Files
open-instruct/configs/beaker_configs/default_finetune_qlora_multinode.yaml
Yizhong WangandGitHub e96a951642 Propagate failure/preemptation and set timeout for multinode training (#278)
* Add parameters in multinode training to propagate failure/preemptation and set timeout.
2024-08-20 13:07:35 -07:00

78 lines
2.3 KiB
YAML

version: v2
description: open-instruct-finetune-multinode-test
tasks:
- name: open-instruct-finetune-multinode-test
replicas: 4
leaderSelection: true
hostNetworking: true
propagateFailure: true
propagatePreemption: true
synchronizedStartTimeout: 15m
image:
beaker: Yizhongw03/open-instruct-multi-node
command: [
'/bin/sh', '-c'
]
arguments: ['
unset CUDA_LAUNCH_BLOCKING && accelerate launch
--mixed_precision bf16
--num_machines 4
--num_processes 32
--machine_rank $BEAKER_REPLICA_RANK
--main_process_ip $BEAKER_LEADER_REPLICA_HOSTNAME
--main_process_port 29400
open_instruct/finetune.py
--model_name_or_path /net/nfs.cirrascale/allennlp/yizhongw/hf_llama2_models/70B
--tokenizer_name /net/nfs.cirrascale/allennlp/yizhongw/hf_llama2_models/70B
--use_slow_tokenizer
--train_file /net/nfs.cirrascale/allennlp/yizhongw/open-instruct-public/data/processed/tulu/tulu_v1_mix.jsonl
--use_flash_attn
--use_lora
--use_qlora
--lora_rank 64
--lora_alpha 64
--lora_dropout 0.1
--gradient_checkpointing
--max_seq_length 2048
--preprocessing_num_workers 64
--per_device_train_batch_size 1
--gradient_accumulation_steps 4
--learning_rate 2e-5
--lr_scheduler_type linear
--warmup_ratio 0.03
--weight_decay 0.
--num_train_epochs 5
--output_dir /output/
--with_tracking
--report_to tensorboard
--logging_steps 1
']
envVars:
- name: CUDA_DEVICE_ORDER
value: PCI_BUS_ID
- name: TRANSFORMERS_CACHE
value: ./cache/
- name: WANDB_PROJECT
value: open-instruct
- name: WANDB_WATCH
value: false
- name: WANDB_LOG_MODEL
value: false
- name: WANDB_DISABLED
value: true
- name: NCCL_NET
value: IB
- name: NCCL_DEBUG
value: INFO
datasets:
- mountPath: /net/nfs.cirrascale
source:
hostPath: /net/nfs.cirrascale
result:
path: /output
resources:
gpuCount: 8
context:
priority: high
constraints:
cluster: [ai2/general-cirrascale-a100-80g-ib]