FUE

This is a sentence transformer model based on all-mpnet-base-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)

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Safetensors

Model size

0.1B params

Tensor type

F32

Evaluation results

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

28.538
map_at_1 on MTEB ArguAna (default)
test set self-reported

12.518
map_at_10 on MTEB ArguAna (default)
test set self-reported

22.123
map_at_100 on MTEB ArguAna (default)
test set self-reported

23.690
map_at_1000 on MTEB ArguAna (default)
test set self-reported

23.753
map_at_20 on MTEB ArguAna (default)
test set self-reported

23.143
map_at_3 on MTEB ArguAna (default)
test set self-reported

18.255
map_at_5 on MTEB ArguAna (default)
test set self-reported

20.101
mrr_at_1 on MTEB ArguAna (default)
test set self-reported

12.518
mrr_at_10 on MTEB ArguAna (default)
test set self-reported

22.118
mrr_at_100 on MTEB ArguAna (default)
test set self-reported

23.691
mrr_at_1000 on MTEB ArguAna (default)
test set self-reported

23.755
mrr_at_20 on MTEB ArguAna (default)
test set self-reported

23.145
mrr_at_3 on MTEB ArguAna (default)
test set self-reported

18.255
mrr_at_5 on MTEB ArguAna (default)
test set self-reported

20.090
nauc_map_at_1000_diff1 on MTEB ArguAna (default)
test set self-reported

9.323
nauc_map_at_1000_max on MTEB ArguAna (default)
test set self-reported

14.255
nauc_map_at_1000_std on MTEB ArguAna (default)
test set self-reported

0.672
nauc_map_at_100_diff1 on MTEB ArguAna (default)
test set self-reported

9.282
nauc_map_at_100_max on MTEB ArguAna (default)
test set self-reported

14.292