Holistic Evaluation of Language Models (HELM), a framework to increase the transparency of language models (https://arxiv.org/abs/2211.09110). This framework is also used to evaluate text-to-image models in HEIM (https://arxiv.org/abs/2311.04287) and vision-language models in VHELM (https://arxiv.org/abs/2410.07112).
When running with the example run_spec: mmlu:subject=anatomy,model=openai/gpt2 and no caching, the HuggingFace client outputs the following warning on every call:
Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation
This is annoying, but I'm not sure if it hurts anything. I think a fix could be to pass pad_token_id to generate with the value being either:
When running with the example run_spec:
mmlu:subject=anatomy,model=openai/gpt2
and no caching, the HuggingFace client outputs the following warning on every call:This is annoying, but I'm not sure if it hurts anything. I think a fix could be to pass
pad_token_id
togenerate
with the value being either:tokenizer.eos_token_id
as recommended in this stackoverflow.However, I'm not sure what impacts, if any, this could have, so I'm going to leave it to someone else to make it.