Spaces:
Sleeping
Sleeping
File size: 1,436 Bytes
5d015e0 47dba14 5d015e0 47dba14 5d015e0 79e5cbd 479ad42 5d015e0 d1beb96 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 |
from dataclasses import dataclass
from enum import Enum
@dataclass
class Task:
benchmark: str
metric: str
col_name: str
# Select your tasks here
# ---------------------------------------------------
class Tasks(Enum):
# task_key, metric_key, name to display in the leaderboard
task0 = Task("avg", "score", "Avg")
task1 = Task("nar", "score", "Nar")
task2 = Task("mt", "score", "MT")
task3 = Task("con", "score", "Con")
task4 = Task("if", "score", "IF")
task5 = Task("scn", "score", "Scn")
task6 = Task("saf", "score", "Saf")
task7 = Task("att", "score", "Att")
# ---------------------------------------------------
# Your leaderboard name
TITLE = """<h1 align="center" id="space-title">🎭 RoleRMBench Leaderboard</h1>"""
# What does your leaderboard evaluate?
INTRODUCTION_TEXT = """
RoleRMBench evaluates reward models on role-playing scenarios across multiple dimensions.
For more information, please refer to: [https://github.com/Dear-Sloth/RoleRMBench](https://github.com/Dear-Sloth/RoleRMBench)
"""
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
CITATION_BUTTON_TEXT = r"""@misc{ ,
title={RoleRMBench & RoleRM: Towards Reward Modeling for Profile-Based Role Play in Dialogue Systems},
author={ },
year={2025},
eprint={ },
archivePrefix={arXiv},
primaryClass={ },
url={https://arxiv.org/abs/ },
}"""
|