spacemanidol commited on
Commit
3b0645c
1 Parent(s): aa4caa8

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +2801 -2
README.md CHANGED
@@ -1,3 +1,2802 @@
1
  ---
2
- license: apache-2.0
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
+ tags:
3
+ - mteb
4
+ - arctic
5
+ - arctic-embed
6
+ model-index:
7
+ - name: snowflake-arctic-embed-s
8
+ results:
9
+ - task:
10
+ type: Classification
11
+ dataset:
12
+ type: mteb/amazon_counterfactual
13
+ name: MTEB AmazonCounterfactualClassification (en)
14
+ config: en
15
+ split: test
16
+ revision: e8379541af4e31359cca9fbcf4b00f2671dba205
17
+ metrics:
18
+ - type: accuracy
19
+ value: 71.17910447761193
20
+ - type: ap
21
+ value: 33.15833652904991
22
+ - type: f1
23
+ value: 64.86214791591543
24
+ - task:
25
+ type: Classification
26
+ dataset:
27
+ type: mteb/amazon_polarity
28
+ name: MTEB AmazonPolarityClassification
29
+ config: default
30
+ split: test
31
+ revision: e2d317d38cd51312af73b3d32a06d1a08b442046
32
+ metrics:
33
+ - type: accuracy
34
+ value: 78.750325
35
+ - type: ap
36
+ value: 72.83242788470943
37
+ - type: f1
38
+ value: 78.63968044029453
39
+ - task:
40
+ type: Classification
41
+ dataset:
42
+ type: mteb/amazon_reviews_multi
43
+ name: MTEB AmazonReviewsClassification (en)
44
+ config: en
45
+ split: test
46
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
47
+ metrics:
48
+ - type: accuracy
49
+ value: 38.264
50
+ - type: f1
51
+ value: 37.140269688532825
52
+ - task:
53
+ type: Retrieval
54
+ dataset:
55
+ type: mteb/arguana
56
+ name: MTEB ArguAna
57
+ config: default
58
+ split: test
59
+ revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
60
+ metrics:
61
+ - type: map_at_1
62
+ value: 32.646
63
+ - type: map_at_10
64
+ value: 48.372
65
+ - type: map_at_100
66
+ value: 49.207
67
+ - type: map_at_1000
68
+ value: 49.214
69
+ - type: map_at_3
70
+ value: 43.611
71
+ - type: map_at_5
72
+ value: 46.601
73
+ - type: mrr_at_1
74
+ value: 33.144
75
+ - type: mrr_at_10
76
+ value: 48.557
77
+ - type: mrr_at_100
78
+ value: 49.385
79
+ - type: mrr_at_1000
80
+ value: 49.392
81
+ - type: mrr_at_3
82
+ value: 43.777
83
+ - type: mrr_at_5
84
+ value: 46.792
85
+ - type: ndcg_at_1
86
+ value: 32.646
87
+ - type: ndcg_at_10
88
+ value: 56.874
89
+ - type: ndcg_at_100
90
+ value: 60.307
91
+ - type: ndcg_at_1000
92
+ value: 60.465999999999994
93
+ - type: ndcg_at_3
94
+ value: 47.339999999999996
95
+ - type: ndcg_at_5
96
+ value: 52.685
97
+ - type: precision_at_1
98
+ value: 32.646
99
+ - type: precision_at_10
100
+ value: 8.378
101
+ - type: precision_at_100
102
+ value: 0.984
103
+ - type: precision_at_1000
104
+ value: 0.1
105
+ - type: precision_at_3
106
+ value: 19.393
107
+ - type: precision_at_5
108
+ value: 14.210999999999999
109
+ - type: recall_at_1
110
+ value: 32.646
111
+ - type: recall_at_10
112
+ value: 83.784
113
+ - type: recall_at_100
114
+ value: 98.43499999999999
115
+ - type: recall_at_1000
116
+ value: 99.644
117
+ - type: recall_at_3
118
+ value: 58.179
119
+ - type: recall_at_5
120
+ value: 71.053
121
+ - task:
122
+ type: Clustering
123
+ dataset:
124
+ type: mteb/arxiv-clustering-p2p
125
+ name: MTEB ArxivClusteringP2P
126
+ config: default
127
+ split: test
128
+ revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
129
+ metrics:
130
+ - type: v_measure
131
+ value: 44.94353025039141
132
+ - task:
133
+ type: Clustering
134
+ dataset:
135
+ type: mteb/arxiv-clustering-s2s
136
+ name: MTEB ArxivClusteringS2S
137
+ config: default
138
+ split: test
139
+ revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
140
+ metrics:
141
+ - type: v_measure
142
+ value: 35.870836103029156
143
+ - task:
144
+ type: Reranking
145
+ dataset:
146
+ type: mteb/askubuntudupquestions-reranking
147
+ name: MTEB AskUbuntuDupQuestions
148
+ config: default
149
+ split: test
150
+ revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
151
+ metrics:
152
+ - type: map
153
+ value: 61.149290266979236
154
+ - type: mrr
155
+ value: 73.8448093919008
156
+ - task:
157
+ type: STS
158
+ dataset:
159
+ type: mteb/biosses-sts
160
+ name: MTEB BIOSSES
161
+ config: default
162
+ split: test
163
+ revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
164
+ metrics:
165
+ - type: cos_sim_pearson
166
+ value: 87.055571064151
167
+ - type: cos_sim_spearman
168
+ value: 86.2652186235749
169
+ - type: euclidean_pearson
170
+ value: 85.82039272282503
171
+ - type: euclidean_spearman
172
+ value: 86.2652186235749
173
+ - type: manhattan_pearson
174
+ value: 85.95825392094812
175
+ - type: manhattan_spearman
176
+ value: 86.6742640885316
177
+ - task:
178
+ type: Classification
179
+ dataset:
180
+ type: mteb/banking77
181
+ name: MTEB Banking77Classification
182
+ config: default
183
+ split: test
184
+ revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
185
+ metrics:
186
+ - type: accuracy
187
+ value: 79.11688311688312
188
+ - type: f1
189
+ value: 78.28328901613885
190
+ - task:
191
+ type: Clustering
192
+ dataset:
193
+ type: jinaai/big-patent-clustering
194
+ name: MTEB BigPatentClustering
195
+ config: default
196
+ split: test
197
+ revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
198
+ metrics:
199
+ - type: v_measure
200
+ value: 19.147523589859325
201
+ - task:
202
+ type: Clustering
203
+ dataset:
204
+ type: mteb/biorxiv-clustering-p2p
205
+ name: MTEB BiorxivClusteringP2P
206
+ config: default
207
+ split: test
208
+ revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
209
+ metrics:
210
+ - type: v_measure
211
+ value: 35.68369864124274
212
+ - task:
213
+ type: Clustering
214
+ dataset:
215
+ type: mteb/biorxiv-clustering-s2s
216
+ name: MTEB BiorxivClusteringS2S
217
+ config: default
218
+ split: test
219
+ revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
220
+ metrics:
221
+ - type: v_measure
222
+ value: 30.474958792950872
223
+ - task:
224
+ type: Retrieval
225
+ dataset:
226
+ type: mteb/cqadupstack-android
227
+ name: MTEB CQADupstackAndroidRetrieval
228
+ config: default
229
+ split: test
230
+ revision: f46a197baaae43b4f621051089b82a364682dfeb
231
+ metrics:
232
+ - type: map_at_1
233
+ value: 33.183
234
+ - type: map_at_10
235
+ value: 43.989
236
+ - type: map_at_100
237
+ value: 45.389
238
+ - type: map_at_1000
239
+ value: 45.517
240
+ - type: map_at_3
241
+ value: 40.275
242
+ - type: map_at_5
243
+ value: 42.306
244
+ - type: mrr_at_1
245
+ value: 40.486
246
+ - type: mrr_at_10
247
+ value: 49.62
248
+ - type: mrr_at_100
249
+ value: 50.351
250
+ - type: mrr_at_1000
251
+ value: 50.393
252
+ - type: mrr_at_3
253
+ value: 46.805
254
+ - type: mrr_at_5
255
+ value: 48.429
256
+ - type: ndcg_at_1
257
+ value: 40.486
258
+ - type: ndcg_at_10
259
+ value: 50.249
260
+ - type: ndcg_at_100
261
+ value: 55.206
262
+ - type: ndcg_at_1000
263
+ value: 57.145
264
+ - type: ndcg_at_3
265
+ value: 44.852
266
+ - type: ndcg_at_5
267
+ value: 47.355000000000004
268
+ - type: precision_at_1
269
+ value: 40.486
270
+ - type: precision_at_10
271
+ value: 9.571
272
+ - type: precision_at_100
273
+ value: 1.4949999999999999
274
+ - type: precision_at_1000
275
+ value: 0.196
276
+ - type: precision_at_3
277
+ value: 21.173000000000002
278
+ - type: precision_at_5
279
+ value: 15.622
280
+ - type: recall_at_1
281
+ value: 33.183
282
+ - type: recall_at_10
283
+ value: 62.134
284
+ - type: recall_at_100
285
+ value: 82.73
286
+ - type: recall_at_1000
287
+ value: 94.93599999999999
288
+ - type: recall_at_3
289
+ value: 46.497
290
+ - type: recall_at_5
291
+ value: 53.199
292
+ - task:
293
+ type: Retrieval
294
+ dataset:
295
+ type: mteb/cqadupstack-english
296
+ name: MTEB CQADupstackEnglishRetrieval
297
+ config: default
298
+ split: test
299
+ revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
300
+ metrics:
301
+ - type: map_at_1
302
+ value: 32.862
303
+ - type: map_at_10
304
+ value: 42.439
305
+ - type: map_at_100
306
+ value: 43.736999999999995
307
+ - type: map_at_1000
308
+ value: 43.864
309
+ - type: map_at_3
310
+ value: 39.67
311
+ - type: map_at_5
312
+ value: 41.202
313
+ - type: mrr_at_1
314
+ value: 40.892
315
+ - type: mrr_at_10
316
+ value: 48.61
317
+ - type: mrr_at_100
318
+ value: 49.29
319
+ - type: mrr_at_1000
320
+ value: 49.332
321
+ - type: mrr_at_3
322
+ value: 46.688
323
+ - type: mrr_at_5
324
+ value: 47.803000000000004
325
+ - type: ndcg_at_1
326
+ value: 40.892
327
+ - type: ndcg_at_10
328
+ value: 47.797
329
+ - type: ndcg_at_100
330
+ value: 52.17699999999999
331
+ - type: ndcg_at_1000
332
+ value: 54.127
333
+ - type: ndcg_at_3
334
+ value: 44.189
335
+ - type: ndcg_at_5
336
+ value: 45.821
337
+ - type: precision_at_1
338
+ value: 40.892
339
+ - type: precision_at_10
340
+ value: 8.841000000000001
341
+ - type: precision_at_100
342
+ value: 1.419
343
+ - type: precision_at_1000
344
+ value: 0.188
345
+ - type: precision_at_3
346
+ value: 21.104
347
+ - type: precision_at_5
348
+ value: 14.777000000000001
349
+ - type: recall_at_1
350
+ value: 32.862
351
+ - type: recall_at_10
352
+ value: 56.352999999999994
353
+ - type: recall_at_100
354
+ value: 74.795
355
+ - type: recall_at_1000
356
+ value: 86.957
357
+ - type: recall_at_3
358
+ value: 45.269999999999996
359
+ - type: recall_at_5
360
+ value: 50.053000000000004
