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import os
from datasets import load_dataset, DatasetDict
import jsonlines
###############
# Load datasets
###############
raw_datasets = load_dataset("HuggingFaceH4/ultrafeedback_binarized")
# convert to just train and test, not necessary but it looks better
raw_datasets = DatasetDict(
{
"train": raw_datasets["train_prefs"],
"test": raw_datasets["test_prefs"],
}
)
os.makedirs(os.path.join("data", "pairwise"), exist_ok=True)
for split in ["train", "test"]:
with open(
os.path.join("data", "pairwise", f"llama3_dpo_{split}_filtered.jsonl"), "w"
) as f:
writer = jsonlines.Writer(f)
for item in raw_datasets[split]:
item["chosen"] = item["chosen"]
item["rejected"] = item["rejected"]
writer.write(item)
os.makedirs(os.path.join("data", "sft"), exist_ok=True)
for split in ["train", "test"]:
with open(
os.path.join("data", "sft", f"llama3_sft_{split}_filtered.jsonl"), "w"
) as f:
writer = jsonlines.Writer(f)
for item in raw_datasets[split]:
item["messages"] = item["chosen"]
writer.write(item)
os.makedirs(os.path.join("data", "kto"), exist_ok=True)
for split in ["train", "test"]:
with open(
os.path.join("data", "kto", f"llama3_kto_{split}_filtered.jsonl"), "w"
) as f:
writer = jsonlines.Writer(f)
for item in raw_datasets[split]:
item["messages"] = item["chosen"]
item["reward"] = 1
writer.write(item)
item["messages"] = item["rejected"]
item["reward"] = -1
writer.write(item)
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