mirror of https://github.com/hpcaitech/ColossalAI
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
45 lines
1.3 KiB
45 lines
1.3 KiB
## 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
|
|
```
|
|
|
|
### Bert-Finetune Results
|
|
|
|
| Plugin | Accuracy | F1-score | GPU number |
|
|
| -------------- | -------- | -------- | -------- |
|
|
| torch_ddp | 84.4% | 88.6% | 2 |
|
|
| torch_ddp_fp16 | 84.7% | 88.8% | 2 |
|
|
| gemini | 84.0% | 88.4% | 2 |
|
|
| hybrid_parallel | 84.5% | 88.6% | 4 |
|
|
|
|
|
|
## 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 |
|