361
+ - task:
362
+ type: Retrieval
363
+ dataset:
364
+ type: mteb/cqadupstack-gaming
365
+ name: MTEB CQADupstackGamingRetrieval
366
+ config: default
367
+ split: test
368
+ revision: 4885aa143210c98657558c04aaf3dc47cfb54340
369
+ metrics:
370
+ - type: map_at_1
371
+ value: 42.998999999999995
372
+ - type: map_at_10
373
+ value: 54.745
374
+ - type: map_at_100
375
+ value: 55.650999999999996
376
+ - type: map_at_1000
377
+ value: 55.703
378
+ - type: map_at_3
379
+ value: 51.67
380
+ - type: map_at_5
381
+ value: 53.503
382
+ - type: mrr_at_1
383
+ value: 49.028
384
+ - type: mrr_at_10
385
+ value: 58.172000000000004
386
+ - type: mrr_at_100
387
+ value: 58.744
388
+ - type: mrr_at_1000
389
+ value: 58.769000000000005
390
+ - type: mrr_at_3
391
+ value: 55.977
392
+ - type: mrr_at_5
393
+ value: 57.38799999999999
394
+ - type: ndcg_at_1
395
+ value: 49.028
396
+ - type: ndcg_at_10
397
+ value: 60.161
398
+ - type: ndcg_at_100
399
+ value: 63.806
400
+ - type: ndcg_at_1000
401
+ value: 64.821
402
+ - type: ndcg_at_3
403
+ value: 55.199
404
+ - type: ndcg_at_5
405
+ value: 57.830999999999996
406
+ - type: precision_at_1
407
+ value: 49.028
408
+ - type: precision_at_10
409
+ value: 9.455
410
+ - type: precision_at_100
411
+ value: 1.216
412
+ - type: precision_at_1000
413
+ value: 0.135
414
+ - type: precision_at_3
415
+ value: 24.242
416
+ - type: precision_at_5
417
+ value: 16.614
418
+ - type: recall_at_1
419
+ value: 42.998999999999995
420
+ - type: recall_at_10
421
+ value: 72.542
422
+ - type: recall_at_100
423
+ value: 88.605
424
+ - type: recall_at_1000
425
+ value: 95.676
426
+ - type: recall_at_3
427
+ value: 59.480999999999995
428
+ - type: recall_at_5
429
+ value: 65.886
430
+ - task:
431
+ type: Retrieval
432
+ dataset:
433
+ type: mteb/cqadupstack-gis
434
+ name: MTEB CQADupstackGisRetrieval
435
+ config: default
436
+ split: test
437
+ revision: 5003b3064772da1887988e05400cf3806fe491f2
438
+ metrics:
439
+ - type: map_at_1
440
+ value: 27.907
441
+ - type: map_at_10
442
+ value: 35.975
443
+ - type: map_at_100
444
+ value: 36.985
445
+ - type: map_at_1000
446
+ value: 37.063
447
+ - type: map_at_3
448
+ value: 33.467999999999996
449
+ - type: map_at_5
450
+ value: 34.749
451
+ - type: mrr_at_1
452
+ value: 30.056
453
+ - type: mrr_at_10
454
+ value: 38.047
455
+ - type: mrr_at_100
456
+ value: 38.932
457
+ - type: mrr_at_1000
458
+ value: 38.991
459
+ - type: mrr_at_3
460
+ value: 35.705999999999996
461
+ - type: mrr_at_5
462
+ value: 36.966
463
+ - type: ndcg_at_1
464
+ value: 30.056
465
+ - type: ndcg_at_10
466
+ value: 40.631
467
+ - type: ndcg_at_100
468
+ value: 45.564
469
+ - type: ndcg_at_1000
470
+ value: 47.685
471
+ - type: ndcg_at_3
472
+ value: 35.748000000000005
473
+ - type: ndcg_at_5
474
+ value: 37.921
475
+ - type: precision_at_1
476
+ value: 30.056
477
+ - type: precision_at_10
478
+ value: 6.079
479
+ - type: precision_at_100
480
+ value: 0.898
481
+ - type: precision_at_1000
482
+ value: 0.11199999999999999
483
+ - type: precision_at_3
484
+ value: 14.727
485
+ - type: precision_at_5
486
+ value: 10.056
487
+ - type: recall_at_1
488
+ value: 27.907
489
+ - type: recall_at_10
490
+ value: 52.981
491
+ - type: recall_at_100
492
+ value: 75.53999999999999
493
+ - type: recall_at_1000
494
+ value: 91.759
495
+ - type: recall_at_3
496
+ value: 39.878
497
+ - type: recall_at_5
498
+ value: 45.077
499
+ - task:
500
+ type: Retrieval
501
+ dataset:
502
+ type: mteb/cqadupstack-mathematica
503
+ name: MTEB CQADupstackMathematicaRetrieval
504
+ config: default
505
+ split: test
506
+ revision: 90fceea13679c63fe563ded68f3b6f06e50061de
507
+ metrics:
508
+ - type: map_at_1
509
+ value: 16.764000000000003
510
+ - type: map_at_10
511
+ value: 24.294
512
+ - type: map_at_100
513
+ value: 25.507999999999996
514
+ - type: map_at_1000
515
+ value: 25.64
516
+ - type: map_at_3
517
+ value: 21.807000000000002
518
+ - type: map_at_5
519
+ value: 23.21
520
+ - type: mrr_at_1
521
+ value: 20.771
522
+ - type: mrr_at_10
523
+ value: 28.677000000000003
524
+ - type: mrr_at_100
525
+ value: 29.742
526
+ - type: mrr_at_1000
527
+ value: 29.816
528
+ - type: mrr_at_3
529
+ value: 26.327
530
+ - type: mrr_at_5
531
+ value: 27.639000000000003
532
+ - type: ndcg_at_1
533
+ value: 20.771
534
+ - type: ndcg_at_10
535
+ value: 29.21
536
+ - type: ndcg_at_100
537
+ value: 34.788000000000004
538
+ - type: ndcg_at_1000
539
+ value: 37.813
540
+ - type: ndcg_at_3
541
+ value: 24.632
542
+ - type: ndcg_at_5
543
+ value: 26.801000000000002
544
+ - type: precision_at_1
545
+ value: 20.771
546
+ - type: precision_at_10
547
+ value: 5.373
548
+ - type: precision_at_100
549
+ value: 0.923
550
+ - type: precision_at_1000
551
+ value: 0.133
552
+ - type: precision_at_3
553
+ value: 12.065
554
+ - type: precision_at_5
555
+ value: 8.706
556
+ - type: recall_at_1
557
+ value: 16.764000000000003
558
+ - type: recall_at_10
559
+ value: 40.072
560
+ - type: recall_at_100
561
+ value: 63.856
562
+ - type: recall_at_1000
563
+ value: 85.141
564
+ - type: recall_at_3
565
+ value: 27.308
566
+ - type: recall_at_5
567
+ value: 32.876
568
+ - task:
569
+ type: Retrieval
570
+ dataset:
571
+ type: mteb/cqadupstack-physics
572
+ name: MTEB CQADupstackPhysicsRetrieval
573
+ config: default
574
+ split: test
575
+ revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
576
+ metrics:
577
+ - type: map_at_1
578
+ value: 31.194
579
+ - type: map_at_10
580
+ value: 40.731
581
+ - type: map_at_100
582
+ value: 42.073
583
+ - type: map_at_1000
584
+ value: 42.178
585
+ - type: map_at_3
586
+ value: 37.726
587
+ - type: map_at_5
588
+ value: 39.474
589
+ - type: mrr_at_1
590
+ value: 37.729
591
+ - type: mrr_at_10
592
+ value: 46.494
593
+ - type: mrr_at_100
594
+ value: 47.368
595
+ - type: mrr_at_1000
596
+ value: 47.407
597
+ - type: mrr_at_3
598
+ value: 44.224999999999994
599
+ - type: mrr_at_5
600
+ value: 45.582
601
+ - type: ndcg_at_1
602
+ value: 37.729
603
+ - type: ndcg_at_10
604
+ value: 46.312999999999995
605
+ - type: ndcg_at_100
606
+ value: 51.915
607
+ - type: ndcg_at_1000
608
+ value: 53.788000000000004
609
+ - type: ndcg_at_3
610
+ value: 41.695
611
+ - type: ndcg_at_5
612
+ value: 43.956
613
+ - type: precision_at_1
614
+ value: 37.729
615
+ - type: precision_at_10
616
+ value: 8.181
617
+ - type: precision_at_100
618
+ value: 1.275
619
+ - type: precision_at_1000
620
+ value: 0.16199999999999998
621
+ - type: precision_at_3
622
+ value: 19.41
623
+ - type: precision_at_5
624
+ value: 13.648
625
+ - type: recall_at_1
626
+ value: 31.194
627
+ - type: recall_at_10
628
+ value: 57.118
629
+ - type: recall_at_100
630
+ value: 80.759
631
+ - type: recall_at_1000
632
+ value: 92.779
633
+ - type: recall_at_3
634
+ value: 44.083
635
+ - type: recall_at_5
636
+ value: 50.044999999999995
637
+ - task:
638
+ type: Retrieval
639
+ dataset:
640
+ type: mteb/cqadupstack-programmers
641
+ name: MTEB CQADupstackProgrammersRetrieval
642
+ config: default
643
+ split: test
644
+ revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
645
+ metrics:
646
+ - type: map_at_1
647
+ value: 28.047
648
+ - type: map_at_10
649
+ value: 37.79
650
+ - type: map_at_100
651
+ value: 39.145
652
+ - type: map_at_1000
653
+ value: 39.254
654
+ - type: map_at_3
655
+ value: 34.857
656
+ - type: map_at_5
657
+ value: 36.545
658
+ - type: mrr_at_1
659
+ value: 35.388
660
+ - type: mrr_at_10
661
+ value: 43.475
662
+ - type: mrr_at_100
663
+ value: 44.440000000000005
664
+ - type: mrr_at_1000
665
+ value: 44.494
666
+ - type: mrr_at_3
667
+ value: 41.286
668
+ - type: mrr_at_5
669
+ value: 42.673
670
+ - type: ndcg_at_1
671
+ value: 35.388
672
+ - type: ndcg_at_10
673
+ value: 43.169000000000004
674
+ - type: ndcg_at_100
675
+ value: 48.785000000000004
676
+ - type: ndcg_at_1000
677
+ value: 51.029
678
+ - type: ndcg_at_3
679
+ value: 38.801
680
+ - type: ndcg_at_5
681
+ value: 40.9
682
+ - type: precision_at_1
683
+ value: 35.388
684
+ - type: precision_at_10
685
+ value: 7.7509999999999994
686
+ - type: precision_at_100
687
+ value: 1.212
688
+ - type: precision_at_1000
689
+ value: 0.157
690
+ - type: precision_at_3
691
+ value: 18.455
692
+ - type: precision_at_5
693
+ value: 13.014000000000001
694
+ - type: recall_at_1
695
+ value: 28.047
696
+ - type: recall_at_10
697
+ value: 53.53099999999999
698
+ - type: recall_at_100
699
+ value: 77.285
700
+ - type: recall_at_1000
701
+ value: 92.575
702
+ - type: recall_at_3
703
+ value: 40.949000000000005
704
+ - type: recall_at_5
705
+ value: 46.742
706
+ - task:
707
+ type: Retrieval
708
+ dataset:
709
+ type: mteb/cqadupstack
710
+ name: MTEB CQADupstackRetrieval
711
+ config: default
712
+ split: test
713
+ revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
714
+ metrics:
715
+ - type: map_at_1
716
+ value: 28.131999999999994
717
+ - type: map_at_10
718
+ value: 36.93333333333334
719
+ - type: map_at_100
720
+ value: 38.117250000000006
721
+ - type: map_at_1000
722
+ value: 38.23275
723
+ - type: map_at_3
724
+ value: 34.19708333333333
725
+ - type: map_at_5
726
+ value: 35.725166666666674
727
+ - type: mrr_at_1
728
+ value: 33.16116666666667
729
+ - type: mrr_at_10
730
+ value: 41.057833333333335
731
+ - type: mrr_at_100
732
