31 lines
1.8 KiB
Markdown
31 lines
1.8 KiB
Markdown
# Harness Evalution
|
|
[Harness evalution](https://github.com/EleutherAI/lm-evaluation-harness) allows users to eaisly get accuracy on various datasets. Here we have enabled harness evalution with BigDL-LLM under
|
|
[Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) settings.
|
|
Before running, make sure to have [bigdl-llm](../../../README.md) installed.
|
|
|
|
## Install Harness
|
|
```bash
|
|
git clone https://github.com/EleutherAI/lm-evaluation-harness.git
|
|
cd lm-evaluation-harness
|
|
git checkout e81d3cc
|
|
pip install -e .
|
|
```
|
|
|
|
## Run
|
|
run `python run_llb.py`. `run_llb.py` combines some arguments in `main.py` to make evalutions easier. The mapping of arguments is defined as a dict in [`llb.py`](llb.py).
|
|
|
|
### Evaluation on CPU
|
|
```python
|
|
python run_llb.py --model bigdl-llm --pretrained /path/to/model --precision nf3 sym_int4 nf4 --device cpu --tasks hellaswag arc mmlu truthfulqa --batch 1 --no_cache
|
|
```
|
|
### Evaluation on Intel GPU
|
|
```python
|
|
python run_llb.py --model bigdl-llm --pretrained /path/to/model --precision nf3 sym_int4 nf4 --device xpu --tasks hellaswag arc mmlu truthfulqa --batch 1 --no_cache
|
|
```
|
|
### Evaluation using multiple Intel GPU
|
|
```python
|
|
python run_multi_llb.py --model bigdl-llm --pretrained /path/to/model --precision nf3 sym_int4 nf4 --device xpu:0,2,3 --tasks hellaswag arc mmlu truthfulqa --batch 1 --no_cache
|
|
```
|
|
Taking example above, the script will fork 3 processes, each for one xpu, to execute the tasks.
|
|
## Results
|
|
We follow [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) to record our metrics, `acc_norm` for `hellaswag` and `arc_challenge`, `mc2` for `truthful_qa` and `acc` for `mmlu`. For `mmlu`, there are 57 subtasks which means users may need to average them manually to get final result.
|