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73cc8d2 | 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 | from __future__ import annotations
import pytest
from mteb.evaluation.evaluators import PairClassificationEvaluator
TOL = 0.0001
class TestPairClassificationEvaluator:
def test_accuracy(self):
scores = [6.12, 5.39, 5.28, 5.94, 6.34, 6.47, 7.88, 6.62, 8.04, 5.9]
labels = [0, 0, 0, 0, 1, 0, 0, 0, 1, 0]
high_score_more_similar = True
acc, acc_threshold = PairClassificationEvaluator.find_best_acc_and_threshold(
scores, labels, high_score_more_similar
)
assert acc == pytest.approx(0.9, TOL)
assert acc_threshold == pytest.approx(7.95999, TOL)
def test_f1(self):
scores = [6.12, 5.39, 5.28, 5.94, 6.34, 6.47, 7.88, 6.62, 8.04, 5.9]
labels = [0, 0, 0, 0, 1, 0, 0, 0, 1, 0]
high_score_more_similar = True
f1, precision, recall, f1_threshold = (
PairClassificationEvaluator.find_best_f1_and_threshold(
scores, labels, high_score_more_similar
)
)
assert f1 == pytest.approx(0.66666, TOL)
assert precision == pytest.approx(1.0, TOL)
assert recall == pytest.approx(0.5, TOL)
assert f1_threshold == pytest.approx(7.95999, TOL)
def test_ap(self):
scores = [6.12, 5.39, 5.28, 5.94, 6.34, 6.47, 7.88, 6.62, 8.04, 5.9]
labels = [0, 0, 0, 0, 1, 0, 0, 0, 1, 0]
high_score_more_similar = True
ap = PairClassificationEvaluator.ap_score(
scores, labels, high_score_more_similar
)
assert ap == pytest.approx(0.7, TOL)
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