+ value: 41.90033333333333
733
+ - type: mrr_at_1000
734
+ value: 41.95625
735
+ - type: mrr_at_3
736
+ value: 38.757333333333335
737
+ - type: mrr_at_5
738
+ value: 40.097333333333324
739
+ - type: ndcg_at_1
740
+ value: 33.16116666666667
741
+ - type: ndcg_at_10
742
+ value: 42.01983333333333
743
+ - type: ndcg_at_100
744
+ value: 46.99916666666667
745
+ - type: ndcg_at_1000
746
+ value: 49.21783333333334
747
+ - type: ndcg_at_3
748
+ value: 37.479916666666654
749
+ - type: ndcg_at_5
750
+ value: 39.6355
751
+ - type: precision_at_1
752
+ value: 33.16116666666667
753
+ - type: precision_at_10
754
+ value: 7.230249999999999
755
+ - type: precision_at_100
756
+ value: 1.1411666666666667
757
+ - type: precision_at_1000
758
+ value: 0.1520833333333333
759
+ - type: precision_at_3
760
+ value: 17.028166666666667
761
+ - type: precision_at_5
762
+ value: 12.046999999999999
763
+ - type: recall_at_1
764
+ value: 28.131999999999994
765
+ - type: recall_at_10
766
+ value: 52.825500000000005
767
+ - type: recall_at_100
768
+ value: 74.59608333333333
769
+ - type: recall_at_1000
770
+ value: 89.87916666666668
771
+ - type: recall_at_3
772
+ value: 40.13625
773
+ - type: recall_at_5
774
+ value: 45.699999999999996
775
+ - task:
776
+ type: Retrieval
777
+ dataset:
778
+ type: mteb/cqadupstack-stats
779
+ name: MTEB CQADupstackStatsRetrieval
780
+ config: default
781
+ split: test
782
+ revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
783
+ metrics:
784
+ - type: map_at_1
785
+ value: 24.773999999999997
786
+ - type: map_at_10
787
+ value: 31.997999999999998
788
+ - type: map_at_100
789
+ value: 32.857
790
+ - type: map_at_1000
791
+ value: 32.957
792
+ - type: map_at_3
793
+ value: 30.041
794
+ - type: map_at_5
795
+ value: 31.119000000000003
796
+ - type: mrr_at_1
797
+ value: 27.607
798
+ - type: mrr_at_10
799
+ value: 34.538000000000004
800
+ - type: mrr_at_100
801
+ value: 35.308
802
+ - type: mrr_at_1000
803
+ value: 35.375
804
+ - type: mrr_at_3
805
+ value: 32.643
806
+ - type: mrr_at_5
807
+ value: 33.755
808
+ - type: ndcg_at_1
809
+ value: 27.607
810
+ - type: ndcg_at_10
811
+ value: 36.035000000000004
812
+ - type: ndcg_at_100
813
+ value: 40.351
814
+ - type: ndcg_at_1000
815
+ value: 42.684
816
+ - type: ndcg_at_3
817
+ value: 32.414
818
+ - type: ndcg_at_5
819
+ value: 34.11
820
+ - type: precision_at_1
821
+ value: 27.607
822
+ - type: precision_at_10
823
+ value: 5.6129999999999995
824
+ - type: precision_at_100
825
+ value: 0.8370000000000001
826
+ - type: precision_at_1000
827
+ value: 0.11199999999999999
828
+ - type: precision_at_3
829
+ value: 13.957
830
+ - type: precision_at_5
831
+ value: 9.571
832
+ - type: recall_at_1
833
+ value: 24.773999999999997
834
+ - type: recall_at_10
835
+ value: 45.717
836
+ - type: recall_at_100
837
+ value: 65.499
838
+ - type: recall_at_1000
839
+ value: 82.311
840
+ - type: recall_at_3
841
+ value: 35.716
842
+ - type: recall_at_5
843
+ value: 40.007999999999996
844
+ - task:
845
+ type: Retrieval
846
+ dataset:
847
+ type: mteb/cqadupstack-tex
848
+ name: MTEB CQADupstackTexRetrieval
849
+ config: default
850
+ split: test
851
+ revision: 46989137a86843e03a6195de44b09deda022eec7
852
+ metrics:
853
+ - type: map_at_1
854
+ value: 19.227
855
+ - type: map_at_10
856
+ value: 26.649
857
+ - type: map_at_100
858
+ value: 27.711999999999996
859
+ - type: map_at_1000
860
+ value: 27.837
861
+ - type: map_at_3
862
+ value: 24.454
863
+ - type: map_at_5
864
+ value: 25.772000000000002
865
+ - type: mrr_at_1
866
+ value: 23.433999999999997
867
+ - type: mrr_at_10
868
+ value: 30.564999999999998
869
+ - type: mrr_at_100
870
+ value: 31.44
871
+ - type: mrr_at_1000
872
+ value: 31.513999999999996
873
+ - type: mrr_at_3
874
+ value: 28.435
875
+ - type: mrr_at_5
876
+ value: 29.744999999999997
877
+ - type: ndcg_at_1
878
+ value: 23.433999999999997
879
+ - type: ndcg_at_10
880
+ value: 31.104
881
+ - type: ndcg_at_100
882
+ value: 36.172
883
+ - type: ndcg_at_1000
884
+ value: 39.006
885
+ - type: ndcg_at_3
886
+ value: 27.248
887
+ - type: ndcg_at_5
888
+ value: 29.249000000000002
889
+ - type: precision_at_1
890
+ value: 23.433999999999997
891
+ - type: precision_at_10
892
+ value: 5.496
893
+ - type: precision_at_100
894
+ value: 0.9490000000000001
895
+ - type: precision_at_1000
896
+ value: 0.13699999999999998
897
+ - type: precision_at_3
898
+ value: 12.709000000000001
899
+ - type: precision_at_5
900
+ value: 9.209
901
+ - type: recall_at_1
902
+ value: 19.227
903
+ - type: recall_at_10
904
+ value: 40.492
905
+ - type: recall_at_100
906
+ value: 63.304
907
+ - type: recall_at_1000
908
+ value: 83.45
909
+ - type: recall_at_3
910
+ value: 29.713
911
+ - type: recall_at_5
912
+ value: 34.82
913
+ - task:
914
+ type: Retrieval
915
+ dataset:
916
+ type: mteb/cqadupstack-unix
917
+ name: MTEB CQADupstackUnixRetrieval
918
+ config: default
919
+ split: test
920
+ revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
921
+ metrics:
922
+ - type: map_at_1
923
+ value: 29.199
924
+ - type: map_at_10
925
+ value: 37.617
926
+ - type: map_at_100
927
+ value: 38.746
928
+ - type: map_at_1000
929
+ value: 38.851
930
+ - type: map_at_3
931
+ value: 34.882000000000005
932
+ - type: map_at_5
933
+ value: 36.571999999999996
934
+ - type: mrr_at_1
935
+ value: 33.489000000000004
936
+ - type: mrr_at_10
937
+ value: 41.089999999999996
938
+ - type: mrr_at_100
939
+ value: 41.965
940
+ - type: mrr_at_1000
941
+ value: 42.028
942
+ - type: mrr_at_3
943
+ value: 38.666
944
+ - type: mrr_at_5
945
+ value: 40.159
946
+ - type: ndcg_at_1
947
+ value: 33.489000000000004
948
+ - type: ndcg_at_10
949
+ value: 42.487
950
+ - type: ndcg_at_100
951
+ value: 47.552
952
+ - type: ndcg_at_1000
953
+ value: 49.774
954
+ - type: ndcg_at_3
955
+ value: 37.623
956
+ - type: ndcg_at_5
957
+ value: 40.184999999999995
958
+ - type: precision_at_1
959
+ value: 33.489000000000004
960
+ - type: precision_at_10
961
+ value: 6.94
962
+ - type: precision_at_100
963
+ value: 1.0699999999999998
964
+ - type: precision_at_1000
965
+ value: 0.136
966
+ - type: precision_at_3
967
+ value: 16.667
968
+ - type: precision_at_5
969
+ value: 11.922
970
+ - type: recall_at_1
971
+ value: 29.199
972
+ - type: recall_at_10
973
+ value: 53.689
974
+ - type: recall_at_100
975
+ value: 75.374
976
+ - type: recall_at_1000
977
+ value: 90.64999999999999
978
+ - type: recall_at_3
979
+ value: 40.577999999999996
980
+ - type: recall_at_5
981
+ value: 46.909
982
+ - task:
983
+ type: Retrieval
984
+ dataset:
985
+ type: mteb/cqadupstack-webmasters
986
+ name: MTEB CQADupstackWebmastersRetrieval
987
+ config: default
988
+ split: test
989
+ revision: 160c094312a0e1facb97e55eeddb698c0abe3571
990
+ metrics:
991
+ - type: map_at_1
992
+ value: 27.206999999999997
993
+ - type: map_at_10
994
+ value: 36.146
995
+ - type: map_at_100
996
+ value: 37.759
997
+ - type: map_at_1000
998
+ value: 37.979
999
+ - type: map_at_3
1000
+ value: 32.967999999999996
1001
+ - type: map_at_5
1002
+ value: 34.809
1003
+ - type: mrr_at_1
1004
+ value: 32.806000000000004
1005
+ - type: mrr_at_10
1006
+ value: 40.449
1007
+ - type: mrr_at_100
1008
+ value: 41.404999999999994
1009
+ - type: mrr_at_1000
1010
+ value: 41.457
1011
+ - type: mrr_at_3
1012
+ value: 37.614999999999995
1013
+ - type: mrr_at_5
1014
+ value: 39.324999999999996
1015
+ - type: ndcg_at_1
1016
+ value: 32.806000000000004
1017
+ - type: ndcg_at_10
1018
+ value: 41.911
1019
+ - type: ndcg_at_100
1020
+ value: 47.576
1021
+ - type: ndcg_at_1000
1022
+ value: 50.072
1023
+ - type: ndcg_at_3
1024
+ value: 36.849
1025
+ - type: ndcg_at_5
1026
+ value: 39.475
1027
+ - type: precision_at_1
1028
+ value: 32.806000000000004
1029
+ - type: precision_at_10
1030
+ value: 8.103
1031
+ - type: precision_at_100
1032
+ value: 1.557
1033
+ - type: precision_at_1000
1034
+ value: 0.242
1035
+ - type: precision_at_3
1036
+ value: 17.26
1037
+ - type: precision_at_5
1038
+ value: 12.885
1039
+ - type: recall_at_1
1040
+ value: 27.206999999999997
1041
+ - type: recall_at_10
1042
+ value: 52.56999999999999
1043
+ - type: recall_at_100
1044
+ value: 78.302
1045
+ - type: recall_at_1000
1046
+ value: 94.121
1047
+ - type: recall_at_3
1048
+ value: 38.317
1049
+ - type: recall_at_5
1050
+ value: 45.410000000000004
1051
+ - task:
1052
+ type: Retrieval
1053
+ dataset:
1054
+ type: mteb/cqadupstack-wordpress
1055
+ name: MTEB CQADupstackWordpressRetrieval
1056
+ config: default
1057
+ split: test
1058
+ revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
1059
+ metrics:
1060
+ - type: map_at_1
1061
+ value: 24.221
1062
+ - type: map_at_10
1063
+ value: 30.826999999999998
1064
+ - type: map_at_100
1065
+ value: 31.845000000000002
1066
+ - type: map_at_1000
1067
+ value: 31.95
1068
+ - type: map_at_3
1069
+ value: 28.547
1070
+ - type: map_at_5
1071
+ value: 29.441
1072
+ - type: mrr_at_1
1073
+ value: 26.247999999999998
1074
+ - type: mrr_at_10
1075
+ value: 32.957
1076
+ - type: mrr_at_100
1077
+ value: 33.819
1078
+ - type: mrr_at_1000
1079
+ value: 33.899
1080
+ - type: mrr_at_3
1081
+ value: 30.714999999999996
1082
+ - type: mrr_at_5
1083
+ value: 31.704
1084
+ - type: ndcg_at_1
1085
+ value: 26.247999999999998
1086
+ - type: ndcg_at_10
1087
