twadada commited on
Commit
7e8f91b
·
verified ·
1 Parent(s): 491fc81

Create README.md

Browse files
Files changed (1) hide show
  1. README.md +2599 -0
README.md ADDED
@@ -0,0 +1,2599 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - mteb
4
+ model-index:
5
+ - name: nomic_classification_307_w50k_b10k
6
+ results:
7
+ - task:
8
+ type: Classification
9
+ dataset:
10
+ type: None
11
+ name: MTEB AmazonCounterfactualClassification (en)
12
+ config: en
13
+ split: test
14
+ revision: e8379541af4e31359cca9fbcf4b00f2671dba205
15
+ metrics:
16
+ - type: accuracy
17
+ value: 71.70149253731343
18
+ - type: ap
19
+ value: 33.79646861902238
20
+ - type: f1
21
+ value: 65.39377031734182
22
+ - task:
23
+ type: Classification
24
+ dataset:
25
+ type: None
26
+ name: MTEB AmazonPolarityClassification
27
+ config: default
28
+ split: test
29
+ revision: e2d317d38cd51312af73b3d32a06d1a08b442046
30
+ metrics:
31
+ - type: accuracy
32
+ value: 64.577125
33
+ - type: ap
34
+ value: 59.69737246109206
35
+ - type: f1
36
+ value: 64.3577747072318
37
+ - task:
38
+ type: Classification
39
+ dataset:
40
+ type: None
41
+ name: MTEB AmazonReviewsClassification (en)
42
+ config: en
43
+ split: test
44
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
45
+ metrics:
46
+ - type: accuracy
47
+ value: 33.748
48
+ - type: f1
49
+ value: 33.3254582178127
50
+ - task:
51
+ type: Retrieval
52
+ dataset:
53
+ type: None
54
+ name: MTEB ArguAna
55
+ config: default
56
+ split: test
57
+ revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
58
+ metrics:
59
+ - type: map_at_1
60
+ value: 20.199
61
+ - type: map_at_10
62
+ value: 34.28
63
+ - type: map_at_100
64
+ value: 35.480000000000004
65
+ - type: map_at_1000
66
+ value: 35.504999999999995
67
+ - type: map_at_3
68
+ value: 29.682
69
+ - type: map_at_5
70
+ value: 32.385000000000005
71
+ - type: mrr_at_1
72
+ value: 20.91
73
+ - type: mrr_at_10
74
+ value: 34.536
75
+ - type: mrr_at_100
76
+ value: 35.743
77
+ - type: mrr_at_1000
78
+ value: 35.768
79
+ - type: mrr_at_3
80
+ value: 29.931
81
+ - type: mrr_at_5
82
+ value: 32.623000000000005
83
+ - type: ndcg_at_1
84
+ value: 20.199
85
+ - type: ndcg_at_10
86
+ value: 42.278
87
+ - type: ndcg_at_100
88
+ value: 47.924
89
+ - type: ndcg_at_1000
90
+ value: 48.537
91
+ - type: ndcg_at_3
92
+ value: 32.815
93
+ - type: ndcg_at_5
94
+ value: 37.681
95
+ - type: precision_at_1
96
+ value: 20.199
97
+ - type: precision_at_10
98
+ value: 6.792
99
+ - type: precision_at_100
100
+ value: 0.9390000000000001
101
+ - type: precision_at_1000
102
+ value: 0.099
103
+ - type: precision_at_3
104
+ value: 13.963999999999999
105
+ - type: precision_at_5
106
+ value: 10.74
107
+ - type: recall_at_1
108
+ value: 20.199
109
+ - type: recall_at_10
110
+ value: 67.923
111
+ - type: recall_at_100
112
+ value: 93.88300000000001
113
+ - type: recall_at_1000
114
+ value: 98.578
115
+ - type: recall_at_3
116
+ value: 41.892
117
+ - type: recall_at_5
118
+ value: 53.698
119
+ - task:
120
+ type: Clustering
121
+ dataset:
122
+ type: None
123
+ name: MTEB ArxivClusteringP2P
124
+ config: default
125
+ split: test
126
+ revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
127
+ metrics:
128
+ - type: v_measure
129
+ value: 31.715994496712955
130
+ - task:
131
+ type: Clustering
132
+ dataset:
133
+ type: None
134
+ name: MTEB ArxivClusteringS2S
135
+ config: default
136
+ split: test
137
+ revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
138
+ metrics:
139
+ - type: v_measure
140
+ value: 22.014928355542406
141
+ - task:
142
+ type: Reranking
143
+ dataset:
144
+ type: None
145
+ name: MTEB AskUbuntuDupQuestions
146
+ config: default
147
+ split: test
148
+ revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
149
+ metrics:
150
+ - type: map
151
+ value: 52.73401198259723
152
+ - type: mrr
153
+ value: 66.18574946137272
154
+ - task:
155
+ type: STS
156
+ dataset:
157
+ type: None
158
+ name: MTEB BIOSSES
159
+ config: default
160
+ split: test
161
+ revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
162
+ metrics:
163
+ - type: cos_sim_pearson
164
+ value: 78.32819163750328
165
+ - type: cos_sim_spearman
166
+ value: 76.32884763830812
167
+ - type: euclidean_pearson
168
+ value: 77.6247892757331
169
+ - type: euclidean_spearman
170
+ value: 76.32884763830812
171
+ - type: manhattan_pearson
172
+ value: 77.4560490620549
173
+ - type: manhattan_spearman
174
+ value: 76.11679461376502
175
+ - task:
176
+ type: Classification
177
+ dataset:
178
+ type: None
179
+ name: MTEB Banking77Classification
180
+ config: default
181
+ split: test
182
+ revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
183
+ metrics:
184
+ - type: accuracy
185
+ value: 72.16883116883118
186
+ - type: f1
187
+ value: 71.34298475263475
188
+ - task:
189
+ type: Clustering
190
+ dataset:
191
+ type: None
192
+ name: MTEB BiorxivClusteringP2P
193
+ config: default
194
+ split: test
195
+ revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
196
+ metrics:
197
+ - type: v_measure
198
+ value: 29.528784676707033
199
+ - task:
200
+ type: Clustering
201
+ dataset:
202
+ type: None
203
+ name: MTEB BiorxivClusteringS2S
204
+ config: default
205
+ split: test
206
+ revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
207
+ metrics:
208
+ - type: v_measure
209
+ value: 19.565519101446977
210
+ - task:
211
+ type: Retrieval
212
+ dataset:
213
+ type: None
214
+ name: MTEB CQADupstackAndroidRetrieval
215
+ config: default
216
+ split: test
217
+ revision: f46a197baaae43b4f621051089b82a364682dfeb
218
+ metrics:
219
+ - type: map_at_1
220
+ value: 21.581
221
+ - type: map_at_10
222
+ value: 28.322999999999997
223
+ - type: map_at_100
224
+ value: 29.392000000000003
225
+ - type: map_at_1000
226
+ value: 29.547
227
+ - type: map_at_3
228
+ value: 26.214
229
+ - type: map_at_5
230
+ value: 27.339000000000002
231
+ - type: mrr_at_1
232
+ value: 27.182000000000002
233
+ - type: mrr_at_10
234
+ value: 34.075
235
+ - type: mrr_at_100
236
+ value: 34.92
237
+ - type: mrr_at_1000
238
+ value: 34.997
239
+ - type: mrr_at_3
240
+ value: 32.26
241
+ - type: mrr_at_5
242
+ value: 33.283
243
+ - type: ndcg_at_1
244
+ value: 27.182000000000002
245
+ - type: ndcg_at_10
246
+ value: 32.903999999999996
247
+ - type: ndcg_at_100
248
+ value: 37.852999999999994
