add npu examples

Former-commit-id: af343034dd
This commit is contained in:
hiyouga
2024-05-14 23:32:53 +08:00
parent e32a44fe6b
commit f5df1ceaf1
9 changed files with 103 additions and 19 deletions

View File

@@ -0,0 +1,18 @@
{
"train_batch_size": "auto",
"train_micro_batch_size_per_gpu": "auto",
"gradient_accumulation_steps": "auto",
"gradient_clipping": "auto",
"zero_allow_untested_optimizer": true,
"fp16": {
"enabled": "auto",
"loss_scale": 0,
"loss_scale_window": 1000,
"initial_scale_power": 16,
"hysteresis": 2,
"min_loss_scale": 1
},
"bf16": {
"enabled": "auto"
}
}

View File

@@ -6,7 +6,7 @@ RANK=0
MASTER_ADDR=192.168.0.1
MASTER_PORT=29500
CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.run \
CUDA_VISIBLE_DEVICES=0,1,2,3 torchrun \
--nproc_per_node $NPROC_PER_NODE \
--nnodes $NNODES \
--node_rank $RANK \

View File

@@ -1,9 +1,15 @@
#!/bin/bash
NPROC_PER_NODE=4
NNODES=1
RANK=0
MASTER_ADDR=127.0.0.1
MASTER_PORT=29500
CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.run \
CUDA_VISIBLE_DEVICES=0,1,2,3 torchrun \
--nproc_per_node $NPROC_PER_NODE \
--nnodes 1 \
--standalone \
--nnodes $NNODES \
--node_rank $RANK \
--master_addr $MASTER_ADDR \
--master_port $MASTER_PORT \
src/train.py examples/full_multi_gpu/llama3_full_sft.yaml

View File

@@ -1,9 +1,15 @@
#!/bin/bash
NPROC_PER_NODE=4
NNODES=1
RANK=0
MASTER_ADDR=127.0.0.1
MASTER_PORT=29500
CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.run \
CUDA_VISIBLE_DEVICES=0,1,2,3 torchrun \
--nproc_per_node $NPROC_PER_NODE \
--nnodes 1 \
--standalone \
--nnodes $NNODES \
--node_rank $RANK \
--master_addr $MASTER_ADDR \
--master_port $MASTER_PORT \
src/train.py examples/lora_multi_gpu/llama3_lora_sft_ds.yaml

View File

@@ -0,0 +1,15 @@
#!/bin/bash
NPROC_PER_NODE=4
NNODES=1
RANK=0
MASTER_ADDR=127.0.0.1
MASTER_PORT=29500
ASCEND_RT_VISIBLE_DEVICES=0,1,2,3 torchrun \
--nproc_per_node $NPROC_PER_NODE \
--nnodes $NNODES \
--node_rank $RANK \
--master_addr $MASTER_ADDR \
--master_port $MASTER_PORT \
src/train.py examples/lora_multi_gpu/llama3_lora_sft_ds.yaml

View File

@@ -0,0 +1,42 @@
# model
model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
# method
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
# ddp
ddp_timeout: 180000000
deepspeed: examples/deepspeed/ds_z0_config.json
# dataset
dataset: identity,alpaca_gpt4_en
template: llama3
cutoff_len: 1024
max_samples: 1000
overwrite_cache: true
preprocessing_num_workers: 16
# output
output_dir: saves/llama3-8b/lora/sft
logging_steps: 10
save_steps: 500
plot_loss: true
overwrite_output_dir: true
# train
per_device_train_batch_size: 1
gradient_accumulation_steps: 2
learning_rate: 0.0001
num_train_epochs: 3.0
lr_scheduler_type: cosine
warmup_steps: 0.1
fp16: true
# eval
val_size: 0.1
per_device_eval_batch_size: 1
evaluation_strategy: steps
eval_steps: 500