6

Table 3: Results on the MTEB benchmark [40] (56 datasets in English subset). Here we only report
averaged numbers on each task category for space reasons, please check out Appendix B for a
detailed version. BERT-FTbase uses the same ﬁne-tuning data as E5 but initializes from BERTbase.

Class. Clust.

PairClass. Rerank Retr.
15

4

3

Summ. Avg
56

1

# of datasets →
Unsupervised models
Glove
BERT
SimCSE-BERT-unsup
E5-PTsmall
E5-PTbase
E5-PTlarge
Supervised models
SimCSE-BERT-sup
BERT-FTbase
Contriever
GTRlarge
Sentence-T5large
E5small
E5base
E5large
Larger models
GTRxxl
Sentence-T5xxl

12

57.3
61.7
62.5
67.0
67.9
69.0

67.3
68.7
66.7
67.1
72.3
71.7
72.6
73.1

67.4
73.4

11

27.7
30.1
29.0
41.7
43.4
44.3

33.4
33.9
41.1
41.6
41.7
39.5
42.1
43.3

42.4
43.7

70.9
56.3
70.3
78.2
79.2
80.3

73.7
82.6
82.5
85.3
85.0
85.1
85.1
85.9

86.1
85.1

STS
10

61.9
54.4
74.3
68.8
69.5
69.9

79.1
79.2
76.5
78.2
81.8
80.9
81.0
82.1

78.4
82.6

21.6
10.6
20.3
40.8
42.9
44.2
E5