5f194a6df26cf749d7bc9bc039f
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examples/lora_multi_gpu/config.yaml
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examples/lora_multi_gpu/config.yaml
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compute_environment: LOCAL_MACHINE
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debug: false
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distributed_type: MULTI_GPU
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downcast_bf16: 'no'
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gpu_ids: all
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machine_rank: 0
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main_training_function: main
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mixed_precision: fp16
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num_machines: 1
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num_processes: 4
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rdzv_backend: static
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same_network: true
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tpu_env: []
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tpu_use_cluster: false
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tpu_use_sudo: false
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use_cpu: false
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examples/lora_multi_gpu/sft.sh
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examples/lora_multi_gpu/sft.sh
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#!/bin/bash
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CUDA_VISIBLE_DEVICES=0,1,2,3 accelerate launch --config_file config.yaml ../../src/train_bash.py \
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--stage sft \
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--do_train \
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--model_name_or_path meta-llama/Llama-2-7b-hf \
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--dataset alpaca_gpt4_en,glaive_toolcall \
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--dataset_dir ../../data \
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--template default \
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--finetuning_type lora \
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--lora_target q_proj,v_proj \
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--output_dir ../../saves/LLaMA2-7B/lora/sft \
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--overwrite_cache \
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--overwrite_output_dir \
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--cutoff_len 1024 \
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--per_device_train_batch_size 1 \
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--per_device_eval_batch_size 1 \
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--gradient_accumulation_steps 2 \
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--lr_scheduler_type cosine \
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--logging_steps 10 \
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--save_steps 100 \
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--eval_steps 100 \
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--evaluation_strategy steps \
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--load_best_model_at_end \
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--learning_rate 5e-5 \
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--num_train_epochs 3.0 \
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--max_samples 3000 \
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--val_size 0.1 \
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--plot_loss \
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--fp16
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