249
+ - type: ndcg_at_1000
250
+ value: 41.177
251
+ - type: ndcg_at_3
252
+ value: 29.976999999999997
253
+ - type: ndcg_at_5
254
+ value: 31.039
255
+ - type: precision_at_1
256
+ value: 27.182000000000002
257
+ - type: precision_at_10
258
+ value: 6.194999999999999
259
+ - type: precision_at_100
260
+ value: 1.09
261
+ - type: precision_at_1000
262
+ value: 0.167
263
+ - type: precision_at_3
264
+ value: 14.354
265
+ - type: precision_at_5
266
+ value: 10.157
267
+ - type: recall_at_1
268
+ value: 21.581
269
+ - type: recall_at_10
270
+ value: 40.487
271
+ - type: recall_at_100
272
+ value: 62.832
273
+ - type: recall_at_1000
274
+ value: 85.768
275
+ - type: recall_at_3
276
+ value: 30.842000000000002
277
+ - type: recall_at_5
278
+ value: 34.497
279
+ - task:
280
+ type: Retrieval
281
+ dataset:
282
+ type: None
283
+ name: MTEB CQADupstackEnglishRetrieval
284
+ config: default
285
+ split: test
286
+ revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
287
+ metrics:
288
+ - type: map_at_1
289
+ value: 16.495
290
+ - type: map_at_10
291
+ value: 21.625
292
+ - type: map_at_100
293
+ value: 22.506
294
+ - type: map_at_1000
295
+ value: 22.633
296
+ - type: map_at_3
297
+ value: 19.819
298
+ - type: map_at_5
299
+ value: 20.817
300
+ - type: mrr_at_1
301
+ value: 20.892
302
+ - type: mrr_at_10
303
+ value: 25.768
304
+ - type: mrr_at_100
305
+ value: 26.533
306
+ - type: mrr_at_1000
307
+ value: 26.61
308
+ - type: mrr_at_3
309
+ value: 23.96
310
+ - type: mrr_at_5
311
+ value: 24.893
312
+ - type: ndcg_at_1
313
+ value: 20.892
314
+ - type: ndcg_at_10
315
+ value: 25.144
316
+ - type: ndcg_at_100
317
+ value: 29.425
318
+ - type: ndcg_at_1000
319
+ value: 32.436
320
+ - type: ndcg_at_3
321
+ value: 22.105
322
+ - type: ndcg_at_5
323
+ value: 23.416
324
+ - type: precision_at_1
325
+ value: 20.892
326
+ - type: precision_at_10
327
+ value: 4.6240000000000006
328
+ - type: precision_at_100
329
+ value: 0.8500000000000001
330
+ - type: precision_at_1000
331
+ value: 0.136
332
+ - type: precision_at_3
333
+ value: 10.403
334
+ - type: precision_at_5
335
+ value: 7.4270000000000005
336
+ - type: recall_at_1
337
+ value: 16.495
338
+ - type: recall_at_10
339
+ value: 31.627
340
+ - type: recall_at_100
341
+ value: 50.653999999999996
342
+ - type: recall_at_1000
343
+ value: 71.38
344
+ - type: recall_at_3
345
+ value: 22.987
346
+ - type: recall_at_5
347
+ value: 26.518000000000004
348
+ - task:
349
+ type: Retrieval
350
+ dataset:
351
+ type: None
352
+ name: MTEB CQADupstackGamingRetrieval
353
+ config: default
354
+ split: test
355
+ revision: 4885aa143210c98657558c04aaf3dc47cfb54340
356
+ metrics:
357
+ - type: map_at_1
358
+ value: 25.19
359
+ - type: map_at_10
360
+ value: 33.159
361
+ - type: map_at_100
362
+ value: 34.223
363
+ - type: map_at_1000
364
+ value: 34.322
365
+ - type: map_at_3
366
+ value: 30.866
367
+ - type: map_at_5
368
+ value: 32.016
369
+ - type: mrr_at_1
370
+ value: 29.091
371
+ - type: mrr_at_10
372
+ value: 36.208
373
+ - type: mrr_at_100
374
+ value: 37.059999999999995
375
+ - type: mrr_at_1000
376
+ value: 37.124
377
+ - type: mrr_at_3
378
+ value: 34.001999999999995
379
+ - type: mrr_at_5
380
+ value: 35.089999999999996
381
+ - type: ndcg_at_1
382
+ value: 29.091
383
+ - type: ndcg_at_10
384
+ value: 37.696000000000005
385
+ - type: ndcg_at_100
386
+ value: 42.774
387
+ - type: ndcg_at_1000
388
+ value: 45.064
389
+ - type: ndcg_at_3
390
+ value: 33.298
391
+ - type: ndcg_at_5
392
+ value: 35.089
393
+ - type: precision_at_1
394
+ value: 29.091
395
+ - type: precision_at_10
396
+ value: 6.132
397
+ - type: precision_at_100
398
+ value: 0.9530000000000001
399
+ - type: precision_at_1000
400
+ value: 0.123
401
+ - type: precision_at_3
402
+ value: 14.754000000000001
403
+ - type: precision_at_5
404
+ value: 10.082
405
+ - type: recall_at_1
406
+ value: 25.19
407
+ - type: recall_at_10
408
+ value: 48.542
409
+ - type: recall_at_100
410
+ value: 71.475
411
+ - type: recall_at_1000
412
+ value: 88.157
413
+ - type: recall_at_3
414
+ value: 36.512
415
+ - type: recall_at_5
416
+ value: 40.998000000000005
417
+ - task:
418
+ type: Retrieval
419
+ dataset:
420
+ type: None
421
+ name: MTEB CQADupstackGisRetrieval
422
+ config: default
423
+ split: test
424
+ revision: 5003b3064772da1887988e05400cf3806fe491f2
425
+ metrics:
426
+ - type: map_at_1
427
+ value: 10.979
428
+ - type: map_at_10
429
+ value: 15.160000000000002
430
+ - type: map_at_100
431
+ value: 15.927
432
+ - type: map_at_1000
433
+ value: 16.039
434
+ - type: map_at_3
435
+ value: 13.905000000000001
436
+ - type: map_at_5
437
+ value: 14.603
438
+ - type: mrr_at_1
439
+ value: 12.09
440
+ - type: mrr_at_10
441
+ value: 16.317999999999998
442
+ - type: mrr_at_100
443
+ value: 17.094
444
+ - type: mrr_at_1000
445
+ value: 17.198
446
+ - type: mrr_at_3
447
+ value: 15.028
448
+ - type: mrr_at_5
449
+ value: 15.712000000000002
450
+ - type: ndcg_at_1
451
+ value: 12.09
452
+ - type: ndcg_at_10
453
+ value: 17.71
454
+ - type: ndcg_at_100
455
+ value: 21.923000000000002
456
+ - type: ndcg_at_1000
457
+ value: 25.407999999999998
458
+ - type: ndcg_at_3
459
+ value: 15.139
460
+ - type: ndcg_at_5
461
+ value: 16.372
462
+ - type: precision_at_1
463
+ value: 12.09
464
+ - type: precision_at_10
465
+ value: 2.768
466
+ - type: precision_at_100
467
+ value: 0.521
468
+ - type: precision_at_1000
469
+ value: 0.087
470
+ - type: precision_at_3
471
+ value: 6.478000000000001
472
+ - type: precision_at_5
473
+ value: 4.542
474
+ - type: recall_at_1
475
+ value: 10.979
476
+ - type: recall_at_10
477
+ value: 24.548000000000002
478
+ - type: recall_at_100
479
+ value: 44.659
480
+ - type: recall_at_1000
481
+ value: 72.15899999999999
482
+ - type: recall_at_3
483
+ value: 17.552
484
+ - type: recall_at_5
485
+ value: 20.584
486
+ - task:
487
+ type: Retrieval
488
+ dataset:
489
+ type: None
490
+ name: MTEB CQADupstackMathematicaRetrieval
491
+ config: default
492
+ split: test
493
+ revision: 90fceea13679c63fe563ded68f3b6f06e50061de
494
+ metrics:
495
+ - type: map_at_1
496
+ value: 6.703
497
+ - type: map_at_10
498
+ value: 9.588000000000001
499
+ - type: map_at_100
500
+ value: 10.312000000000001
501
+ - type: map_at_1000
502
+ value: 10.428999999999998
503
+ - type: map_at_3
504
+ value: 8.473
