FAE

This is a sentence transformer model based on e5-large-v2.

Usage

from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is encoded"]

model = SentenceTransformer('FAE')
embeddings = model.encode(sentences)
print(embeddings)

Downloads last month: 37

Safetensors

Model size

0.3B params

Tensor type

F32

Model tree for qinxianliu/FAE-v1

Quantizations

1 model

Evaluation results

main_score on MTEB ArguAna (default)
test set self-reported

46.744
map_at_1 on MTEB ArguAna (default)
test set self-reported

22.404
map_at_10 on MTEB ArguAna (default)
test set self-reported

37.445
map_at_100 on MTEB ArguAna (default)
test set self-reported

38.608
map_at_1000 on MTEB ArguAna (default)
test set self-reported

38.617
map_at_20 on MTEB ArguAna (default)
test set self-reported

38.337
map_at_3 on MTEB ArguAna (default)
test set self-reported

32.112
map_at_5 on MTEB ArguAna (default)
test set self-reported

34.815
mrr_at_1 on MTEB ArguAna (default)
test set self-reported

22.902
mrr_at_10 on MTEB ArguAna (default)
test set self-reported

37.615
mrr_at_100 on MTEB ArguAna (default)
test set self-reported

38.784
mrr_at_1000 on MTEB ArguAna (default)
test set self-reported

38.794
mrr_at_20 on MTEB ArguAna (default)
test set self-reported

38.514
mrr_at_3 on MTEB ArguAna (default)
test set self-reported

32.314
mrr_at_5 on MTEB ArguAna (default)
test set self-reported

34.977
nauc_map_at_1000_diff1 on MTEB ArguAna (default)
test set self-reported

7.863
nauc_map_at_1000_max on MTEB ArguAna (default)
test set self-reported

-13.041
nauc_map_at_1000_std on MTEB ArguAna (default)
test set self-reported

-7.702
nauc_map_at_100_diff1 on MTEB ArguAna (default)
test set self-reported

7.858
nauc_map_at_100_max on MTEB ArguAna (default)
test set self-reported

-13.030