+ value: 35.171
1088
+ - type: ndcg_at_100
1089
+ value: 40.098
1090
+ - type: ndcg_at_1000
1091
+ value: 42.67
1092
+ - type: ndcg_at_3
1093
+ value: 30.508999999999997
1094
+ - type: ndcg_at_5
1095
+ value: 32.022
1096
+ - type: precision_at_1
1097
+ value: 26.247999999999998
1098
+ - type: precision_at_10
1099
+ value: 5.36
1100
+ - type: precision_at_100
1101
+ value: 0.843
1102
+ - type: precision_at_1000
1103
+ value: 0.11499999999999999
1104
+ - type: precision_at_3
1105
+ value: 12.568999999999999
1106
+ - type: precision_at_5
1107
+ value: 8.540000000000001
1108
+ - type: recall_at_1
1109
+ value: 24.221
1110
+ - type: recall_at_10
1111
+ value: 46.707
1112
+ - type: recall_at_100
1113
+ value: 69.104
1114
+ - type: recall_at_1000
1115
+ value: 88.19500000000001
1116
+ - type: recall_at_3
1117
+ value: 33.845
1118
+ - type: recall_at_5
1119
+ value: 37.375
1120
+ - task:
1121
+ type: Retrieval
1122
+ dataset:
1123
+ type: mteb/climate-fever
1124
+ name: MTEB ClimateFEVER
1125
+ config: default
1126
+ split: test
1127
+ revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
1128
+ metrics:
1129
+ - type: map_at_1
1130
+ value: 13.624
1131
+ - type: map_at_10
1132
+ value: 22.557
1133
+ - type: map_at_100
1134
+ value: 24.367
1135
+ - type: map_at_1000
1136
+ value: 24.54
1137
+ - type: map_at_3
1138
+ value: 18.988
1139
+ - type: map_at_5
1140
+ value: 20.785999999999998
1141
+ - type: mrr_at_1
1142
+ value: 30.619000000000003
1143
+ - type: mrr_at_10
1144
+ value: 42.019
1145
+ - type: mrr_at_100
1146
+ value: 42.818
1147
+ - type: mrr_at_1000
1148
+ value: 42.856
1149
+ - type: mrr_at_3
1150
+ value: 38.578
1151
+ - type: mrr_at_5
1152
+ value: 40.669
1153
+ - type: ndcg_at_1
1154
+ value: 30.619000000000003
1155
+ - type: ndcg_at_10
1156
+ value: 31.252999999999997
1157
+ - type: ndcg_at_100
1158
+ value: 38.238
1159
+ - type: ndcg_at_1000
1160
+ value: 41.368
1161
+ - type: ndcg_at_3
1162
+ value: 25.843
1163
+ - type: ndcg_at_5
1164
+ value: 27.638
1165
+ - type: precision_at_1
1166
+ value: 30.619000000000003
1167
+ - type: precision_at_10
1168
+ value: 9.687
1169
+ - type: precision_at_100
1170
+ value: 1.718
1171
+ - type: precision_at_1000
1172
+ value: 0.22999999999999998
1173
+ - type: precision_at_3
1174
+ value: 18.849
1175
+ - type: precision_at_5
1176
+ value: 14.463000000000001
1177
+ - type: recall_at_1
1178
+ value: 13.624
1179
+ - type: recall_at_10
1180
+ value: 36.693999999999996
1181
+ - type: recall_at_100
1182
+ value: 60.9
1183
+ - type: recall_at_1000
1184
+ value: 78.46
1185
+ - type: recall_at_3
1186
+ value: 23.354
1187
+ - type: recall_at_5
1188
+ value: 28.756999999999998
1189
+ - task:
1190
+ type: Retrieval
1191
+ dataset:
1192
+ type: mteb/dbpedia
1193
+ name: MTEB DBPedia
1194
+ config: default
1195
+ split: test
1196
+ revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
1197
+ metrics:
1198
+ - type: map_at_1
1199
+ value: 9.077
1200
+ - type: map_at_10
1201
+ value: 19.813
1202
+ - type: map_at_100
1203
+ value: 27.822999999999997
1204
+ - type: map_at_1000
1205
+ value: 29.485
1206
+ - type: map_at_3
1207
+ value: 14.255999999999998
1208
+ - type: map_at_5
1209
+ value: 16.836000000000002
1210
+ - type: mrr_at_1
1211
+ value: 69.25
1212
+ - type: mrr_at_10
1213
+ value: 77.059
1214
+ - type: mrr_at_100
1215
+ value: 77.41
1216
+ - type: mrr_at_1000
1217
+ value: 77.416
1218
+ - type: mrr_at_3
1219
+ value: 75.625
1220
+ - type: mrr_at_5
1221
+ value: 76.512
1222
+ - type: ndcg_at_1
1223
+ value: 55.75
1224
+ - type: ndcg_at_10
1225
+ value: 41.587
1226
+ - type: ndcg_at_100
1227
+ value: 46.048
1228
+ - type: ndcg_at_1000
1229
+ value: 53.172
1230
+ - type: ndcg_at_3
1231
+ value: 46.203
1232
+ - type: ndcg_at_5
1233
+ value: 43.696
1234
+ - type: precision_at_1
1235
+ value: 69.25
1236
+ - type: precision_at_10
1237
+ value: 32.95
1238
+ - type: precision_at_100
1239
+ value: 10.555
1240
+ - type: precision_at_1000
1241
+ value: 2.136
1242
+ - type: precision_at_3
1243
+ value: 49.667
1244
+ - type: precision_at_5
1245
+ value: 42.5
1246
+ - type: recall_at_1
1247
+ value: 9.077
1248
+ - type: recall_at_10
1249
+ value: 25.249
1250
+ - type: recall_at_100
1251
+ value: 51.964
1252
+ - type: recall_at_1000
1253
+ value: 74.51
1254
+ - type: recall_at_3
1255
+ value: 15.584000000000001
1256
+ - type: recall_at_5
1257
+ value: 19.717000000000002
1258
+ - task:
1259
+ type: Classification
1260
+ dataset:
1261
+ type: mteb/emotion
1262
+ name: MTEB EmotionClassification
1263
+ config: default
1264
+ split: test
1265
+ revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
1266
+ metrics:
1267
+ - type: accuracy
1268
+ value: 45.769999999999996
1269
+ - type: f1
1270
+ value: 41.64144711933962
1271
+ - task:
1272
+ type: Retrieval
1273
+ dataset:
1274
+ type: mteb/fever
1275
+ name: MTEB FEVER
1276
+ config: default
1277
+ split: test
1278
+ revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
1279
+ metrics:
1280
+ - type: map_at_1
1281
+ value: 67.098
1282
+ - type: map_at_10
1283
+ value: 77.69800000000001
1284
+ - type: map_at_100
1285
+ value: 77.947
1286
+ - type: map_at_1000
1287
+ value: 77.961
1288
+ - type: map_at_3
1289
+ value: 76.278
1290
+ - type: map_at_5
1291
+ value: 77.217
1292
+ - type: mrr_at_1
1293
+ value: 72.532
1294
+ - type: mrr_at_10
1295
+ value: 82.41199999999999
1296
+ - type: mrr_at_100
1297
+ value: 82.527
1298
+ - type: mrr_at_1000
1299
+ value: 82.529
1300
+ - type: mrr_at_3
1301
+ value: 81.313
1302
+ - type: mrr_at_5
1303
+ value: 82.069
1304
+ - type: ndcg_at_1
1305
+ value: 72.532
1306
+ - type: ndcg_at_10
1307
+ value: 82.488
1308
+ - type: ndcg_at_100
1309
+ value: 83.382
1310
+ - type: ndcg_at_1000
1311
+ value: 83.622
1312
+ - type: ndcg_at_3
1313
+ value: 80.101
1314
+ - type: ndcg_at_5
1315
+ value: 81.52199999999999
1316
+ - type: precision_at_1
1317
+ value: 72.532
1318
+ - type: precision_at_10
1319
+ value: 10.203
1320
+ - type: precision_at_100
1321
+ value: 1.082
1322
+ - type: precision_at_1000
1323
+ value: 0.11199999999999999
1324
+ - type: precision_at_3
1325
+ value: 31.308000000000003
1326
+ - type: precision_at_5
1327
+ value: 19.652
1328
+ - type: recall_at_1
1329
+ value: 67.098
1330
+ - type: recall_at_10
1331
+ value: 92.511
1332
+ - type: recall_at_100
1333
+ value: 96.06099999999999
1334
+ - type: recall_at_1000
1335
+ value: 97.548
1336
+ - type: recall_at_3
1337
+ value: 86.105
1338
+ - type: recall_at_5
1339
+ value: 89.661
1340
+ - task:
1341
+ type: Retrieval
1342
+ dataset:
1343
+ type: mteb/fiqa
1344
+ name: MTEB FiQA2018
1345
+ config: default
1346
+ split: test
1347
+ revision: 27a168819829fe9bcd655c2df245fb19452e8e06
1348
+ metrics:
1349
+ - type: map_at_1
1350
+ value: 18.681
1351
+ - type: map_at_10
1352
+ value: 31.739
1353
+ - type: map_at_100
1354
+ value: 33.503
1355
+ - type: map_at_1000
1356
+ value: 33.69
1357
+ - type: map_at_3
1358
+ value: 27.604
1359
+ - type: map_at_5
1360
+ value: 29.993
1361
+ - type: mrr_at_1
1362
+ value: 37.5
1363
+ - type: mrr_at_10
1364
+ value: 46.933
1365
+ - type: mrr_at_100
1366
+ value: 47.771
1367
+ - type: mrr_at_1000
1368
+ value: 47.805
1369
+ - type: mrr_at_3
1370
+ value: 44.239
1371
+ - type: mrr_at_5
1372
+ value: 45.766
1373
+ - type: ndcg_at_1
1374
+ value: 37.5
1375
+ - type: ndcg_at_10
1376
+ value: 39.682
1377
+ - type: ndcg_at_100
1378
+ value: 46.127
1379
+ - type: ndcg_at_1000
1380
+ value: 48.994
1381
+ - type: ndcg_at_3
1382
+ value: 35.655
1383
+ - type: ndcg_at_5
1384
+ value: 37.036
1385
+ - type: precision_at_1
1386
+ value: 37.5
1387
+ - type: precision_at_10
1388
+ value: 11.08
1389
+ - type: precision_at_100
1390
+ value: 1.765
1391
+ - type: precision_at_1000
1392
+ value: 0.22999999999999998
1393
+ - type: precision_at_3
1394
+ value: 23.919999999999998
1395
+ - type: precision_at_5
1396
+ value: 17.809
1397
+ - type: recall_at_1
1398
+ value: 18.681
1399
+ - type: recall_at_10
1400
+ value: 47.548
1401
+ - type: recall_at_100
1402
+ value: 71.407
1403
+ - type: recall_at_1000
1404
+ value: 87.805
1405
+ - type: recall_at_3
1406
+ value: 32.979
1407
+ - type: recall_at_5
1408
+ value: 39.192
1409
+ - task:
1410
+ type: Retrieval
1411
+ dataset:
1412
+ type: mteb/hotpotqa
1413
+ name: MTEB HotpotQA
1414
+ config: default
1415
+ split: test
1416
+ revision: ab518f4d6fcca38d87c25209f94beba119d02014
1417
+ metrics:
1418
+ - type: map_at_1
1419
+ value: 38.257999999999996
1420
+ - type: map_at_10
1421
+ value: 57.605
1422
+ - type: map_at_100
1423
+ value: 58.50300000000001
1424
+ - type: map_at_1000
1425
+ value: 58.568
1426
+ - type: map_at_3
1427
+ value: 54.172
1428
+ - type: map_at_5
1429
+ value: 56.323
1430
+ - type: mrr_at_1
1431
+ value: 76.51599999999999
1432
+ - type: mrr_at_10
1433
+ value: 82.584
1434
+ - type: mrr_at_100
1435
+ value: 82.78
1436
+ - type: mrr_at_1000
1437
+ value: 82.787
1438
+ - type: mrr_at_3
1439
+ value: 81.501
1440
+ - type: mrr_at_5
1441
+ value: 82.185
1442
+ - type: ndcg_at_1
1443
+ value: 76.51599999999999
1444
+ - type: ndcg_at_10
1445
+ value: 66.593
1446
+ - type: ndcg_at_100
1447
+ value: 69.699
1448
+ - type: ndcg_at_1000
1449
+ value: 70.953
1450
+ - type: ndcg_at_3
1451
+ value: 61.673
1452
+ - type: ndcg_at_5
1453
+ value: 64.42
