Spaces:
Running
Running
File size: 3,327 Bytes
a19f11e 076f69b a19f11e 50a5912 076f69b 50a5912 076f69b a19f11e 076f69b a19f11e 076f69b a19f11e 076f69b a19f11e 519572d a19f11e 076f69b a19f11e 076f69b a19f11e 076f69b b272a27 076f69b a19f11e 076f69b a19f11e 076f69b b272a27 076f69b |
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 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 |
"""
It provides a leaderboard component.
"""
from collections import defaultdict
import enum
import math
import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore
import gradio as gr
import pandas as pd
from credentials import get_credentials_json
# TODO(#21): Fix auto-reload issue related to the initialization of Firebase.
firebase_admin.initialize_app(credentials.Certificate(get_credentials_json()))
db = firestore.client()
class LeaderboardTab(enum.Enum):
SUMMARIZATION = "Summarization"
TRANSLATION = "Translation"
# Ref: https://colab.research.google.com/drive/1RAWb22-PFNI-X1gPVzc927SGUdfr6nsR?usp=sharing#scrollTo=QLGc6DwxyvQc pylint: disable=line-too-long
def compute_elo(battles, k=4, scale=400, base=10, initial_rating=1000):
rating = defaultdict(lambda: initial_rating)
for model_a, model_b, winner in battles[["model_a", "model_b",
"winner"]].itertuples(index=False):
rating_a = rating[model_a]
rating_b = rating[model_b]
expected_score_a = 1 / (1 + base**((rating_b - rating_a) / scale))
expected_score_b = 1 / (1 + base**((rating_a - rating_b) / scale))
scored_point_a = 0.5 if winner == "tie" else int(winner == "model_a")
rating[model_a] += k * (scored_point_a - expected_score_a)
rating[model_b] += k * (1 - scored_point_a - expected_score_b)
return rating
def get_docs(tab):
if tab == LeaderboardTab.SUMMARIZATION:
return db.collection("arena-summarizations").order_by("timestamp").stream()
if tab == LeaderboardTab.TRANSLATION:
return db.collection("arena-translations").order_by("timestamp").stream()
def load_elo_ratings(tab):
docs = get_docs(tab)
battles = []
for doc in docs:
data = doc.to_dict()
battles.append({
"model_a": data["model_a"],
"model_b": data["model_b"],
"winner": data["winner"]
})
if not battles:
return
battles = pd.DataFrame(battles)
ratings = compute_elo(battles)
sorted_ratings = sorted(ratings.items(), key=lambda x: x[1], reverse=True)
return [[i + 1, model, math.floor(rating + 0.5)]
for i, (model, rating) in enumerate(sorted_ratings)]
def load_summarization_elo_ratings():
return load_elo_ratings(LeaderboardTab.SUMMARIZATION)
def load_translation_elo_ratings():
return load_elo_ratings(LeaderboardTab.TRANSLATION)
LEADERBOARD_UPDATE_INTERVAL = 600 # 10 minutes
LEADERBOARD_INFO = "The leaderboard is updated every 10 minutes."
def build_leaderboard():
with gr.Tabs():
with gr.Tab(LeaderboardTab.SUMMARIZATION.value):
gr.Dataframe(headers=["Rank", "Model", "Elo rating"],
datatype=["number", "str", "number"],
value=load_summarization_elo_ratings,
every=LEADERBOARD_UPDATE_INTERVAL,
elem_classes="leaderboard")
gr.Markdown(LEADERBOARD_INFO)
# TODO(#9): Add language filter options.
with gr.Tab(LeaderboardTab.TRANSLATION.value):
gr.Dataframe(headers=["Rank", "Model", "Elo rating"],
datatype=["number", "str", "number"],
value=load_translation_elo_ratings,
every=LEADERBOARD_UPDATE_INTERVAL,
elem_classes="leaderboard")
gr.Markdown(LEADERBOARD_INFO)
|