505
+ - type: map_at_5
506
+ value: 9.118
507
+ - type: mrr_at_1
508
+ value: 8.706
509
+ - type: mrr_at_10
510
+ value: 11.818
511
+ - type: mrr_at_100
512
+ value: 12.568999999999999
513
+ - type: mrr_at_1000
514
+ value: 12.664
515
+ - type: mrr_at_3
516
+ value: 10.551
517
+ - type: mrr_at_5
518
+ value: 11.235000000000001
519
+ - type: ndcg_at_1
520
+ value: 8.706
521
+ - type: ndcg_at_10
522
+ value: 11.823
523
+ - type: ndcg_at_100
524
+ value: 15.674
525
+ - type: ndcg_at_1000
526
+ value: 19.256
527
+ - type: ndcg_at_3
528
+ value: 9.637
529
+ - type: ndcg_at_5
530
+ value: 10.661
531
+ - type: precision_at_1
532
+ value: 8.706
533
+ - type: precision_at_10
534
+ value: 2.251
535
+ - type: precision_at_100
536
+ value: 0.484
537
+ - type: precision_at_1000
538
+ value: 0.093
539
+ - type: precision_at_3
540
+ value: 4.601999999999999
541
+ - type: precision_at_5
542
+ value: 3.458
543
+ - type: recall_at_1
544
+ value: 6.703
545
+ - type: recall_at_10
546
+ value: 16.579
547
+ - type: recall_at_100
548
+ value: 34.054
549
+ - type: recall_at_1000
550
+ value: 60.769
551
+ - type: recall_at_3
552
+ value: 10.530000000000001
553
+ - type: recall_at_5
554
+ value: 13.126
555
+ - task:
556
+ type: Retrieval
557
+ dataset:
558
+ type: None
559
+ name: MTEB CQADupstackPhysicsRetrieval
560
+ config: default
561
+ split: test
562
+ revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
563
+ metrics:
564
+ - type: map_at_1
565
+ value: 17.688000000000002
566
+ - type: map_at_10
567
+ value: 23.169
568
+ - type: map_at_100
569
+ value: 24.275
570
+ - type: map_at_1000
571
+ value: 24.409
572
+ - type: map_at_3
573
+ value: 21.284
574
+ - type: map_at_5
575
+ value: 22.171
576
+ - type: mrr_at_1
577
+ value: 22.233
578
+ - type: mrr_at_10
579
+ value: 27.857
580
+ - type: mrr_at_100
581
+ value: 28.76
582
+ - type: mrr_at_1000
583
+ value: 28.841
584
+ - type: mrr_at_3
585
+ value: 25.857999999999997
586
+ - type: mrr_at_5
587
+ value: 26.922
588
+ - type: ndcg_at_1
589
+ value: 22.233
590
+ - type: ndcg_at_10
591
+ value: 27.203
592
+ - type: ndcg_at_100
593
+ value: 32.543
594
+ - type: ndcg_at_1000
595
+ value: 35.654
596
+ - type: ndcg_at_3
597
+ value: 23.863
598
+ - type: ndcg_at_5
599
+ value: 25.117
600
+ - type: precision_at_1
601
+ value: 22.233
602
+ - type: precision_at_10
603
+ value: 4.957000000000001
604
+ - type: precision_at_100
605
+ value: 0.919
606
+ - type: precision_at_1000
607
+ value: 0.13899999999999998
608
+ - type: precision_at_3
609
+ value: 11.036
610
+ - type: precision_at_5
611
+ value: 7.8149999999999995
612
+ - type: recall_at_1
613
+ value: 17.688000000000002
614
+ - type: recall_at_10
615
+ value: 34.969
616
+ - type: recall_at_100
617
+ value: 58.370999999999995
618
+ - type: recall_at_1000
619
+ value: 80.02
620
+ - type: recall_at_3
621
+ value: 25.332
622
+ - type: recall_at_5
623
+ value: 28.703
624
+ - task:
625
+ type: Retrieval
626
+ dataset:
627
+ type: None
628
+ name: MTEB CQADupstackProgrammersRetrieval
629
+ config: default
630
+ split: test
631
+ revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
632
+ metrics:
633
+ - type: map_at_1
634
+ value: 11.15
635
+ - type: map_at_10
636
+ value: 16.797
637
+ - type: map_at_100
638
+ value: 17.822
639
+ - type: map_at_1000
640
+ value: 17.956
641
+ - type: map_at_3
642
+ value: 14.985999999999999
643
+ - type: map_at_5
644
+ value: 16.044
645
+ - type: mrr_at_1
646
+ value: 14.155000000000001
647
+ - type: mrr_at_10
648
+ value: 20.01
649
+ - type: mrr_at_100
650
+ value: 20.966
651
+ - type: mrr_at_1000
652
+ value: 21.049
653
+ - type: mrr_at_3
654
+ value: 18.227
655
+ - type: mrr_at_5
656
+ value: 19.231
657
+ - type: ndcg_at_1
658
+ value: 14.155000000000001
659
+ - type: ndcg_at_10
660
+ value: 20.327
661
+ - type: ndcg_at_100
662
+ value: 25.490000000000002
663
+ - type: ndcg_at_1000
664
+ value: 28.854000000000003
665
+ - type: ndcg_at_3
666
+ value: 17.046
667
+ - type: ndcg_at_5
668
+ value: 18.647
669
+ - type: precision_at_1
670
+ value: 14.155000000000001
671
+ - type: precision_at_10
672
+ value: 3.893
673
+ - type: precision_at_100
674
+ value: 0.771
675
+ - type: precision_at_1000
676
+ value: 0.124
677
+ - type: precision_at_3
678
+ value: 8.219
679
+ - type: precision_at_5
680
+ value: 6.164
681
+ - type: recall_at_1
682
+ value: 11.15
683
+ - type: recall_at_10
684
+ value: 27.750999999999998
685
+ - type: recall_at_100
686
+ value: 50.612
687
+ - type: recall_at_1000
688
+ value: 74.617
689
+ - type: recall_at_3
690
+ value: 19.101000000000003
691
+ - type: recall_at_5
692
+ value: 22.999
693
+ - task:
694
+ type: Retrieval
695
+ dataset:
696
+ type: mteb/cqadupstack
697
+ name: MTEB CQADupstackRetrieval
698
+ config: default
699
+ split: test
700
+ revision: 4885aa143210c98657558c04aaf3dc47cfb54340
701
+ metrics:
702
+ - type: map_at_1
703
+ value: 13.562333333333335
704
+ - type: map_at_10
705
+ value: 18.514583333333334
706
+ - type: map_at_100
707
+ value: 19.362916666666667
708
+ - type: map_at_1000
709
+ value: 19.48625
710
+ - type: map_at_3
711
+ value: 16.955583333333337
712
+ - type: map_at_5
713
+ value: 17.788
714
+ - type: mrr_at_1
715
+ value: 16.54575
716
+ - type: mrr_at_10
717
+ value: 21.549249999999997
718
+ - type: mrr_at_100
719
+ value: 22.318500000000004
720
+ - type: mrr_at_1000
721
+ value: 22.405583333333333
722
+ - type: mrr_at_3
723
+ value: 19.9585
724
+ - type: mrr_at_5
725
+ value: 20.82183333333333
726
+ - type: ndcg_at_1
727
+ value: 16.54575
728
+ - type: ndcg_at_10
729
+ value: 21.80341666666667
730
+ - type: ndcg_at_100
731
+ value: 26.133833333333328
732
+ - type: ndcg_at_1000
733
+ value: 29.348666666666666
734
+ - type: ndcg_at_3
735
+ value: 18.973499999999998
736
+ - type: ndcg_at_5
737
+ value: 20.200833333333332
738
+ - type: precision_at_1
739
+ value: 16.54575
740
+ - type: precision_at_10
741
+ value: 3.895333333333334
742
+ - type: precision_at_100
743
+ value: 0.7226666666666668
744
+ - type: precision_at_1000
745
+ value: 0.11775
746
+ - type: precision_at_3
747
+ value: 8.796666666666667
748
+ - type: precision_at_5
749
+ value: 6.278083333333333
750
+ - type: recall_at_1
751
+ value: 13.562333333333335
752
+ - type: recall_at_10
753
+ value: 28.738833333333336
754
+ - type: recall_at_100
755
+ value: 48.66516666666668
