History

Hongxin Liu 7f8b16635b [misc] refactor launch API and tensor constructor (#5666 ) * [misc] remove config arg from initialize * [misc] remove old tensor contrusctor * [plugin] add npu support for ddp * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [devops] fix doc test ci * [test] fix test launch * [doc] update launch doc --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>		2024-04-29 10:40:11 +08:00
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README.md	[example] add train resnet/vit with booster example (#3694 )	2023-05-08 10:42:30 +08:00
data.py	[misc] update pre-commit and run all files (#4752 )	2023-09-19 14:20:26 +08:00
finetune.py	[misc] refactor launch API and tensor constructor (#5666 )	2024-04-29 10:40:11 +08:00
requirements.txt	[example] add train resnet/vit with booster example (#3694 )	2023-05-08 10:42:30 +08:00
test_ci.sh	[fix] fix weekly runing example (#4787 )	2023-09-25 16:19:33 +08:00

README.md

Finetune BERT on GLUE

🚀 Quick Start

This example provides a training script, which provides an example of finetuning BERT on GLUE dataset.

Training Arguments
- -t, --task: GLUE task to run. Defaults to mrpc.
- -p, --plugin: Plugin to use. Choices: torch_ddp, torch_ddp_fp16, gemini, low_level_zero. Defaults to torch_ddp.
- --target_f1: Target f1 score. Raise exception if not reached. Defaults to None.

Install requirements

pip install -r requirements.txt

Train

# train with torch DDP with fp32
colossalai run --nproc_per_node 4 finetune.py

# train with torch DDP with mixed precision training
colossalai run --nproc_per_node 4 finetune.py -p torch_ddp_fp16

# train with gemini
colossalai run --nproc_per_node 4 finetune.py -p gemini

# train with low level zero
colossalai run --nproc_per_node 4 finetune.py -p low_level_zero

Expected F1-score will be:

Model	Single-GPU Baseline FP32	Booster DDP with FP32	Booster DDP with FP16	Booster Gemini	Booster Low Level Zero
bert-base-uncased	0.86	0.88	0.87	0.88	0.89