1454
+ - type: precision_at_1
1455
+ value: 76.51599999999999
1456
+ - type: precision_at_10
1457
+ value: 13.857
1458
+ - type: precision_at_100
1459
+ value: 1.628
1460
+ - type: precision_at_1000
1461
+ value: 0.179
1462
+ - type: precision_at_3
1463
+ value: 38.956
1464
+ - type: precision_at_5
1465
+ value: 25.541999999999998
1466
+ - type: recall_at_1
1467
+ value: 38.257999999999996
1468
+ - type: recall_at_10
1469
+ value: 69.284
1470
+ - type: recall_at_100
1471
+ value: 81.391
1472
+ - type: recall_at_1000
1473
+ value: 89.689
1474
+ - type: recall_at_3
1475
+ value: 58.433
1476
+ - type: recall_at_5
1477
+ value: 63.856
1478
+ - task:
1479
+ type: Classification
1480
+ dataset:
1481
+ type: mteb/imdb
1482
+ name: MTEB ImdbClassification
1483
+ config: default
1484
+ split: test
1485
+ revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
1486
+ metrics:
1487
+ - type: accuracy
1488
+ value: 69.48679999999999
1489
+ - type: ap
1490
+ value: 63.97638838971138
1491
+ - type: f1
1492
+ value: 69.22731638841675
1493
+ - task:
1494
+ type: Retrieval
1495
+ dataset:
1496
+ type: mteb/msmarco
1497
+ name: MTEB MSMARCO
1498
+ config: default
1499
+ split: dev
1500
+ revision: c5a29a104738b98a9e76336939199e264163d4a0
1501
+ metrics:
1502
+ - type: map_at_1
1503
+ value: 20.916999999999998
1504
+ - type: map_at_10
1505
+ value: 32.929
1506
+ - type: map_at_100
1507
+ value: 34.1
1508
+ - type: map_at_1000
1509
+ value: 34.152
1510
+ - type: map_at_3
1511
+ value: 29.065
1512
+ - type: map_at_5
1513
+ value: 31.287
1514
+ - type: mrr_at_1
1515
+ value: 21.562
1516
+ - type: mrr_at_10
1517
+ value: 33.533
1518
+ - type: mrr_at_100
1519
+ value: 34.644000000000005
1520
+ - type: mrr_at_1000
1521
+ value: 34.69
1522
+ - type: mrr_at_3
1523
+ value: 29.735
1524
+ - type: mrr_at_5
1525
+ value: 31.928
1526
+ - type: ndcg_at_1
1527
+ value: 21.562
1528
+ - type: ndcg_at_10
1529
+ value: 39.788000000000004
1530
+ - type: ndcg_at_100
1531
+ value: 45.434999999999995
1532
+ - type: ndcg_at_1000
1533
+ value: 46.75
1534
+ - type: ndcg_at_3
1535
+ value: 31.942999999999998
1536
+ - type: ndcg_at_5
1537
+ value: 35.888
1538
+ - type: precision_at_1
1539
+ value: 21.562
1540
+ - type: precision_at_10
1541
+ value: 6.348
1542
+ - type: precision_at_100
1543
+ value: 0.918
1544
+ - type: precision_at_1000
1545
+ value: 0.10300000000000001
1546
+ - type: precision_at_3
1547
+ value: 13.682
1548
+ - type: precision_at_5
1549
+ value: 10.189
1550
+ - type: recall_at_1
1551
+ value: 20.916999999999998
1552
+ - type: recall_at_10
1553
+ value: 60.926
1554
+ - type: recall_at_100
1555
+ value: 87.03800000000001
1556
+ - type: recall_at_1000
1557
+ value: 97.085
1558
+ - type: recall_at_3
1559
+ value: 39.637
1560
+ - type: recall_at_5
1561
+ value: 49.069
1562
+ - task:
1563
+ type: Classification
1564
+ dataset:
1565
+ type: mteb/mtop_domain
1566
+ name: MTEB MTOPDomainClassification (en)
1567
+ config: en
1568
+ split: test
1569
+ revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
1570
+ metrics:
1571
+ - type: accuracy
1572
+ value: 90.93935248518011
1573
+ - type: f1
1574
+ value: 90.56439321844506
1575
+ - task:
1576
+ type: Classification
1577
+ dataset:
1578
+ type: mteb/mtop_intent
1579
+ name: MTEB MTOPIntentClassification (en)
1580
+ config: en
1581
+ split: test
1582
+ revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1583
+ metrics:
1584
+ - type: accuracy
1585
+ value: 58.62517099863203
1586
+ - type: f1
1587
+ value: 40.69925681703197
1588
+ - task:
1589
+ type: Classification
1590
+ dataset:
1591
+ type: masakhane/masakhanews
1592
+ name: MTEB MasakhaNEWSClassification (eng)
1593
+ config: eng
1594
+ split: test
1595
+ revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
1596
+ metrics:
1597
+ - type: accuracy
1598
+ value: 76.29746835443039
1599
+ - type: f1
1600
+ value: 75.31702672039506
1601
+ - task:
1602
+ type: Clustering
1603
+ dataset:
1604
+ type: masakhane/masakhanews
1605
+ name: MTEB MasakhaNEWSClusteringP2P (eng)
1606
+ config: eng
1607
+ split: test
1608
+ revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
1609
+ metrics:
1610
+ - type: v_measure
1611
+ value: 43.05495067062023
1612
+ - task:
1613
+ type: Clustering
1614
+ dataset:
1615
+ type: masakhane/masakhanews
1616
+ name: MTEB MasakhaNEWSClusteringS2S (eng)
1617
+ config: eng
1618
+ split: test
1619
+ revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
1620
+ metrics:
1621
+ - type: v_measure
1622
+ value: 19.625272848173843
1623
+ - task:
1624
+ type: Classification
1625
+ dataset:
1626
+ type: mteb/amazon_massive_intent
1627
+ name: MTEB MassiveIntentClassification (en)
1628
+ config: en
1629
+ split: test
1630
+ revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
1631
+ metrics:
1632
+ - type: accuracy
1633
+ value: 64.76126429051781
1634
+ - type: f1
1635
+ value: 62.60284261265268
1636
+ - task:
1637
+ type: Classification
1638
+ dataset:
1639
+ type: mteb/amazon_massive_scenario
1640
+ name: MTEB MassiveScenarioClassification (en)
1641
+ config: en
1642
+ split: test
1643
+ revision: 7d571f92784cd94a019292a1f45445077d0ef634
1644
+ metrics:
1645
+ - type: accuracy
1646
+ value: 70.05043712172159
1647
+ - type: f1
1648
+ value: 69.08340521169049
1649
+ - task:
1650
+ type: Clustering
1651
+ dataset:
1652
+ type: mteb/medrxiv-clustering-p2p
1653
+ name: MTEB MedrxivClusteringP2P
1654
+ config: default
1655
+ split: test
1656
+ revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
1657
+ metrics:
1658
+ - type: v_measure
1659
+ value: 30.78969229005989
1660
+ - task:
1661
+ type: Clustering
1662
+ dataset:
1663
+ type: mteb/medrxiv-clustering-s2s
1664
+ name: MTEB MedrxivClusteringS2S
1665
+ config: default
1666
+ split: test
1667
+ revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
1668
+ metrics:
1669
+ - type: v_measure
1670
+ value: 27.954325178520335
1671
+ - task:
1672
+ type: Reranking
1673
+ dataset:
1674
+ type: mteb/mind_small
1675
+ name: MTEB MindSmallReranking
1676
+ config: default
1677
+ split: test
1678
+ revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
1679
+ metrics:
1680
+ - type: map
1681
+ value: 30.601827413968596
1682
+ - type: mrr
1683
+ value: 31.515372019474196
1684
+ - task:
1685
+ type: Retrieval
1686
+ dataset:
1687
+ type: mteb/nfcorpus
1688
+ name: MTEB NFCorpus
1689
+ config: default
1690
+ split: test
1691
+ revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
1692
+ metrics:
1693
+ - type: map_at_1
1694
+ value: 5.4559999999999995
1695
+ - type: map_at_10
1696
+ value: 12.039
1697
+ - type: map_at_100
1698
+ value: 14.804999999999998
1699
+ - type: map_at_1000
1700
+ value: 16.081
1701
+ - type: map_at_3
1702
+ value: 8.996
1703
+ - type: map_at_5
1704
+ value: 10.357
1705
+ - type: mrr_at_1
1706
+ value: 45.82
1707
+ - type: mrr_at_10
1708
+ value: 53.583999999999996
1709
+ - type: mrr_at_100
1710
+ value: 54.330999999999996
1711
+ - type: mrr_at_1000
1712
+ value: 54.366
1713
+ - type: mrr_at_3
1714
+ value: 52.166999999999994
1715
+ - type: mrr_at_5
1716
+ value: 52.971999999999994
1717
+ - type: ndcg_at_1
1718
+ value: 44.427
1719
+ - type: ndcg_at_10
1720
+ value: 32.536
1721
+ - type: ndcg_at_100
1722
+ value: 29.410999999999998
1723
+ - type: ndcg_at_1000
1724
+ value: 38.012
1725
+ - type: ndcg_at_3
1726
+ value: 38.674
1727
+ - type: ndcg_at_5
1728
+ value: 36.107
1729
+ - type: precision_at_1
1730
+ value: 45.82
1731
+ - type: precision_at_10
1732
+ value: 23.591
1733
+ - type: precision_at_100
1734
+ value: 7.35
1735
+ - type: precision_at_1000
1736
+ value: 1.9769999999999999
1737
+ - type: precision_at_3
1738
+ value: 36.016999999999996
1739
+ - type: precision_at_5
1740
+ value: 30.959999999999997
1741
+ - type: recall_at_1
1742
+ value: 5.4559999999999995
1743
+ - type: recall_at_10
1744
+ value: 15.387
1745
+ - type: recall_at_100
1746
+ value: 28.754999999999995
1747
+ - type: recall_at_1000
1748
+ value: 59.787
1749
+ - type: recall_at_3
1750
+ value: 10.137
1751
+ - type: recall_at_5
1752
+ value: 12.200999999999999
1753
+ - task:
1754
+ type: Retrieval
1755
+ dataset:
1756
+ type: mteb/nq
1757
+ name: MTEB NQ
1758
+ config: default
1759
+ split: test
1760
+ revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
1761
+ metrics:
1762
+ - type: map_at_1
1763
+ value: 32.609
1764
+ - type: map_at_10
1765
+ value: 48.522
1766
+ - type: map_at_100
1767
+ value: 49.468
1768
+ - type: map_at_1000
1769
+ value: 49.497
1770
+ - type: map_at_3
1771
+ value: 44.327
1772
+ - type: map_at_5
1773
+ value: 46.937
1774
+ - type: mrr_at_1
1775
+ value: 36.616
1776
+ - type: mrr_at_10
1777
+ value: 50.943000000000005
1778
+ - type: mrr_at_100
1779
+ value: 51.626000000000005
1780
+ - type: mrr_at_1000
1781
+ value: 51.647
1782
+ - type: mrr_at_3
1783
+ value: 47.532999999999994
1784
+ - type: mrr_at_5
1785
+ value: 49.714000000000006
1786
+ - type: ndcg_at_1
1787
+ value: 36.586999999999996
1788
+ - type: ndcg_at_10
1789
+ value: 56.19499999999999
1790
+ - type: ndcg_at_100
1791
+ value: 60.014
1792
+ - type: ndcg_at_1000
1793
+ value: 60.707
1794
+ - type: ndcg_at_3
1795
+ value: 48.486000000000004
1796
+ - type: ndcg_at_5
1797
+ value: 52.791999999999994
1798
+ - type: precision_at_1
1799