756
+ - type: recall_at_1000
757
+ value: 72.21291666666666
758
+ - type: recall_at_3
759
+ value: 20.722166666666663
760
+ - type: recall_at_5
761
+ value: 23.920416666666668
762
+ - task:
763
+ type: Retrieval
764
+ dataset:
765
+ type: None
766
+ name: MTEB CQADupstackStatsRetrieval
767
+ config: default
768
+ split: test
769
+ revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
770
+ metrics:
771
+ - type: map_at_1
772
+ value: 10.612
773
+ - type: map_at_10
774
+ value: 14.233
775
+ - type: map_at_100
776
+ value: 14.804999999999998
777
+ - type: map_at_1000
778
+ value: 14.887
779
+ - type: map_at_3
780
+ value: 13.050999999999998
781
+ - type: map_at_5
782
+ value: 13.642999999999999
783
+ - type: mrr_at_1
784
+ value: 12.577
785
+ - type: mrr_at_10
786
+ value: 16.256999999999998
787
+ - type: mrr_at_100
788
+ value: 16.830000000000002
789
+ - type: mrr_at_1000
790
+ value: 16.909
791
+ - type: mrr_at_3
792
+ value: 15.031
793
+ - type: mrr_at_5
794
+ value: 15.613
795
+ - type: ndcg_at_1
796
+ value: 12.577
797
+ - type: ndcg_at_10
798
+ value: 16.81
799
+ - type: ndcg_at_100
800
+ value: 20.085
801
+ - type: ndcg_at_1000
802
+ value: 22.684
803
+ - type: ndcg_at_3
804
+ value: 14.471
805
+ - type: ndcg_at_5
806
+ value: 15.384
807
+ - type: precision_at_1
808
+ value: 12.577
809
+ - type: precision_at_10
810
+ value: 2.8529999999999998
811
+ - type: precision_at_100
812
+ value: 0.49699999999999994
813
+ - type: precision_at_1000
814
+ value: 0.079
815
+ - type: precision_at_3
816
+ value: 6.544
817
+ - type: precision_at_5
818
+ value: 4.601
819
+ - type: recall_at_1
820
+ value: 10.612
821
+ - type: recall_at_10
822
+ value: 22.983999999999998
823
+ - type: recall_at_100
824
+ value: 38.745000000000005
825
+ - type: recall_at_1000
826
+ value: 58.886
827
+ - type: recall_at_3
828
+ value: 15.982
829
+ - type: recall_at_5
830
+ value: 18.433
831
+ - task:
832
+ type: Retrieval
833
+ dataset:
834
+ type: None
835
+ name: MTEB CQADupstackTexRetrieval
836
+ config: default
837
+ split: test
838
+ revision: 46989137a86843e03a6195de44b09deda022eec7
839
+ metrics:
840
+ - type: map_at_1
841
+ value: 7.04
842
+ - type: map_at_10
843
+ value: 10.277
844
+ - type: map_at_100
845
+ value: 10.873
846
+ - type: map_at_1000
847
+ value: 10.989
848
+ - type: map_at_3
849
+ value: 9.243
850
+ - type: map_at_5
851
+ value: 9.843
852
+ - type: mrr_at_1
853
+ value: 8.774999999999999
854
+ - type: mrr_at_10
855
+ value: 12.468
856
+ - type: mrr_at_100
857
+ value: 13.084999999999999
858
+ - type: mrr_at_1000
859
+ value: 13.184000000000001
860
+ - type: mrr_at_3
861
+ value: 11.293000000000001
862
+ - type: mrr_at_5
863
+ value: 12.034
864
+ - type: ndcg_at_1
865
+ value: 8.774999999999999
866
+ - type: ndcg_at_10
867
+ value: 12.527
868
+ - type: ndcg_at_100
869
+ value: 15.939
870
+ - type: ndcg_at_1000
871
+ value: 19.383
872
+ - type: ndcg_at_3
873
+ value: 10.565
874
+ - type: ndcg_at_5
875
+ value: 11.555
876
+ - type: precision_at_1
877
+ value: 8.774999999999999
878
+ - type: precision_at_10
879
+ value: 2.3640000000000003
880
+ - type: precision_at_100
881
+ value: 0.49
882
+ - type: precision_at_1000
883
+ value: 0.094
884
+ - type: precision_at_3
885
+ value: 5.047
886
+ - type: precision_at_5
887
+ value: 3.8129999999999997
888
+ - type: recall_at_1
889
+ value: 7.04
890
+ - type: recall_at_10
891
+ value: 17.193
892
+ - type: recall_at_100
893
+ value: 33.33
894
+ - type: recall_at_1000
895
+ value: 59.134
896
+ - type: recall_at_3
897
+ value: 11.859
898
+ - type: recall_at_5
899
+ value: 14.243
900
+ - task:
901
+ type: Retrieval
902
+ dataset:
903
+ type: None
904
+ name: MTEB CQADupstackUnixRetrieval
905
+ config: default
906
+ split: test
907
+ revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
908
+ metrics:
909
+ - type: map_at_1
910
+ value: 11.381
911
+ - type: map_at_10
912
+ value: 15.676000000000002
913
+ - type: map_at_100
914
+ value: 16.448999999999998
915
+ - type: map_at_1000
916
+ value: 16.563
917
+ - type: map_at_3
918
+ value: 14.313
919
+ - type: map_at_5
920
+ value: 15.010000000000002
921
+ - type: mrr_at_1
922
+ value: 14.086000000000002
923
+ - type: mrr_at_10
924
+ value: 18.621
925
+ - type: mrr_at_100
926
+ value: 19.41
927
+ - type: mrr_at_1000
928
+ value: 19.506999999999998
929
+ - type: mrr_at_3
930
+ value: 17.149
931
+ - type: mrr_at_5
932
+ value: 17.918
933
+ - type: ndcg_at_1
934
+ value: 14.086000000000002
935
+ - type: ndcg_at_10
936
+ value: 18.647
937
+ - type: ndcg_at_100
938
+ value: 22.823
939
+ - type: ndcg_at_1000
940
+ value: 26.207
941
+ - type: ndcg_at_3
942
+ value: 15.986
943
+ - type: ndcg_at_5
944
+ value: 17.108
945
+ - type: precision_at_1
946
+ value: 14.086000000000002
947
+ - type: precision_at_10
948
+ value: 3.218
949
+ - type: precision_at_100
950
+ value: 0.585
951
+ - type: precision_at_1000
952
+ value: 0.099
953
+ - type: precision_at_3
954
+ value: 7.369000000000001
955
+ - type: precision_at_5
956
+ value: 5.187
957
+ - type: recall_at_1
958
+ value: 11.381
959
+ - type: recall_at_10
960
+ value: 25.008999999999997
961
+ - type: recall_at_100
962
+ value: 44.368
963
+ - type: recall_at_1000
964
+ value: 69.587
965
+ - type: recall_at_3
966
+ value: 17.612
967
+ - type: recall_at_5
968
+ value: 20.506
969
+ - task:
970
+ type: Retrieval
971
+ dataset:
972
+ type: None
973
+ name: MTEB CQADupstackWebmastersRetrieval
974
+ config: default
975
+ split: test
976
+ revision: 160c094312a0e1facb97e55eeddb698c0abe3571
977
+ metrics:
978
+ - type: map_at_1
979
+ value: 12.641
980
+ - type: map_at_10
981
+ value: 19.067
982
+ - type: map_at_100
983
+ value: 20.046
984
+ - type: map_at_1000
985
+ value: 20.221
986
+ - type: map_at_3
987
+ value: 17.699
988
+ - type: map_at_5
989
+ value: 18.458
990
+ - type: mrr_at_1
991
+ value: 16.008
992
+ - type: mrr_at_10
993
+ value: 22.526
994
+ - type: mrr_at_100
995
+ value: 23.307
996
+ - type: mrr_at_1000
997
+ value: 23.391000000000002
998
+ - type: mrr_at_3
999
+ value: 21.047
1000
+ - type: mrr_at_5
1001
+ value: 21.956999999999997
1002
+ - type: ndcg_at_1
1003
+ value: 16.008
1004
+ - type: ndcg_at_10
1005
+ value: 23.029
1006
+ - type: ndcg_at_100
1007
+ value: 27.533
1008
+ - type: ndcg_at_1000
1009
+ value: 31.096
1010
+ - type: ndcg_at_3
1011
