Open-Assistant/model/reward/instructor

Sections to train Reward Model (RM)

Trainer code based on huggingface. Compatible with deepspeed or accelerate

Install Python requirements

pip install -r requirements.txt

Write or inherit a configs/<config-name>.yml file to store training configuration details.

The configuration file must have at least all the keys present in configs/dummy.yml

Run training procedure

python trainer.py configs/<config-name>.yml

Additional axis labeling, this outputs a 4 summary quality evaluation metrics (score are normalized to 0-1 )

python summary_quality_trainer.py configs/test-bloomz-560m-quality.yml

The four summary are :

• overall

• accuracy

• coverage

• coherence

Dataset

For now we only supports webgpt and summary dataset from OpenAI. Once open-asisstant dataset are available it will be added here.

Model

Check out configs

Open-Assistant/model/reward/instructor/configs/
    bloomz-560m.yml
    electra-base-dis-webgpt.yml
    galactica-125m.yml
    galactica-1b.yml

You can add new huggingface model as you want.