+ value: 36.586999999999996
1800
+ - type: precision_at_10
1801
+ value: 9.139999999999999
1802
+ - type: precision_at_100
1803
+ value: 1.129
1804
+ - type: precision_at_1000
1805
+ value: 0.11900000000000001
1806
+ - type: precision_at_3
1807
+ value: 22.171
1808
+ - type: precision_at_5
1809
+ value: 15.787999999999998
1810
+ - type: recall_at_1
1811
+ value: 32.609
1812
+ - type: recall_at_10
1813
+ value: 77.011
1814
+ - type: recall_at_100
1815
+ value: 93.202
1816
+ - type: recall_at_1000
1817
+ value: 98.344
1818
+ - type: recall_at_3
1819
+ value: 57.286
1820
+ - type: recall_at_5
1821
+ value: 67.181
1822
+ - task:
1823
+ type: Classification
1824
+ dataset:
1825
+ type: ag_news
1826
+ name: MTEB NewsClassification
1827
+ config: default
1828
+ split: test
1829
+ revision: eb185aade064a813bc0b7f42de02595523103ca4
1830
+ metrics:
1831
+ - type: accuracy
1832
+ value: 77.4421052631579
1833
+ - type: f1
1834
+ value: 77.23976860913628
1835
+ - task:
1836
+ type: PairClassification
1837
+ dataset:
1838
+ type: GEM/opusparcus
1839
+ name: MTEB OpusparcusPC (en)
1840
+ config: en
1841
+ split: test
1842
+ revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
1843
+ metrics:
1844
+ - type: cos_sim_accuracy
1845
+ value: 99.89816700610999
1846
+ - type: cos_sim_ap
1847
+ value: 100
1848
+ - type: cos_sim_f1
1849
+ value: 99.9490575649516
1850
+ - type: cos_sim_precision
1851
+ value: 100
1852
+ - type: cos_sim_recall
1853
+ value: 99.89816700610999
1854
+ - type: dot_accuracy
1855
+ value: 99.89816700610999
1856
+ - type: dot_ap
1857
+ value: 100
1858
+ - type: dot_f1
1859
+ value: 99.9490575649516
1860
+ - type: dot_precision
1861
+ value: 100
1862
+ - type: dot_recall
1863
+ value: 99.89816700610999
1864
+ - type: euclidean_accuracy
1865
+ value: 99.89816700610999
1866
+ - type: euclidean_ap
1867
+ value: 100
1868
+ - type: euclidean_f1
1869
+ value: 99.9490575649516
1870
+ - type: euclidean_precision
1871
+ value: 100
1872
+ - type: euclidean_recall
1873
+ value: 99.89816700610999
1874
+ - type: manhattan_accuracy
1875
+ value: 99.89816700610999
1876
+ - type: manhattan_ap
1877
+ value: 100
1878
+ - type: manhattan_f1
1879
+ value: 99.9490575649516
1880
+ - type: manhattan_precision
1881
+ value: 100
1882
+ - type: manhattan_recall
1883
+ value: 99.89816700610999
1884
+ - type: max_accuracy
1885
+ value: 99.89816700610999
1886
+ - type: max_ap
1887
+ value: 100
1888
+ - type: max_f1
1889
+ value: 99.9490575649516
1890
+ - task:
1891
+ type: PairClassification
1892
+ dataset:
1893
+ type: paws-x
1894
+ name: MTEB PawsX (en)
1895
+ config: en
1896
+ split: test
1897
+ revision: 8a04d940a42cd40658986fdd8e3da561533a3646
1898
+ metrics:
1899
+ - type: cos_sim_accuracy
1900
+ value: 61.25000000000001
1901
+ - type: cos_sim_ap
1902
+ value: 59.23166242799505
1903
+ - type: cos_sim_f1
1904
+ value: 62.53016201309893
1905
+ - type: cos_sim_precision
1906
+ value: 45.486459378134406
1907
+ - type: cos_sim_recall
1908
+ value: 100
1909
+ - type: dot_accuracy
1910
+ value: 61.25000000000001
1911
+ - type: dot_ap
1912
+ value: 59.23109306756652
1913
+ - type: dot_f1
1914
+ value: 62.53016201309893
1915
+ - type: dot_precision
1916
+ value: 45.486459378134406
1917
+ - type: dot_recall
1918
+ value: 100
1919
+ - type: euclidean_accuracy
1920
+ value: 61.25000000000001
1921
+ - type: euclidean_ap
1922
+ value: 59.23166242799505
1923
+ - type: euclidean_f1
1924
+ value: 62.53016201309893
1925
+ - type: euclidean_precision
1926
+ value: 45.486459378134406
1927
+ - type: euclidean_recall
1928
+ value: 100
1929
+ - type: manhattan_accuracy
1930
+ value: 61.25000000000001
1931
+ - type: manhattan_ap
1932
+ value: 59.23015114712089
1933
+ - type: manhattan_f1
1934
+ value: 62.50861474844934
1935
+ - type: manhattan_precision
1936
+ value: 45.46365914786967
1937
+ - type: manhattan_recall
1938
+ value: 100
1939
+ - type: max_accuracy
1940
+ value: 61.25000000000001
1941
+ - type: max_ap
1942
+ value: 59.23166242799505
1943
+ - type: max_f1
1944
+ value: 62.53016201309893
1945
+ - task:
1946
+ type: Retrieval
1947
+ dataset:
1948
+ type: mteb/quora
1949
+ name: MTEB QuoraRetrieval
1950
+ config: default
1951
+ split: test
1952
+ revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
1953
+ metrics:
1954
+ - type: map_at_1
1955
+ value: 69.919
1956
+ - type: map_at_10
1957
+ value: 83.636
1958
+ - type: map_at_100
1959
+ value: 84.27
1960
+ - type: map_at_1000
1961
+ value: 84.289
1962
+ - type: map_at_3
1963
+ value: 80.744
1964
+ - type: map_at_5
1965
+ value: 82.509
1966
+ - type: mrr_at_1
1967
+ value: 80.52
1968
+ - type: mrr_at_10
1969
+ value: 86.751
1970
+ - type: mrr_at_100
1971
+ value: 86.875
1972
+ - type: mrr_at_1000
1973
+ value: 86.876
1974
+ - type: mrr_at_3
1975
+ value: 85.798
1976
+ - type: mrr_at_5
1977
+ value: 86.414
1978
+ - type: ndcg_at_1
1979
+ value: 80.53
1980
+ - type: ndcg_at_10
1981
+ value: 87.465
1982
+ - type: ndcg_at_100
1983
+ value: 88.762
1984
+ - type: ndcg_at_1000
1985
+ value: 88.90599999999999
1986
+ - type: ndcg_at_3
1987
+ value: 84.634
1988
+ - type: ndcg_at_5
1989
+ value: 86.09400000000001
1990
+ - type: precision_at_1
1991
+ value: 80.53
1992
+ - type: precision_at_10
1993
+ value: 13.263
1994
+ - type: precision_at_100
1995
+ value: 1.517
1996
+ - type: precision_at_1000
1997
+ value: 0.156
1998
+ - type: precision_at_3
1999
+ value: 36.973
2000
+ - type: precision_at_5
2001
+ value: 24.25
2002
+ - type: recall_at_1
2003
+ value: 69.919
2004
+ - type: recall_at_10
2005
+ value: 94.742
2006
+ - type: recall_at_100
2007
+ value: 99.221
2008
+ - type: recall_at_1000
2009
+ value: 99.917
2010
+ - type: recall_at_3
2011
+ value: 86.506
2012
+ - type: recall_at_5
2013
+ value: 90.736
2014
+ - task:
2015
+ type: Clustering
2016
+ dataset:
2017
+ type: mteb/reddit-clustering
2018
+ name: MTEB RedditClustering
2019
+ config: default
2020
+ split: test
2021
+ revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
2022
+ metrics:
2023
+ - type: v_measure
2024
+ value: 50.47309147963901
2025
+ - task:
2026
+ type: Clustering
2027
+ dataset:
2028
+ type: mteb/reddit-clustering-p2p
2029
+ name: MTEB RedditClusteringP2P
2030
+ config: default
2031
+ split: test
2032
+ revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
2033
+ metrics:
2034
+ - type: v_measure
2035
+ value: 60.53779561923047
2036
+ - task:
2037
+ type: Retrieval
2038
+ dataset:
2039
+ type: mteb/scidocs
2040
+ name: MTEB SCIDOCS
2041
+ config: default
2042
+ split: test
2043
+ revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
2044
+ metrics:
2045
+ - type: map_at_1
2046
+ value: 4.843
2047
+ - type: map_at_10
2048
+ value: 11.664
2049
+ - type: map_at_100
2050
+ value: 13.499
2051
+ - type: map_at_1000
2052
+ value: 13.771
2053
+ - type: map_at_3
2054
+ value: 8.602
2055
+ - type: map_at_5
2056
+ value: 10.164
2057
+ - type: mrr_at_1
2058
+ value: 23.9
2059
+ - type: mrr_at_10
2060
+ value: 34.018
2061
+ - type: mrr_at_100
2062
+ value: 35.099000000000004
2063
+ - type: mrr_at_1000
2064
+ value: 35.162
2065
+ - type: mrr_at_3
2066
+ value: 31.233
2067
+ - type: mrr_at_5
2068
+ value: 32.793
2069
+ - type: ndcg_at_1
2070
+ value: 23.9
2071
+ - type: ndcg_at_10
2072
+ value: 19.42
2073
+ - type: ndcg_at_100
2074
+ value: 26.715
2075
+ - type: ndcg_at_1000
2076
+ value: 31.776
2077
+ - type: ndcg_at_3
2078
+ value: 19.165
2079
+ - type: ndcg_at_5
2080
+ value: 16.46
2081
+ - type: precision_at_1
2082
+ value: 23.9
2083
+ - type: precision_at_10
2084
+ value: 9.82
2085
+ - type: precision_at_100
2086
+ value: 2.0340000000000003
2087
+ - type: precision_at_1000
2088
+ value: 0.325
2089
+ - type: precision_at_3
2090
+ value: 17.767
2091
+ - type: precision_at_5
2092
+ value: 14.24
2093
+ - type: recall_at_1
2094
+ value: 4.843
2095
+ - type: recall_at_10
2096
+ value: 19.895
2097
+ - type: recall_at_100
2098
+ value: 41.302
2099
+ - type: recall_at_1000
2100
+ value: 66.077
2101
+ - type: recall_at_3
2102
+ value: 10.803
2103
+ - type: recall_at_5
2104
+ value: 14.418000000000001
2105
+ - task:
2106
+ type: STS
2107
+ dataset:
2108
+ type: mteb/sickr-sts
2109
+ name: MTEB SICK-R
2110
+ config: default
2111
+ split: test
2112
+ revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
2113
+ metrics:
2114
+ - type: cos_sim_pearson
2115
+ value: 76.94120735638143
2116
+ - type: cos_sim_spearman
2117
+ value: 69.66114097154585
2118
+ - type: euclidean_pearson
2119
+ value: 73.11242035696426
2120
+ - type: euclidean_spearman
2121
+ value: 69.66114271982464
2122
+ - type: manhattan_pearson
2123
+ value: 73.07993034858605
2124
+ - type: manhattan_spearman
2125
+ value: 69.6457893357314
2126
+ - task:
2127
+ type: STS
2128
+ dataset:
2129
+ type: mteb/sts12-sts
2130
+ name: MTEB STS12
2131
+ config: default
2132
+ split: test
2133
+ revision: a0d554a64d88156834ff5ae9920b964011b16384
2134
+ metrics:
2135
+ - type: cos_sim_pearson
2136
+ value: 74.72893353272778
2137
+ - type: cos_sim_spearman
2138
+ value: 68.78540928870311
2139
+ - type: euclidean_pearson
2140
+ value: 71.13907970605574
2141
+ - type: euclidean_spearman
2142
+ value: 68.78540928870311
2143
+ - type: manhattan_pearson
2144
+ value: 71.02709590547859
2145
+ - type: manhattan_spearman
2146
+ value: 68.71685896660532