+ value: 20.806
1012
+ - type: ndcg_at_5
1013
+ value: 21.859
1014
+ - type: precision_at_1
1015
+ value: 16.008
1016
+ - type: precision_at_10
1017
+ value: 4.605
1018
+ - type: precision_at_100
1019
+ value: 0.9939999999999999
1020
+ - type: precision_at_1000
1021
+ value: 0.182
1022
+ - type: precision_at_3
1023
+ value: 10.408000000000001
1024
+ - type: precision_at_5
1025
+ value: 7.470000000000001
1026
+ - type: recall_at_1
1027
+ value: 12.641
1028
+ - type: recall_at_10
1029
+ value: 30.236
1030
+ - type: recall_at_100
1031
+ value: 51.543000000000006
1032
+ - type: recall_at_1000
1033
+ value: 76.265
1034
+ - type: recall_at_3
1035
+ value: 23.677999999999997
1036
+ - type: recall_at_5
1037
+ value: 26.456000000000003
1038
+ - task:
1039
+ type: Retrieval
1040
+ dataset:
1041
+ type: None
1042
+ name: MTEB CQADupstackWordpressRetrieval
1043
+ config: default
1044
+ split: test
1045
+ revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
1046
+ metrics:
1047
+ - type: map_at_1
1048
+ value: 11.288
1049
+ - type: map_at_10
1050
+ value: 15.101
1051
+ - type: map_at_100
1052
+ value: 15.725
1053
+ - type: map_at_1000
1054
+ value: 15.840000000000002
1055
+ - type: map_at_3
1056
+ value: 13.614
1057
+ - type: map_at_5
1058
+ value: 14.394000000000002
1059
+ - type: mrr_at_1
1060
+ value: 12.753999999999998
1061
+ - type: mrr_at_10
1062
+ value: 16.665
1063
+ - type: mrr_at_100
1064
+ value: 17.288
1065
+ - type: mrr_at_1000
1066
+ value: 17.393
1067
+ - type: mrr_at_3
1068
+ value: 15.096000000000002
1069
+ - type: mrr_at_5
1070
+ value: 15.974
1071
+ - type: ndcg_at_1
1072
+ value: 12.753999999999998
1073
+ - type: ndcg_at_10
1074
+ value: 17.821
1075
+ - type: ndcg_at_100
1076
+ value: 21.544
1077
+ - type: ndcg_at_1000
1078
+ value: 24.965
1079
+ - type: ndcg_at_3
1080
+ value: 14.789
1081
+ - type: ndcg_at_5
1082
+ value: 16.163
1083
+ - type: precision_at_1
1084
+ value: 12.753999999999998
1085
+ - type: precision_at_10
1086
+ value: 2.884
1087
+ - type: precision_at_100
1088
+ value: 0.518
1089
+ - type: precision_at_1000
1090
+ value: 0.09
1091
+ - type: precision_at_3
1092
+ value: 6.346
1093
+ - type: precision_at_5
1094
+ value: 4.621
1095
+ - type: recall_at_1
1096
+ value: 11.288
1097
+ - type: recall_at_10
1098
+ value: 24.941
1099
+ - type: recall_at_100
1100
+ value: 43.339
1101
+ - type: recall_at_1000
1102
+ value: 69.813
1103
+ - type: recall_at_3
1104
+ value: 16.679
1105
+ - type: recall_at_5
1106
+ value: 19.982
1107
+ - task:
1108
+ type: Retrieval
1109
+ dataset:
1110
+ type: None
1111
+ name: MTEB ClimateFEVER
1112
+ config: default
1113
+ split: test
1114
+ revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
1115
+ metrics:
1116
+ - type: map_at_1
1117
+ value: 5.319
1118
+ - type: map_at_10
1119
+ value: 9.538
1120
+ - type: map_at_100
1121
+ value: 10.786
1122
+ - type: map_at_1000
1123
+ value: 10.979
1124
+ - type: map_at_3
1125
+ value: 7.693999999999999
1126
+ - type: map_at_5
1127
+ value: 8.623
1128
+ - type: mrr_at_1
1129
+ value: 11.922
1130
+ - type: mrr_at_10
1131
+ value: 19.683
1132
+ - type: mrr_at_100
1133
+ value: 20.881
1134
+ - type: mrr_at_1000
1135
+ value: 20.961
1136
+ - type: mrr_at_3
1137
+ value: 17.014000000000003
1138
+ - type: mrr_at_5
1139
+ value: 18.47
1140
+ - type: ndcg_at_1
1141
+ value: 11.922
1142
+ - type: ndcg_at_10
1143
+ value: 14.517
1144
+ - type: ndcg_at_100
1145
+ value: 20.541999999999998
1146
+ - type: ndcg_at_1000
1147
+ value: 24.648999999999997
1148
+ - type: ndcg_at_3
1149
+ value: 10.975
1150
+ - type: ndcg_at_5
1151
+ value: 12.276
1152
+ - type: precision_at_1
1153
+ value: 11.922
1154
+ - type: precision_at_10
1155
+ value: 4.893
1156
+ - type: precision_at_100
1157
+ value: 1.129
1158
+ - type: precision_at_1000
1159
+ value: 0.187
1160
+ - type: precision_at_3
1161
+ value: 8.382000000000001
1162
+ - type: precision_at_5
1163
+ value: 6.801
1164
+ - type: recall_at_1
1165
+ value: 5.319
1166
+ - type: recall_at_10
1167
+ value: 18.593
1168
+ - type: recall_at_100
1169
+ value: 39.957
1170
+ - type: recall_at_1000
1171
+ value: 63.748000000000005
1172
+ - type: recall_at_3
1173
+ value: 10.314
1174
+ - type: recall_at_5
1175
+ value: 13.564000000000002
1176
+ - task:
1177
+ type: Retrieval
1178
+ dataset:
1179
+ type: None
1180
+ name: MTEB DBPedia
1181
+ config: default
1182
+ split: test
1183
+ revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
1184
+ metrics:
1185
+ - type: map_at_1
1186
+ value: 3.819
1187
+ - type: map_at_10
1188
+ value: 7.771999999999999
1189
+ - type: map_at_100
1190
+ value: 10.424999999999999
1191
+ - type: map_at_1000
1192
+ value: 11.165
1193
+ - type: map_at_3
1194
+ value: 5.586
1195
+ - type: map_at_5
1196
+ value: 6.524000000000001
1197
+ - type: mrr_at_1
1198
+ value: 34.75
1199
+ - type: mrr_at_10
1200
+ value: 43.289
1201
+ - type: mrr_at_100
1202
+ value: 44.184
1203
+ - type: mrr_at_1000
1204
+ value: 44.239
1205
+ - type: mrr_at_3
1206
+ value: 40.75
1207
+ - type: mrr_at_5
1208
+ value: 42.175000000000004
1209
+ - type: ndcg_at_1
1210
+ value: 25.5
1211
+ - type: ndcg_at_10
1212
+ value: 19.994
1213
+ - type: ndcg_at_100
1214
+ value: 21.802
1215
+ - type: ndcg_at_1000
1216
+ value: 28.086
1217
+ - type: ndcg_at_3
1218
+ value: 22.279
1219
+ - type: ndcg_at_5
1220
+ value: 20.986
1221
+ - type: precision_at_1
1222
+ value: 34.75
1223
+ - type: precision_at_10
1224
+ value: 17.65
1225
+ - type: precision_at_100
1226
+ value: 5.317
1227
+ - type: precision_at_1000
1228
+ value: 1.146
1229
+ - type: precision_at_3
1230
+ value: 25.75
1231
+ - type: precision_at_5
1232
+ value: 22.400000000000002
1233
+ - type: recall_at_1
1234
+ value: 3.819
1235
+ - type: recall_at_10
1236
+ value: 11.533
1237
+ - type: recall_at_100
1238
+ value: 26.484999999999996
1239
+ - type: recall_at_1000
1240
+ value: 47.63
1241
+ - type: recall_at_3
1242
+ value: 6.268999999999999
1243
+ - type: recall_at_5
1244
+ value: 8.218
1245
+ - task:
1246
+ type: Classification
1247
+ dataset:
1248
+ type: None
1249
+ name: MTEB EmotionClassification
1250
+ config: default
1251
+ split: test
1252
+ revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
1253
+ metrics:
1254
+ - type: accuracy
1255
+ value: 43.69500000000001
1256
+ - type: f1
1257
+ value: 39.81935458907266
1258
