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README.md | 1 year ago | |
benchmark.py | 1 year ago | |
benchmark.sh | 1 year ago | |
benchmark_utils.py | 1 year ago | |
data.py | 1 year ago | |
finetune.py | 1 year ago | |
requirements.txt | 1 year ago | |
test_ci.sh | 1 year ago |
README.md
Overview
This directory includes two parts: Using the Booster API finetune Huggingface Bert and AlBert models and benchmarking Bert and AlBert models with different Booster Plugin.
Finetune
bash test_ci.sh
Benchmark
bash benchmark.sh
Now include these metrics in benchmark: CUDA mem occupy, throughput and the number of model parameters. If you have custom metrics, you can add them to benchmark_util.
Results
Bert
max cuda mem | throughput(sample/s) | params | |
---|---|---|---|
ddp | 21.44 GB | 3.0 | 82M |
ddp_fp16 | 16.26 GB | 11.3 | 82M |
gemini | 11.0 GB | 12.9 | 82M |
low_level_zero | 11.29 G | 14.7 | 82M |
AlBert
max cuda mem | throughput(sample/s) | params | |
---|---|---|---|
ddp | OOM | ||
ddp_fp16 | OOM | ||
gemini | 69.39 G | 1.3 | 208M |
low_level_zero | 56.89 G | 1.4 | 208M |