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I'm trying to reproduce the Score Card results using the lm-evaluation-harness. Based on this comment https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard/discussions/60#648c567bb010e9fed5f92328 I ran this command on commit 441e6ac1 of the lm-evaluation harness repository. The evaluation results I get do not match the score card results for LAMBADA.

python main.py \
    --model=hf-causal-experimental \
    --model_args="pretrained=gpt2,use_accelerate=True" \
    --tasks=lambada_openai \
    --num_fewshot=0 \
    --batch_size=2 \
    --output_path=output

My results on commit 4416ac1

{
  "results": {
    "lambada_openai": {
      "ppl": 40.05542021199565,
      "ppl_stderr": 1.4880684857031479,
      "acc": 0.32563555210556955, (should be 45.99%)
      "acc_stderr": 0.00652867895783546
    }
  },
  "versions": {
    "lambada_openai": 0
  },
  "config": {
    "model": "hf-causal-experimental",
    "model_args": "pretrained=gpt2,use_accelerate=True",
    "num_fewshot": 0,
    "batch_size": "2",
    "device": null,
    "no_cache": false,
    "limit": null,
    "bootstrap_iters": 100000,
    "description_dict": {}
  }
}

My results on commit b281b09 (according to the About tab on https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard)
I also delete lm_cache in between to make sure these results were not cached from previous runs.

{
  "results": {
    "lambada_openai": {
      "ppl": 40.05542021199565,
      "ppl_stderr": 1.4880684857031479,
      "acc": 0.32563555210556955, (should be 45.99%)
      "acc_stderr": 0.00652867895783546
    }
  },
  "versions": {
    "lambada_openai": 0
  },
  "config": {
    "model": "hf-causal-experimental",
    "model_args": "pretrained=gpt2,use_accelerate=True",
    "num_fewshot": 0,
    "batch_size": "2",
    "batch_sizes": [],
    "device": null,
    "no_cache": false,
    "limit": null,
    "bootstrap_iters": 100000,
    "description_dict": {}
  }
}

But the Score Card (https://huggingface.co./openai-community/gpt2) achieves 45.99% acc for LAMBADA.

I did manage to reproduce the ARC Challenge results for GPT2 (using same commit as above):

Command:

python main.py \
     --model=hf-causal-experimental \
     --model_args="pretrained=gpt2,use_accelerate=True" \
     --tasks=arc_challenge \
     --num_fewshot=25 \
     --batch_size=2 \
     --output_path=output

My results

 "results": {
    "arc_challenge": {
      "acc": 0.20051194539249148,
      "acc_stderr": 0.011700318050499373,
      "acc_norm": 0.21928327645051193,
      "acc_norm_stderr": 0.012091245787615723
    }

Results from https://huggingface.co./datasets/open-llm-leaderboard/details_gpt2

"harness|arc:challenge|25": {
        "acc": 0.197098976109215,
        "acc_stderr": 0.011625047669880633,
        "acc_norm": 0.22013651877133106,
        "acc_norm_stderr": 0.01210812488346097
    },

Can anyone share the commands for reproducing the GPT2 score card results?