update examples

Former-commit-id: 194e25606515bfa42c3be27d68f68d604191514b
This commit is contained in:
hiyouga 2024-03-06 13:14:57 +08:00
parent 3168abc0a1
commit 6b407092d9
13 changed files with 124 additions and 1 deletions

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@ -0,0 +1,37 @@
#!/bin/bash
python -m torch.distributed.run \
--nproc_per_node $NPROC_PER_NODE \
--nnodes $NNODES \
--node_rank $RANK \
--master_addr $MASTER_ADDR \
--master_port $MASTER_PORT \
../../src/train_bash.py \
--deepspeed ds_z3_config.json \
--stage sft \
--do_train \
--model_name_or_path meta-llama/Llama-2-7b-hf \
--dataset alpaca_gpt4_en \
--dataset_dir ../../data \
--template default \
--finetuning_type full \
--output_dir ../../saves/LLaMA2-7B/full/sft \
--overwrite_cache \
--overwrite_output_dir \
--cutoff_len 1024 \
--preprocessing_num_workers 16 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--gradient_accumulation_steps 2 \
--lr_scheduler_type cosine \
--logging_steps 10 \
--warmup_steps 20 \
--save_steps 100 \
--eval_steps 100 \
--evaluation_strategy steps \
--learning_rate 5e-5 \
--num_train_epochs 3.0 \
--max_samples 3000 \
--val_size 0.1 \
--plot_loss \
--fp16

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@ -13,11 +13,13 @@ deepspeed --num_gpus 4 ../../src/train_bash.py \
--overwrite_cache \
--overwrite_output_dir \
--cutoff_len 1024 \
--preprocessing_num_workers 16 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--gradient_accumulation_steps 2 \
--lr_scheduler_type cosine \
--logging_steps 10 \
--warmup_steps 20 \
--save_steps 100 \
--eval_steps 100 \
--evaluation_strategy steps \

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@ -0,0 +1,18 @@
compute_environment: LOCAL_MACHINE
debug: false
distributed_type: MULTI_GPU
downcast_bf16: 'no'
gpu_ids: all
machine_rank: 0
main_process_ip: 192.168.0.1
main_process_port: 29555
main_training_function: main
mixed_precision: fp16
num_machines: 2
num_processes: 16
rdzv_backend: static
same_network: true
tpu_env: []
tpu_use_cluster: false
tpu_use_sudo: false
use_cpu: false

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@ -1,6 +1,8 @@
#!/bin/bash
CUDA_VISIBLE_DEVICES=0,1,2,3 accelerate launch --config_file config.yaml ../../src/train_bash.py \
CUDA_VISIBLE_DEVICES=0,1,2,3 accelerate launch \
--config_file master_config.yaml \
../../src/train_bash.py \
--stage sft \
--do_train \
--model_name_or_path meta-llama/Llama-2-7b-hf \
@ -13,11 +15,13 @@ CUDA_VISIBLE_DEVICES=0,1,2,3 accelerate launch --config_file config.yaml ../../s
--overwrite_cache \
--overwrite_output_dir \
--cutoff_len 1024 \
--preprocessing_num_workers 16 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--gradient_accumulation_steps 2 \
--lr_scheduler_type cosine \
--logging_steps 10 \
--warmup_steps 20 \
--save_steps 100 \
--eval_steps 100 \
--evaluation_strategy steps \

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@ -0,0 +1,34 @@
#!/bin/bash
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 accelerate launch \
--config_file single_config.yaml \
../../src/train_bash.py \
--stage sft \
--do_train \
--model_name_or_path meta-llama/Llama-2-7b-hf \
--dataset alpaca_gpt4_en,glaive_toolcall \
--dataset_dir ../../data \
--template default \
--finetuning_type lora \
--lora_target q_proj,v_proj \
--output_dir ../../saves/LLaMA2-7B/lora/sft \
--overwrite_cache \
--overwrite_output_dir \
--cutoff_len 1024 \
--preprocessing_num_workers 16 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--gradient_accumulation_steps 2 \
--lr_scheduler_type cosine \
--logging_steps 10 \
--warmup_steps 20 \
--save_steps 100 \
--eval_steps 100 \
--evaluation_strategy steps \
--load_best_model_at_end \
--learning_rate 5e-5 \
--num_train_epochs 3.0 \
--max_samples 3000 \
--val_size 0.1 \
--plot_loss \
--fp16

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@ -0,0 +1,18 @@
compute_environment: LOCAL_MACHINE
debug: false
distributed_type: MULTI_GPU
downcast_bf16: 'no'
gpu_ids: all
machine_rank: 1
main_process_ip: 192.168.0.1
main_process_port: 29555
main_training_function: main
mixed_precision: fp16
num_machines: 2
num_processes: 16
rdzv_backend: static
same_network: true
tpu_env: []
tpu_use_cluster: false
tpu_use_sudo: false
use_cpu: false

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@ -15,11 +15,13 @@ CUDA_VISIBLE_DEVICES=0 python ../../src/train_bash.py \
--overwrite_cache \
--overwrite_output_dir \
--cutoff_len 1024 \
--preprocessing_num_workers 16 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--gradient_accumulation_steps 8 \
--lr_scheduler_type cosine \
--logging_steps 10 \
--warmup_steps 20 \
--save_steps 100 \
--eval_steps 100 \
--evaluation_strategy steps \

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@ -16,6 +16,7 @@ CUDA_VISIBLE_DEVICES=0 python ../../src/train_bash.py \
--overwrite_cache \
--overwrite_output_dir \
--cutoff_len 512 \
--preprocessing_num_workers 16 \
--per_device_train_batch_size 1 \
--gradient_accumulation_steps 8 \
--lr_scheduler_type cosine \

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@ -13,6 +13,7 @@ CUDA_VISIBLE_DEVICES=0 python ../../src/train_bash.py \
--overwrite_cache \
--overwrite_output_dir \
--cutoff_len 1024 \
--preprocessing_num_workers 16 \
--per_device_eval_batch_size 1 \
--max_samples 20 \
--predict_with_generate

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@ -12,11 +12,13 @@ CUDA_VISIBLE_DEVICES=0 python ../../src/train_bash.py \
--overwrite_cache \
--overwrite_output_dir \
--cutoff_len 1024 \
--preprocessing_num_workers 16 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--gradient_accumulation_steps 8 \
--lr_scheduler_type cosine \
--logging_steps 10 \
--warmup_steps 20 \
--save_steps 100 \
--eval_steps 100 \
--evaluation_strategy steps \

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@ -15,11 +15,13 @@ CUDA_VISIBLE_DEVICES=0 python ../../src/train_bash.py \
--overwrite_cache \
--overwrite_output_dir \
--cutoff_len 1024 \
--preprocessing_num_workers 16 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--gradient_accumulation_steps 8 \
--lr_scheduler_type cosine \
--logging_steps 10 \
--warmup_steps 20 \
--save_steps 100 \
--eval_steps 100 \
--evaluation_strategy steps \

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@ -13,11 +13,13 @@ CUDA_VISIBLE_DEVICES=0 python ../../src/train_bash.py \
--overwrite_cache \
--overwrite_output_dir \
--cutoff_len 1024 \
--preprocessing_num_workers 16 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--gradient_accumulation_steps 8 \
--lr_scheduler_type cosine \
--logging_steps 10 \
--warmup_steps 20 \
--save_steps 100 \
--eval_steps 100 \
--evaluation_strategy steps \