+ - task:
1259
+ type: Retrieval
1260
+ dataset:
1261
+ type: None
1262
+ name: MTEB FEVER
1263
+ config: default
1264
+ split: test
1265
+ revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
1266
+ metrics:
1267
+ - type: map_at_1
1268
+ value: 10.544
1269
+ - type: map_at_10
1270
+ value: 16.105
1271
+ - type: map_at_100
1272
+ value: 16.91
1273
+ - type: map_at_1000
1274
+ value: 16.993
1275
+ - type: map_at_3
1276
+ value: 14.273
1277
+ - type: map_at_5
1278
+ value: 15.259
1279
+ - type: mrr_at_1
1280
+ value: 11.206000000000001
1281
+ - type: mrr_at_10
1282
+ value: 17.129
1283
+ - type: mrr_at_100
1284
+ value: 17.955
1285
+ - type: mrr_at_1000
1286
+ value: 18.032999999999998
1287
+ - type: mrr_at_3
1288
+ value: 15.214
1289
+ - type: mrr_at_5
1290
+ value: 16.249
1291
+ - type: ndcg_at_1
1292
+ value: 11.206000000000001
1293
+ - type: ndcg_at_10
1294
+ value: 19.546
1295
+ - type: ndcg_at_100
1296
+ value: 23.934
1297
+ - type: ndcg_at_1000
1298
+ value: 26.356
1299
+ - type: ndcg_at_3
1300
+ value: 15.706999999999999
1301
+ - type: ndcg_at_5
1302
+ value: 17.488999999999997
1303
+ - type: precision_at_1
1304
+ value: 11.206000000000001
1305
+ - type: precision_at_10
1306
+ value: 3.195
1307
+ - type: precision_at_100
1308
+ value: 0.557
1309
+ - type: precision_at_1000
1310
+ value: 0.078
1311
+ - type: precision_at_3
1312
+ value: 6.7860000000000005
1313
+ - type: precision_at_5
1314
+ value: 4.997999999999999
1315
+ - type: recall_at_1
1316
+ value: 10.544
1317
+ - type: recall_at_10
1318
+ value: 29.421999999999997
1319
+ - type: recall_at_100
1320
+ value: 50.54
1321
+ - type: recall_at_1000
1322
+ value: 69.53200000000001
1323
+ - type: recall_at_3
1324
+ value: 18.901
1325
+ - type: recall_at_5
1326
+ value: 23.183999999999997
1327
+ - task:
1328
+ type: Retrieval
1329
+ dataset:
1330
+ type: None
1331
+ name: MTEB FiQA2018
1332
+ config: default
1333
+ split: test
1334
+ revision: 27a168819829fe9bcd655c2df245fb19452e8e06
1335
+ metrics:
1336
+ - type: map_at_1
1337
+ value: 5.688
1338
+ - type: map_at_10
1339
+ value: 9.454
1340
+ - type: map_at_100
1341
+ value: 10.459
1342
+ - type: map_at_1000
1343
+ value: 10.645
1344
+ - type: map_at_3
1345
+ value: 7.914000000000001
1346
+ - type: map_at_5
1347
+ value: 8.622
1348
+ - type: mrr_at_1
1349
+ value: 11.42
1350
+ - type: mrr_at_10
1351
+ value: 16.608
1352
+ - type: mrr_at_100
1353
+ value: 17.566000000000003
1354
+ - type: mrr_at_1000
1355
+ value: 17.675
1356
+ - type: mrr_at_3
1357
+ value: 14.712
1358
+ - type: mrr_at_5
1359
+ value: 15.638
1360
+ - type: ndcg_at_1
1361
+ value: 11.42
1362
+ - type: ndcg_at_10
1363
+ value: 13.293
1364
+ - type: ndcg_at_100
1365
+ value: 18.289
1366
+ - type: ndcg_at_1000
1367
+ value: 22.781000000000002
1368
+ - type: ndcg_at_3
1369
+ value: 10.835
1370
+ - type: ndcg_at_5
1371
+ value: 11.576
1372
+ - type: precision_at_1
1373
+ value: 11.42
1374
+ - type: precision_at_10
1375
+ value: 3.997
1376
+ - type: precision_at_100
1377
+ value: 0.897
1378
+ - type: precision_at_1000
1379
+ value: 0.167
1380
+ - type: precision_at_3
1381
+ value: 7.356
1382
+ - type: precision_at_5
1383
+ value: 5.772
1384
+ - type: recall_at_1
1385
+ value: 5.688
1386
+ - type: recall_at_10
1387
+ value: 17.544
1388
+ - type: recall_at_100
1389
+ value: 37.358999999999995
1390
+ - type: recall_at_1000
1391
+ value: 65.735
1392
+ - type: recall_at_3
1393
+ value: 9.987
1394
+ - type: recall_at_5
1395
+ value: 12.337
1396
+ - task:
1397
+ type: Retrieval
1398
+ dataset:
1399
+ type: None
1400
+ name: MTEB HotpotQA
1401
+ config: default
1402
+ split: test
1403
+ revision: ab518f4d6fcca38d87c25209f94beba119d02014
1404
+ metrics:
1405
+ - type: map_at_1
1406
+ value: 13.248
1407
+ - type: map_at_10
1408
+ value: 18.584
1409
+ - type: map_at_100
1410
+ value: 19.348000000000003
1411
+ - type: map_at_1000
1412
+ value: 19.457
1413
+ - type: map_at_3
1414
+ value: 16.962
1415
+ - type: map_at_5
1416
+ value: 17.862000000000002
1417
+ - type: mrr_at_1
1418
+ value: 26.496
1419
+ - type: mrr_at_10
1420
+ value: 32.580999999999996
1421
+ - type: mrr_at_100
1422
+ value: 33.314
1423
+ - type: mrr_at_1000
1424
+ value: 33.387
1425
+ - type: mrr_at_3
1426
+ value: 30.808000000000003
1427
+ - type: mrr_at_5
1428
+ value: 31.805
1429
+ - type: ndcg_at_1
1430
+ value: 26.496
1431
+ - type: ndcg_at_10
1432
+ value: 24.198
1433
+ - type: ndcg_at_100
1434
+ value: 28.017999999999997
1435
+ - type: ndcg_at_1000
1436
+ value: 30.839
1437
+ - type: ndcg_at_3
1438
+ value: 21.002000000000002
1439
+ - type: ndcg_at_5
1440
+ value: 22.547
1441
+ - type: precision_at_1
1442
+ value: 26.496
1443
+ - type: precision_at_10
1444
+ value: 5.415
1445
+ - type: precision_at_100
1446
+ value: 0.8500000000000001
1447
+ - type: precision_at_1000
1448
+ value: 0.123
1449
+ - type: precision_at_3
1450
+ value: 13.234000000000002
1451
+ - type: precision_at_5
1452
+ value: 9.164
1453
+ - type: recall_at_1
1454
+ value: 13.248
1455
+ - type: recall_at_10
1456
+ value: 27.076
1457
+ - type: recall_at_100
1458
+ value: 42.512
1459
+ - type: recall_at_1000
1460
+ value: 61.41799999999999
1461
+ - type: recall_at_3
1462
+ value: 19.851
1463
+ - type: recall_at_5
1464
+ value: 22.91
1465
+ - task:
1466
+ type: Classification
1467
+ dataset:
1468
+ type: None
1469
+ name: MTEB ImdbClassification
1470
+ config: default
1471
+ split: test
1472
+ revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
1473
+ metrics:
1474
+ - type: accuracy
1475
+ value: 63.98560000000001
1476
+ - type: ap
1477
+ value: 59.217561950701445
1478
+ - type: f1
1479
+ value: 63.818409911217046
1480
+ - task:
1481
+ type: Retrieval
1482
+ dataset:
1483
+ type: None
1484
+ name: MTEB MSMARCO
1485
+ config: default
1486
+ split: dev
1487
+ revision: c5a29a104738b98a9e76336939199e264163d4a0
1488
+ metrics:
1489
+ - type: map_at_1
1490
+ value: 5.179
1491
+ - type: map_at_10
1492
+ value: 9.055
1493
+ - type: map_at_100
1494
+ value: 9.814
1495
+ - type: map_at_1000
1496
+ value: 9.911
1497
+ - type: map_at_3
1498
+ value: 7.631
1499
+ - type: map_at_5
1500
+ value: 8.415000000000001
1501
+ - type: mrr_at_1
1502
+ value: 5.3580000000000005
1503
+ - type: mrr_at_10
1504
+ value: 9.302000000000001
1505
+ - type: mrr_at_100
1506
+ value: 10.075000000000001
1507
