33 lines
1.0 KiB
Python
33 lines
1.0 KiB
Python
# example run command
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# python dev/eval/summarize_eval.py lm-evaluation-harness/results/result774M
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# this script is optional, the run_eval.sh should already print these
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# but this script can be used to re-print them
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import json, sys
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RESULT = sys.argv[1]
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print("-"*40)
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key = {"arc_challenge_25shot.json": "acc_norm",
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"gsm8k_5shot.json": "acc",
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"hellaswag_10shot.json": "acc_norm",
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"mmlu_5shot.json": "acc",
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"truthfulqa_0shot.json": "mc2",
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"winogrande_5shot.json": "acc"
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}
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total = 0
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for test in ["arc_challenge_25shot.json", "gsm8k_5shot.json", "hellaswag_10shot.json", "mmlu_5shot.json", "truthfulqa_0shot.json", "winogrande_5shot.json"]:
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data = json.loads(open("./%s/%s"%(RESULT, test)).read())
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r_count = 0
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r_total = 0
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for test_name in data['results']:
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r_count += 1
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r_total += data['results'][test_name][key[test]]
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score = (r_total*100)/r_count
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print(f"{test:<30} : {score:.4f}")
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total += score
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average = total / 6.0
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print("-"*40)
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print(f"Average Score : {average:.4f}")
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