2147
+ - task:
2148
+ type: STS
2149
+ dataset:
2150
+ type: mteb/sts13-sts
2151
+ name: MTEB STS13
2152
+ config: default
2153
+ split: test
2154
+ revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
2155
+ metrics:
2156
+ - type: cos_sim_pearson
2157
+ value: 79.30142652684971
2158
+ - type: cos_sim_spearman
2159
+ value: 79.61879435615303
2160
+ - type: euclidean_pearson
2161
+ value: 79.08730432883864
2162
+ - type: euclidean_spearman
2163
+ value: 79.61879435615303
2164
+ - type: manhattan_pearson
2165
+ value: 78.99621073156322
2166
+ - type: manhattan_spearman
2167
+ value: 79.53806342308278
2168
+ - task:
2169
+ type: STS
2170
+ dataset:
2171
+ type: mteb/sts14-sts
2172
+ name: MTEB STS14
2173
+ config: default
2174
+ split: test
2175
+ revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
2176
+ metrics:
2177
+ - type: cos_sim_pearson
2178
+ value: 78.99585233036139
2179
+ - type: cos_sim_spearman
2180
+ value: 75.57574519760183
2181
+ - type: euclidean_pearson
2182
+ value: 77.33835658613162
2183
+ - type: euclidean_spearman
2184
+ value: 75.57573873503655
2185
+ - type: manhattan_pearson
2186
+ value: 77.12175044789362
2187
+ - type: manhattan_spearman
2188
+ value: 75.41293517634836
2189
+ - task:
2190
+ type: STS
2191
+ dataset:
2192
+ type: mteb/sts15-sts
2193
+ name: MTEB STS15
2194
+ config: default
2195
+ split: test
2196
+ revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
2197
+ metrics:
2198
+ - type: cos_sim_pearson
2199
+ value: 83.9694268253376
2200
+ - type: cos_sim_spearman
2201
+ value: 84.64256921939338
2202
+ - type: euclidean_pearson
2203
+ value: 83.92322958711
2204
+ - type: euclidean_spearman
2205
+ value: 84.64257976421872
2206
+ - type: manhattan_pearson
2207
+ value: 83.93503107204337
2208
+ - type: manhattan_spearman
2209
+ value: 84.63611608236032
2210
+ - task:
2211
+ type: STS
2212
+ dataset:
2213
+ type: mteb/sts16-sts
2214
+ name: MTEB STS16
2215
+ config: default
2216
+ split: test
2217
+ revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
2218
+ metrics:
2219
+ - type: cos_sim_pearson
2220
+ value: 81.09041419790253
2221
+ - type: cos_sim_spearman
2222
+ value: 82.39869157752557
2223
+ - type: euclidean_pearson
2224
+ value: 82.04595698258301
2225
+ - type: euclidean_spearman
2226
+ value: 82.39869157752557
2227
+ - type: manhattan_pearson
2228
+ value: 81.97581168053004
2229
+ - type: manhattan_spearman
2230
+ value: 82.34255320578193
2231
+ - task:
2232
+ type: STS
2233
+ dataset:
2234
+ type: mteb/sts17-crosslingual-sts
2235
+ name: MTEB STS17 (en-en)
2236
+ config: en-en
2237
+ split: test
2238
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
2239
+ metrics:
2240
+ - type: cos_sim_pearson
2241
+ value: 86.35210432821825
2242
+ - type: cos_sim_spearman
2243
+ value: 86.73200885328937
2244
+ - type: euclidean_pearson
2245
+ value: 86.8527089168747
2246
+ - type: euclidean_spearman
2247
+ value: 86.73200885328937
2248
+ - type: manhattan_pearson
2249
+ value: 86.95671235295457
2250
+ - type: manhattan_spearman
2251
+ value: 86.77713700838545
2252
+ - task:
2253
+ type: STS
2254
+ dataset:
2255
+ type: mteb/sts22-crosslingual-sts
2256
+ name: MTEB STS22 (en)
2257
+ config: en
2258
+ split: test
2259
+ revision: eea2b4fe26a775864c896887d910b76a8098ad3f
2260
+ metrics:
2261
+ - type: cos_sim_pearson
2262
+ value: 68.91106612960657
2263
+ - type: cos_sim_spearman
2264
+ value: 69.48524490302286
2265
+ - type: euclidean_pearson
2266
+ value: 70.51347841618035
2267
+ - type: euclidean_spearman
2268
+ value: 69.48524490302286
2269
+ - type: manhattan_pearson
2270
+ value: 70.31770181334245
2271
+ - type: manhattan_spearman
2272
+ value: 69.12494700138238
2273
+ - task:
2274
+ type: STS
2275
+ dataset:
2276
+ type: mteb/stsbenchmark-sts
2277
+ name: MTEB STSBenchmark
2278
+ config: default
2279
+ split: test
2280
+ revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
2281
+ metrics:
2282
+ - type: cos_sim_pearson
2283
+ value: 81.54104342761988
2284
+ - type: cos_sim_spearman
2285
+ value: 81.18789220331483
2286
+ - type: euclidean_pearson
2287
+ value: 81.5895544590969
2288
+ - type: euclidean_spearman
2289
+ value: 81.18789220331483
2290
+ - type: manhattan_pearson
2291
+ value: 81.4738562449809
2292
+ - type: manhattan_spearman
2293
+ value: 81.06565101416024
2294
+ - task:
2295
+ type: STS
2296
+ dataset:
2297
+ type: PhilipMay/stsb_multi_mt
2298
+ name: MTEB STSBenchmarkMultilingualSTS (en)
2299
+ config: en
2300
+ split: test
2301
+ revision: 93d57ef91790589e3ce9c365164337a8a78b7632
2302
+ metrics:
2303
+ - type: cos_sim_pearson
2304
+ value: 81.54104346197056
2305
+ - type: cos_sim_spearman
2306
+ value: 81.18789220331483
2307
+ - type: euclidean_pearson
2308
+ value: 81.58955451690102
2309
+ - type: euclidean_spearman
2310
+ value: 81.18789220331483
2311
+ - type: manhattan_pearson
2312
+ value: 81.47385630064072
2313
+ - type: manhattan_spearman
2314
+ value: 81.06565101416024
2315
+ - task:
2316
+ type: Reranking
2317
+ dataset:
2318
+ type: mteb/scidocs-reranking
2319
+ name: MTEB SciDocsRR
2320
+ config: default
2321
+ split: test
2322
+ revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
2323
+ metrics:
2324
+ - type: map
2325
+ value: 79.34107964300796
2326
+ - type: mrr
2327
+ value: 94.01917889662987
2328
+ - task:
2329
+ type: Retrieval
2330
+ dataset:
2331
+ type: mteb/scifact
2332
+ name: MTEB SciFact
2333
+ config: default
2334
+ split: test
2335
+ revision: 0228b52cf27578f30900b9e5271d331663a030d7
2336
+ metrics:
2337
+ - type: map_at_1
2338
+ value: 55.928
2339
+ - type: map_at_10
2340
+ value: 65.443
2341
+ - type: map_at_100
2342
+ value: 66.067
2343
+ - type: map_at_1000
2344
+ value: 66.091
2345
+ - type: map_at_3
2346
+ value: 62.629999999999995
2347
+ - type: map_at_5
2348
+ value: 64.35
2349
+ - type: mrr_at_1
2350
+ value: 59
2351
+ - type: mrr_at_10
2352
+ value: 66.845
2353
+ - type: mrr_at_100
2354
+ value: 67.31899999999999
2355
+ - type: mrr_at_1000
2356
+ value: 67.342
2357
+ - type: mrr_at_3
2358
+ value: 64.61099999999999
2359
+ - type: mrr_at_5
2360
+ value: 66.044
2361
+ - type: ndcg_at_1
2362
+ value: 59
2363
+ - type: ndcg_at_10
2364
+ value: 69.921
2365
+ - type: ndcg_at_100
2366
+ value: 72.365
2367
+ - type: ndcg_at_1000
2368
+ value: 73.055
2369
+ - type: ndcg_at_3
2370
+ value: 65.086
2371
+ - type: ndcg_at_5
2372
+ value: 67.62700000000001
2373
+ - type: precision_at_1
2374
+ value: 59
2375
+ - type: precision_at_10
2376
+ value: 9.3
2377
+ - type: precision_at_100
2378
+ value: 1.057
2379
+ - type: precision_at_1000
2380
+ value: 0.11100000000000002
2381
+ - type: precision_at_3
2382
+ value: 25.333
2383
+ - type: precision_at_5
2384
+ value: 16.866999999999997
2385
+ - type: recall_at_1
2386
+ value: 55.928
2387
+ - type: recall_at_10
2388
+ value: 82.289
2389
+ - type: recall_at_100
2390
+ value: 92.833
2391
+ - type: recall_at_1000
2392
+ value: 98.333
2393
+ - type: recall_at_3
2394
+ value: 69.172
2395
+ - type: recall_at_5
2396
+ value: 75.628
2397
+ - task:
2398
+ type: PairClassification
2399
+ dataset:
2400
+ type: mteb/sprintduplicatequestions-pairclassification
2401
+ name: MTEB SprintDuplicateQuestions
2402
+ config: default
2403
+ split: test
2404
+ revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
2405
+ metrics:
2406
+ - type: cos_sim_accuracy
2407
+ value: 99.81881188118813
2408
+ - type: cos_sim_ap
2409
+ value: 95.2776439040401
2410
+ - type: cos_sim_f1
2411
+ value: 90.74355083459787
2412
+ - type: cos_sim_precision
2413
+ value: 91.81166837256909
2414
+ - type: cos_sim_recall
2415
+ value: 89.7
2416
+ - type: dot_accuracy
2417
+ value: 99.81881188118813
2418
+ - type: dot_ap
2419
+ value: 95.27764092100406
2420
+ - type: dot_f1
2421
+ value: 90.74355083459787
2422
+ - type: dot_precision
2423
+ value: 91.81166837256909
2424
+ - type: dot_recall
2425
+ value: 89.7
2426
+ - type: euclidean_accuracy
2427
+ value: 99.81881188118813
2428
+ - type: euclidean_ap
2429
+ value: 95.27764091101388
2430
+ - type: euclidean_f1
2431
+ value: 90.74355083459787
2432
+ - type: euclidean_precision
2433
+ value: 91.81166837256909
2434
+ - type: euclidean_recall
2435
+ value: 89.7
2436
+ - type: manhattan_accuracy
2437
+ value: 99.82079207920792
2438
+ - type: manhattan_ap
2439
+ value: 95.25081634689418
2440
+ - type: manhattan_f1
2441
+ value: 90.75114971895759
2442
+ - type: manhattan_precision
2443
+ value: 92.78996865203762
2444
+ - type: manhattan_recall
2445
+ value: 88.8
2446
+ - type: max_accuracy
2447
+ value: 99.82079207920792
2448
+ - type: max_ap
2449
+ value: 95.2776439040401
2450
+ - type: max_f1
2451
+ value: 90.75114971895759
2452
+ - task:
2453
+ type: Clustering
2454
+ dataset:
2455
+ type: mteb/stackexchange-clustering
2456
+ name: MTEB StackExchangeClustering
2457
+ config: default
2458
+ split: test
2459
+ revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
2460
+ metrics:
2461
+ - type: v_measure
2462
+ value: 60.69855369728728
2463
+ - task:
2464
+ type: Clustering
2465
+ dataset:
2466
+ type: mteb/stackexchange-clustering-p2p
2467
+ name: MTEB StackExchangeClusteringP2P
2468
+ config: default
2469
+ split: test
2470
+ revision: 815ca46b2622cec33ccafc3735d572c266efdb44
2471
+ metrics:
2472