+ - type: mrr_at_1000
1508
+ value: 10.169
1509
+ - type: mrr_at_3
1510
+ value: 7.856000000000001
1511
+ - type: mrr_at_5
1512
+ value: 8.654
1513
+ - type: ndcg_at_1
1514
+ value: 5.33
1515
+ - type: ndcg_at_10
1516
+ value: 11.491
1517
+ - type: ndcg_at_100
1518
+ value: 15.735
1519
+ - type: ndcg_at_1000
1520
+ value: 18.721
1521
+ - type: ndcg_at_3
1522
+ value: 8.522
1523
+ - type: ndcg_at_5
1524
+ value: 9.943
1525
+ - type: precision_at_1
1526
+ value: 5.33
1527
+ - type: precision_at_10
1528
+ value: 1.983
1529
+ - type: precision_at_100
1530
+ value: 0.42
1531
+ - type: precision_at_1000
1532
+ value: 0.068
1533
+ - type: precision_at_3
1534
+ value: 3.763
1535
+ - type: precision_at_5
1536
+ value: 2.9770000000000003
1537
+ - type: recall_at_1
1538
+ value: 5.179
1539
+ - type: recall_at_10
1540
+ value: 19.069
1541
+ - type: recall_at_100
1542
+ value: 39.946
1543
+ - type: recall_at_1000
1544
+ value: 64.031
1545
+ - type: recall_at_3
1546
+ value: 10.91
1547
+ - type: recall_at_5
1548
+ value: 14.334
1549
+ - task:
1550
+ type: Classification
1551
+ dataset:
1552
+ type: None
1553
+ name: MTEB MTOPDomainClassification (en)
1554
+ config: en
1555
+ split: test
1556
+ revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
1557
+ metrics:
1558
+ - type: accuracy
1559
+ value: 89.25444596443229
1560
+ - type: f1
1561
+ value: 88.34114464691379
1562
+ - task:
1563
+ type: Classification
1564
+ dataset:
1565
+ type: None
1566
+ name: MTEB MTOPIntentClassification (en)
1567
+ config: en
1568
+ split: test
1569
+ revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1570
+ metrics:
1571
+ - type: accuracy
1572
+ value: 59.3251253989968
1573
+ - type: f1
1574
+ value: 39.879870396124964
1575
+ - task:
1576
+ type: Classification
1577
+ dataset:
1578
+ type: None
1579
+ name: MTEB MassiveIntentClassification (en)
1580
+ config: en
1581
+ split: test
1582
+ revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
1583
+ metrics:
1584
+ - type: accuracy
1585
+ value: 61.90316072629455
1586
+ - type: f1
1587
+ value: 59.6419867903448
1588
+ - task:
1589
+ type: Classification
1590
+ dataset:
1591
+ type: None
1592
+ name: MTEB MassiveScenarioClassification (en)
1593
+ config: en
1594
+ split: test
1595
+ revision: 7d571f92784cd94a019292a1f45445077d0ef634
1596
+ metrics:
1597
+ - type: accuracy
1598
+ value: 68.5474108944183
1599
+ - type: f1
1600
+ value: 67.13260105586494
1601
+ - task:
1602
+ type: Clustering
1603
+ dataset:
1604
+ type: None
1605
+ name: MTEB MedrxivClusteringP2P
1606
+ config: default
1607
+ split: test
1608
+ revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
1609
+ metrics:
1610
+ - type: v_measure
1611
+ value: 27.08360278577924
1612
+ - task:
1613
+ type: Clustering
1614
+ dataset:
1615
+ type: None
1616
+ name: MTEB MedrxivClusteringS2S
1617
+ config: default
1618
+ split: test
1619
+ revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
1620
+ metrics:
1621
+ - type: v_measure
1622
+ value: 23.539985814012603
1623
+ - task:
1624
+ type: Reranking
1625
+ dataset:
1626
+ type: None
1627
+ name: MTEB MindSmallReranking
1628
+ config: default
1629
+ split: test
1630
+ revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
1631
+ metrics:
1632
+ - type: map
1633
+ value: 28.52217790319968
1634
+ - type: mrr
1635
+ value: 29.375037759331086
1636
+ - task:
1637
+ type: Retrieval
1638
+ dataset:
1639
+ type: None
1640
+ name: MTEB NFCorpus
1641
+ config: default
1642
+ split: test
1643
+ revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
1644
+ metrics:
1645
+ - type: map_at_1
1646
+ value: 3.202
1647
+ - type: map_at_10
1648
+ value: 6.216
1649
+ - type: map_at_100
1650
+ value: 7.902000000000001
1651
+ - type: map_at_1000
1652
+ value: 9.114
1653
+ - type: map_at_3
1654
+ value: 4.752
1655
+ - type: map_at_5
1656
+ value: 5.414
1657
+ - type: mrr_at_1
1658
+ value: 31.269000000000002
1659
+ - type: mrr_at_10
1660
+ value: 39.649
1661
+ - type: mrr_at_100
1662
+ value: 40.261
1663
+ - type: mrr_at_1000
1664
+ value: 40.338
1665
+ - type: mrr_at_3
1666
+ value: 37.049
1667
+ - type: mrr_at_5
1668
+ value: 38.643
1669
+ - type: ndcg_at_1
1670
+ value: 29.412
1671
+ - type: ndcg_at_10
1672
+ value: 21.224
1673
+ - type: ndcg_at_100
1674
+ value: 19.897000000000002
1675
+ - type: ndcg_at_1000
1676
+ value: 29.53
1677
+ - type: ndcg_at_3
1678
+ value: 24.635
1679
+ - type: ndcg_at_5
1680
+ value: 23.114
1681
+ - type: precision_at_1
1682
+ value: 31.269000000000002
1683
+ - type: precision_at_10
1684
+ value: 15.697
1685
+ - type: precision_at_100
1686
+ value: 5.842
1687
+ - type: precision_at_1000
1688
+ value: 1.8880000000000001
1689
+ - type: precision_at_3
1690
+ value: 23.013
1691
+ - type: precision_at_5
1692
+ value: 19.628
1693
+ - type: recall_at_1
1694
+ value: 3.202
1695
+ - type: recall_at_10
1696
+ value: 9.889000000000001
1697
+ - type: recall_at_100
1698
+ value: 21.366
1699
+ - type: recall_at_1000
1700
+ value: 56.267999999999994
1701
+ - type: recall_at_3
1702
+ value: 5.7459999999999996
1703
+ - type: recall_at_5
1704
+ value: 7.473000000000001
1705
+ - task:
1706
+ type: Retrieval
1707
+ dataset:
1708
+ type: None
1709
+ name: MTEB NQ
1710
+ config: default
1711
+ split: test
1712
+ revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
1713
+ metrics:
1714
+ - type: map_at_1
1715
+ value: 7.892
1716
+ - type: map_at_10
1717
+ value: 13.358999999999998
1718
+ - type: map_at_100
1719
+ value: 14.396
1720
+ - type: map_at_1000
1721
+ value: 14.499
1722
+ - type: map_at_3
1723
+ value: 11.335
1724
+ - type: map_at_5
1725
+ value: 12.375
1726
+ - type: mrr_at_1
1727
+ value: 8.98
1728
+ - type: mrr_at_10
1729
+ value: 14.762
1730
+ - type: mrr_at_100
1731
+ value: 15.787
1732
+ - type: mrr_at_1000
1733
+ value: 15.873000000000001
1734
+ - type: mrr_at_3
1735
+ value: 12.65
1736
+ - type: mrr_at_5
1737
+ value: 13.761000000000001
1738
+ - type: ndcg_at_1
1739
+ value: 8.98
1740
+ - type: ndcg_at_10
1741
+ value: 17.013
1742
+ - type: ndcg_at_100
1743
+ value: 22.582
1744
+ - type: ndcg_at_1000
1745
+ value: 25.546000000000003
1746
+ - type: ndcg_at_3
1747
+ value: 12.765
1748
+ - type: ndcg_at_5
1749
+ value: 14.662
1750
+ - type: precision_at_1
1751
+ value: 8.98
1752
+ - type: precision_at_10
1753
+ value: 3.152
1754
+ - type: precision_at_100
