Normalize lm-eval command between baseline and correctness test (#18560)

Signed-off-by: mgoin <mgoin64@gmail.com>
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Michael Goin 2025-07-10 22:27:32 +09:00 committed by GitHub
parent be1e128dfb
commit 1a4f35e2ea
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2 changed files with 4 additions and 2 deletions

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@ -46,6 +46,6 @@ while getopts "m:b:l:f:t:" OPT; do
done
lm_eval --model vllm \
--model_args "pretrained=$MODEL,tensor_parallel_size=$TP_SIZE,distributed_executor_backend=ray,trust_remote_code=true,max_model_len=4096" \
--model_args "pretrained=$MODEL,tensor_parallel_size=$TP_SIZE,add_bos_token=true,trust_remote_code=true,max_model_len=4096" \
--tasks gsm8k --num_fewshot "$FEWSHOT" --limit "$LIMIT" \
--batch_size "$BATCH_SIZE"

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@ -18,12 +18,14 @@ RTOL = 0.08
def launch_lm_eval(eval_config, tp_size):
trust_remote_code = eval_config.get("trust_remote_code", False)
max_model_len = eval_config.get("max_model_len", 4096)
model_args = (
f"pretrained={eval_config['model_name']},"
f"tensor_parallel_size={tp_size},"
f"enforce_eager=true,"
f"add_bos_token=true,"
f"trust_remote_code={trust_remote_code}"
f"trust_remote_code={trust_remote_code},"
f"max_model_len={max_model_len}"
)
results = lm_eval.simple_evaluate(
model="vllm",