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import os
import json
from glob import glob
import pandas as pd
from datasets import load_dataset
os.makedirs("analysis/flan_ul2_additional_analysis", exist_ok=True)
data = load_dataset("cardiffnlp/relentless_full", split="test")
data = {i['relation_type']: i for i in data}
pred_zero = {}
for i in glob("results/lm_qa_zeroshot/flan-ul2/*.jsonl"):
r = os.path.basename(i).replace("__", "/").replace("_", " ").replace("ppl.", "").replace("is ", "").replace(".jsonl", "")
with open(i) as f:
pred_zero[r] = [json.loads(l)['perplexity'] for l in f.read().split("\n")]
pred_few = {}
for i in glob("results/lm_qa_1shots_1seed/flan-ul2/*.jsonl"):
r = os.path.basename(i).replace("__", "/").replace("_", " ").replace("ppl.", "").replace("is ", "").replace(".jsonl", "")
with open(i) as f:
pred_few[r] = [json.loads(l)['perplexity'] for l in f.read().split("\n")]
def get_rank(score):
s2r = {s: n for n, s in enumerate(sorted(score))}
return [s2r[s] for s in score]
for k, v in data.items():
df = pd.DataFrame({
"pairs": v['pairs'],
"score_fewshot": pred_few[k],
"score_zeroshot": pred_zero[k],
"score_true": v["scores_mean"],
"rank_fewshot": get_rank(pred_few[k]),
"rank_zeroshot": get_rank(pred_zero[k]),
"rank_true": v["ranks"],
})
df.to_csv(f"analysis/flan_ul2_additional_analysis/{k[:4]}.csv", index=False)
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