ColossalAI/applications/Chat/benchmarks
flybird11111 be400a0936
[chat] fix gemini strategy (#4698)
* [chat] fix gemini strategy

* [chat] fix gemini strategy

* [chat] fix gemini strategy

* [chat] fix gemini strategy

* g# This is a combination of 2 commits.

[chat] fix gemini strategy

fox

* [chat] fix gemini strategy

update llama2 example

[chat] fix gemini strategy

* [fix] fix gemini strategy

* [fix] fix gemini strategy

* [fix] fix gemini strategy

* [fix] fix gemini strategy

* [fix] fix gemini strategy

* [fix] fix gemini strategy

* [fix] fix gemini strategy

* [fix] fix gemini strategy

* [fix] fix gemini strategy

* [fix] fix gemini strategy

* fix

* fix

* fix

* fix

* fix

* Update train_prompts.py
2023-09-27 13:15:32 +08:00
..
ray [misc] update pre-commit and run all files (#4752) 2023-09-19 14:20:26 +08:00
README.md [doc] update Coati README (#4405) 2023-08-14 15:26:27 +08:00
benchmark_opt_lora_dummy.py [chat] fix gemini strategy (#4698) 2023-09-27 13:15:32 +08:00

README.md

Benchmarks

Benchmark OPT with LoRA on dummy prompt data

We provide various OPT models (string in parentheses is the corresponding model name used in this script):

  • OPT-125M (125m)
  • OPT-350M (350m)
  • OPT-700M (700m)
  • OPT-1.3B (1.3b)
  • OPT-2.7B (2.7b)
  • OPT-3.5B (3.5b)
  • OPT-5.5B (5.5b)
  • OPT-6.7B (6.7b)
  • OPT-10B (10b)
  • OPT-13B (13b)

We also provide various training strategies:

  • ddp: torch DDP
  • colossalai_gemini: ColossalAI GeminiDDP with placement_policy="cuda", like zero3
  • colossalai_gemini_cpu: ColossalAI GeminiDDP with placement_policy="cpu", like zero3-offload
  • colossalai_zero2: ColossalAI zero2
  • colossalai_zero2_cpu: ColossalAI zero2-offload
  • colossalai_zero1: ColossalAI zero1
  • colossalai_zero1_cpu: ColossalAI zero1-offload

We only support torchrun to launch now. E.g.

# run OPT-125M with no lora (lora_rank=0) on single-node single-GPU with min batch size
torchrun --standalone --nproc_per_node 1 benchmark_opt_lora_dummy.py \
    --model 125m --critic_model 125m --strategy ddp \
    --experience_batch_size 1 --train_batch_size 1 --lora_rank 0
# run Actor (OPT-1.3B) and Critic (OPT-350M) with lora_rank=4 on single-node 4-GPU
torchrun --standalone --nproc_per_node 4 benchmark_opt_lora_dummy.py \
    --model 1.3b --critic_model 350m --strategy colossalai_zero2 --lora_rank 4