+ - type: v_measure
2473
+ value: 33.98191834367251
2474
+ - task:
2475
+ type: Reranking
2476
+ dataset:
2477
+ type: mteb/stackoverflowdupquestions-reranking
2478
+ name: MTEB StackOverflowDupQuestions
2479
+ config: default
2480
+ split: test
2481
+ revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
2482
+ metrics:
2483
+ - type: map
2484
+ value: 50.156163330429614
2485
+ - type: mrr
2486
+ value: 50.90145148968678
2487
+ - task:
2488
+ type: Summarization
2489
+ dataset:
2490
+ type: mteb/summeval
2491
+ name: MTEB SummEval
2492
+ config: default
2493
+ split: test
2494
+ revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
2495
+ metrics:
2496
+ - type: cos_sim_pearson
2497
+ value: 31.16938079808134
2498
+ - type: cos_sim_spearman
2499
+ value: 31.74655874538245
2500
+ - type: dot_pearson
2501
+ value: 31.169380299671705
2502
+ - type: dot_spearman
2503
+ value: 31.74655874538245
2504
+ - task:
2505
+ type: Retrieval
2506
+ dataset:
2507
+ type: mteb/trec-covid
2508
+ name: MTEB TRECCOVID
2509
+ config: default
2510
+ split: test
2511
+ revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
2512
+ metrics:
2513
+ - type: map_at_1
2514
+ value: 0.252
2515
+ - type: map_at_10
2516
+ value: 2.009
2517
+ - type: map_at_100
2518
+ value: 11.611
2519
+ - type: map_at_1000
2520
+ value: 27.811999999999998
2521
+ - type: map_at_3
2522
+ value: 0.685
2523
+ - type: map_at_5
2524
+ value: 1.08
2525
+ - type: mrr_at_1
2526
+ value: 94
2527
+ - type: mrr_at_10
2528
+ value: 97
2529
+ - type: mrr_at_100
2530
+ value: 97
2531
+ - type: mrr_at_1000
2532
+ value: 97
2533
+ - type: mrr_at_3
2534
+ value: 97
2535
+ - type: mrr_at_5
2536
+ value: 97
2537
+ - type: ndcg_at_1
2538
+ value: 88
2539
+ - type: ndcg_at_10
2540
+ value: 81.388
2541
+ - type: ndcg_at_100
2542
+ value: 60.629
2543
+ - type: ndcg_at_1000
2544
+ value: 52.38
2545
+ - type: ndcg_at_3
2546
+ value: 86.827
2547
+ - type: ndcg_at_5
2548
+ value: 84.597
2549
+ - type: precision_at_1
2550
+ value: 94
2551
+ - type: precision_at_10
2552
+ value: 85.8
2553
+ - type: precision_at_100
2554
+ value: 62.419999999999995
2555
+ - type: precision_at_1000
2556
+ value: 23.31
2557
+ - type: precision_at_3
2558
+ value: 90.667
2559
+ - type: precision_at_5
2560
+ value: 88.4
2561
+ - type: recall_at_1
2562
+ value: 0.252
2563
+ - type: recall_at_10
2564
+ value: 2.164
2565
+ - type: recall_at_100
2566
+ value: 14.613999999999999
2567
+ - type: recall_at_1000
2568
+ value: 48.730000000000004
2569
+ - type: recall_at_3
2570
+ value: 0.7020000000000001
2571
+ - type: recall_at_5
2572
+ value: 1.122
2573
+ - task:
2574
+ type: Retrieval
2575
+ dataset:
2576
+ type: mteb/touche2020
2577
+ name: MTEB Touche2020
2578
+ config: default
2579
+ split: test
2580
+ revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
2581
+ metrics:
2582
+ - type: map_at_1
2583
+ value: 3.476
2584
+ - type: map_at_10
2585
+ value: 13.442000000000002
2586
+ - type: map_at_100
2587
+ value: 20.618
2588
+ - type: map_at_1000
2589
+ value: 22.175
2590
+ - type: map_at_3
2591
+ value: 6.968000000000001
2592
+ - type: map_at_5
2593
+ value: 9.214
2594
+ - type: mrr_at_1
2595
+ value: 44.897999999999996
2596
+ - type: mrr_at_10
2597
+ value: 56.77100000000001
2598
+ - type: mrr_at_100
2599
+ value: 57.226
2600
+ - type: mrr_at_1000
2601
+ value: 57.226
2602
+ - type: mrr_at_3
2603
+ value: 52.381
2604
+ - type: mrr_at_5
2605
+ value: 54.523999999999994
2606
+ - type: ndcg_at_1
2607
+ value: 42.857
2608
+ - type: ndcg_at_10
2609
+ value: 32.507999999999996
2610
+ - type: ndcg_at_100
2611
+ value: 43.614000000000004
2612
+ - type: ndcg_at_1000
2613
+ value: 53.82
2614
+ - type: ndcg_at_3
2615
+ value: 36.818
2616
+ - type: ndcg_at_5
2617
+ value: 33.346
2618
+ - type: precision_at_1
2619
+ value: 44.897999999999996
2620
+ - type: precision_at_10
2621
+ value: 28.571
2622
+ - type: precision_at_100
2623
+ value: 8.652999999999999
2624
+ - type: precision_at_1000
2625
+ value: 1.5709999999999997
2626
+ - type: precision_at_3
2627
+ value: 38.095
2628
+ - type: precision_at_5
2629
+ value: 32.245000000000005
2630
+ - type: recall_at_1
2631
+ value: 3.476
2632
+ - type: recall_at_10
2633
+ value: 20.827
2634
+ - type: recall_at_100
2635
+ value: 53.04299999999999
2636
+ - type: recall_at_1000
2637
+ value: 84.221
2638
+ - type: recall_at_3
2639
+ value: 8.200000000000001
2640
+ - type: recall_at_5
2641
+ value: 11.651
2642
+ - task:
2643
+ type: Classification
2644
+ dataset:
2645
+ type: mteb/toxic_conversations_50k
2646
+ name: MTEB ToxicConversationsClassification
2647
+ config: default
2648
+ split: test
2649
+ revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
2650
+ metrics:
2651
+ - type: accuracy
2652
+ value: 61.96360000000001
2653
+ - type: ap
2654
+ value: 11.256160324436445
2655
+ - type: f1
2656
+ value: 48.07712827691349
2657
+ - task:
2658
+ type: Classification
2659
+ dataset:
2660
+ type: mteb/tweet_sentiment_extraction
2661
+ name: MTEB TweetSentimentExtractionClassification
2662
+ config: default
2663
+ split: test
2664
+ revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
2665
+ metrics:
2666
+ - type: accuracy
2667
+ value: 58.90492359932088
2668
+ - type: f1
2669
+ value: 59.12542417513503
2670
+ - task:
2671
+ type: Clustering
2672
+ dataset:
2673
+ type: mteb/twentynewsgroups-clustering
2674
+ name: MTEB TwentyNewsgroupsClustering
2675
+ config: default
2676
+ split: test
2677
+ revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
2678
+ metrics:
2679
+ - type: v_measure
2680
+ value: 38.284935353315355
2681
+ - task:
2682
+ type: PairClassification
2683
+ dataset:
2684
+ type: mteb/twittersemeval2015-pairclassification
2685
+ name: MTEB TwitterSemEval2015
2686
+ config: default
2687
+ split: test
2688
+ revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
2689
+ metrics:
2690
+ - type: cos_sim_accuracy
2691
+ value: 83.4714192048638
2692
+ - type: cos_sim_ap
2693
+ value: 65.77588263185375
2694
+ - type: cos_sim_f1
2695
+ value: 62.459508098380326
2696
+ - type: cos_sim_precision
2697
+ value: 57.27172717271727
2698
+ - type: cos_sim_recall
2699
+ value: 68.68073878627968
2700
+ - type: dot_accuracy
2701
+ value: 83.4714192048638
2702
+ - type: dot_ap
2703
+ value: 65.77588818364636
2704
+ - type: dot_f1
2705
+ value: 62.459508098380326
2706
+ - type: dot_precision
2707
+ value: 57.27172717271727
2708
+ - type: dot_recall
2709
+ value: 68.68073878627968
2710
+ - type: euclidean_accuracy
2711
+ value: 83.4714192048638
2712
+ - type: euclidean_ap
2713
+ value: 65.77587693431595
2714
+ - type: euclidean_f1
2715
+ value: 62.459508098380326
2716
+ - type: euclidean_precision
2717
+ value: 57.27172717271727
2718
+ - type: euclidean_recall
2719
+ value: 68.68073878627968
2720
+ - type: manhattan_accuracy
2721
+ value: 83.47737974608094
2722
+ - type: manhattan_ap
2723
+ value: 65.65957745829654
2724
+ - type: manhattan_f1
2725
+ value: 62.22760290556902
2726
+ - type: manhattan_precision
2727
+ value: 57.494407158836694
2728
+ - type: manhattan_recall
2729
+ value: 67.81002638522428
2730
+ - type: max_accuracy
2731
+ value: 83.47737974608094
2732
+ - type: max_ap
2733
+ value: 65.77588818364636
2734
+ - type: max_f1
2735
+ value: 62.459508098380326
2736
+ - task:
2737
+ type: PairClassification
2738
+ dataset:
2739
+ type: mteb/twitterurlcorpus-pairclassification
2740
+ name: MTEB TwitterURLCorpus
2741
+ config: default
2742
+ split: test
2743
+ revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
2744
+ metrics:
2745
+ - type: cos_sim_accuracy
2746
+ value: 88.64244964489463
2747
+ - type: cos_sim_ap
2748
+ value: 85.154122301394
2749
+ - type: cos_sim_f1
2750
+ value: 77.45617911327146
2751
+ - type: cos_sim_precision
2752
+ value: 74.23066064370413
2753
+ - type: cos_sim_recall
2754
+ value: 80.97474591931014
2755
+ - type: dot_accuracy
2756
+ value: 88.64244964489463
2757
+ - type: dot_ap
2758
+ value: 85.15411965587543
2759
+ - type: dot_f1
2760
+ value: 77.45617911327146
2761
+ - type: dot_precision
2762
+ value: 74.23066064370413
2763
+ - type: dot_recall
2764
+ value: 80.97474591931014
2765
+ - type: euclidean_accuracy
2766
+ value: 88.64244964489463
2767
+ - type: euclidean_ap
2768
+ value: 85.15414684113986
2769
+ - type: euclidean_f1
2770
+ value: 77.45617911327146
2771
+ - type: euclidean_precision
2772
+ value: 74.23066064370413
2773
+ - type: euclidean_recall
2774
+ value: 80.97474591931014
2775
+ - type: manhattan_accuracy
2776
+ value: 88.57841425078588
2777
+ - type: manhattan_ap
2778
+ value: 85.12472268567576
2779
+ - type: manhattan_f1
2780
+ value: 77.39497339937627
2781
+ - type: manhattan_precision
2782
+ value: 73.92584285413892
2783
+ - type: manhattan_recall
2784
+ value: 81.20572836464429
2785
+ - type: max_accuracy
2786
+ value: 88.64244964489463
2787
+ - type: max_ap
2788
+ value: 85.15414684113986
2789
+ - type: max_f1
2790
+ value: 77.45617911327146
2791
+ - task:
2792
+ type: Clustering
2793
+ dataset:
2794
+ type: jinaai/cities_wiki_clustering
2795
+ name: MTEB WikiCitiesClustering
2796
+ config: default
2797
+ split: test
2798
+ revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
2799
+ metrics:
2800
+ - type: v_measure
2801
+ value: 79.58576208710117
2802
+ ---