1755
+ value: 0.636
1756
+ - type: precision_at_1000
1757
+ value: 0.092
1758
+ - type: precision_at_3
1759
+ value: 5.997
1760
+ - type: precision_at_5
1761
+ value: 4.652
1762
+ - type: recall_at_1
1763
+ value: 7.892
1764
+ - type: recall_at_10
1765
+ value: 27.081
1766
+ - type: recall_at_100
1767
+ value: 53.36300000000001
1768
+ - type: recall_at_1000
1769
+ value: 76.419
1770
+ - type: recall_at_3
1771
+ value: 15.623999999999999
1772
+ - type: recall_at_5
1773
+ value: 20.104
1774
+ - task:
1775
+ type: Retrieval
1776
+ dataset:
1777
+ type: None
1778
+ name: MTEB QuoraRetrieval
1779
+ config: default
1780
+ split: test
1781
+ revision: None
1782
+ metrics:
1783
+ - type: map_at_1
1784
+ value: 61.224999999999994
1785
+ - type: map_at_10
1786
+ value: 73.768
1787
+ - type: map_at_100
1788
+ value: 74.54899999999999
1789
+ - type: map_at_1000
1790
+ value: 74.588
1791
+ - type: map_at_3
1792
+ value: 70.845
1793
+ - type: map_at_5
1794
+ value: 72.61
1795
+ - type: mrr_at_1
1796
+ value: 70.63000000000001
1797
+ - type: mrr_at_10
1798
+ value: 78.204
1799
+ - type: mrr_at_100
1800
+ value: 78.469
1801
+ - type: mrr_at_1000
1802
+ value: 78.477
1803
+ - type: mrr_at_3
1804
+ value: 76.67500000000001
1805
+ - type: mrr_at_5
1806
+ value: 77.644
1807
+ - type: ndcg_at_1
1808
+ value: 70.61
1809
+ - type: ndcg_at_10
1810
+ value: 78.586
1811
+ - type: ndcg_at_100
1812
+ value: 80.852
1813
+ - type: ndcg_at_1000
1814
+ value: 81.32000000000001
1815
+ - type: ndcg_at_3
1816
+ value: 74.902
1817
+ - type: ndcg_at_5
1818
+ value: 76.787
1819
+ - type: precision_at_1
1820
+ value: 70.61
1821
+ - type: precision_at_10
1822
+ value: 11.904
1823
+ - type: precision_at_100
1824
+ value: 1.438
1825
+ - type: precision_at_1000
1826
+ value: 0.154
1827
+ - type: precision_at_3
1828
+ value: 32.503
1829
+ - type: precision_at_5
1830
+ value: 21.526
1831
+ - type: recall_at_1
1832
+ value: 61.224999999999994
1833
+ - type: recall_at_10
1834
+ value: 87.908
1835
+ - type: recall_at_100
1836
+ value: 96.63000000000001
1837
+ - type: recall_at_1000
1838
+ value: 99.367
1839
+ - type: recall_at_3
1840
+ value: 77.358
1841
+ - type: recall_at_5
1842
+ value: 82.584
1843
+ - task:
1844
+ type: Clustering
1845
+ dataset:
1846
+ type: None
1847
+ name: MTEB RedditClustering
1848
+ config: default
1849
+ split: test
1850
+ revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
1851
+ metrics:
1852
+ - type: v_measure
1853
+ value: 33.05951893381823
1854
+ - task:
1855
+ type: Clustering
1856
+ dataset:
1857
+ type: None
1858
+ name: MTEB RedditClusteringP2P
1859
+ config: default
1860
+ split: test
1861
+ revision: 282350215ef01743dc01b456c7f5241fa8937f16
1862
+ metrics:
1863
+ - type: v_measure
1864
+ value: 42.691497046210955
1865
+ - task:
1866
+ type: Retrieval
1867
+ dataset:
1868
+ type: None
1869
+ name: MTEB SCIDOCS
1870
+ config: default
1871
+ split: test
1872
+ revision: None
1873
+ metrics:
1874
+ - type: map_at_1
1875
+ value: 2.585
1876
+ - type: map_at_10
1877
+ value: 5.988
1878
+ - type: map_at_100
1879
+ value: 7.21
1880
+ - type: map_at_1000
1881
+ value: 7.449999999999999
1882
+ - type: map_at_3
1883
+ value: 4.372
1884
+ - type: map_at_5
1885
+ value: 5.194
1886
+ - type: mrr_at_1
1887
+ value: 12.8
1888
+ - type: mrr_at_10
1889
+ value: 19.963
1890
+ - type: mrr_at_100
1891
+ value: 21.195
1892
+ - type: mrr_at_1000
1893
+ value: 21.29
1894
+ - type: mrr_at_3
1895
+ value: 17.533
1896
+ - type: mrr_at_5
1897
+ value: 18.853
1898
+ - type: ndcg_at_1
1899
+ value: 12.8
1900
+ - type: ndcg_at_10
1901
+ value: 10.874
1902
+ - type: ndcg_at_100
1903
+ value: 16.695
1904
+ - type: ndcg_at_1000
1905
+ value: 21.762999999999998
1906
+ - type: ndcg_at_3
1907
+ value: 10.209
1908
+ - type: ndcg_at_5
1909
+ value: 8.999
1910
+ - type: precision_at_1
1911
+ value: 12.8
1912
+ - type: precision_at_10
1913
+ value: 5.65
1914
+ - type: precision_at_100
1915
+ value: 1.411
1916
+ - type: precision_at_1000
1917
+ value: 0.264
1918
+ - type: precision_at_3
1919
+ value: 9.433
1920
+ - type: precision_at_5
1921
+ value: 7.88
1922
+ - type: recall_at_1
1923
+ value: 2.585
1924
+ - type: recall_at_10
1925
+ value: 11.455
1926
+ - type: recall_at_100
1927
+ value: 28.665000000000003
1928
+ - type: recall_at_1000
1929
+ value: 53.547999999999995
1930
+ - type: recall_at_3
1931
+ value: 5.748
1932
+ - type: recall_at_5
1933
+ value: 7.983
1934
+ - task:
1935
+ type: STS
1936
+ dataset:
1937
+ type: None
1938
+ name: MTEB SICK-R
1939
+ config: default
1940
+ split: test
1941
+ revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
1942
+ metrics:
1943
+ - type: cos_sim_pearson
1944
+ value: 76.47089854443493
1945
+ - type: cos_sim_spearman
1946
+ value: 67.65881641628117
1947
+ - type: euclidean_pearson
1948
+ value: 72.75220596907191
1949
+ - type: euclidean_spearman
1950
+ value: 67.65881507675402
1951
+ - type: manhattan_pearson
1952
+ value: 71.2932268352905
1953
+ - type: manhattan_spearman
1954
+ value: 66.28937203768146
1955
+ - task:
1956
+ type: STS
1957
+ dataset:
1958
+ type: None
1959
+ name: MTEB STS12
1960
+ config: default
1961
+ split: test
1962
+ revision: a0d554a64d88156834ff5ae9920b964011b16384
1963
+ metrics:
1964
+ - type: cos_sim_pearson
1965
+ value: 73.59904123111602
1966
+ - type: cos_sim_spearman
1967
+ value: 66.64191118455778
1968
+ - type: euclidean_pearson
1969
+ value: 70.031991407929
1970
+ - type: euclidean_spearman
1971
+ value: 66.64312867708462
1972
+ - type: manhattan_pearson
1973
+ value: 70.87113974670322
1974
+ - type: manhattan_spearman
1975
+ value: 67.87998624470126
1976
+ - task:
1977
+ type: STS
1978
+ dataset:
1979
+ type: None
1980
+ name: MTEB STS13
1981
+ config: default
1982
+ split: test
1983
+ revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
1984
+ metrics:
1985
+ - type: cos_sim_pearson
1986
+ value: 77.1868454480634
1987
+ - type: cos_sim_spearman
1988
+ value: 78.5663631376088
1989
+ - type: euclidean_pearson
1990
+ value: 78.1441330499307
1991
+ - type: euclidean_spearman
1992
+ value: 78.5663753212518
1993
+ - type: manhattan_pearson
1994
+ value: 78.7258747377543
1995
+ - type: manhattan_spearman
1996
+ value: 79.24251325682667
1997
+ - task:
1998
+ type: STS
1999
+ dataset:
2000
+ type: None
2001
+ name: MTEB STS14
2002
+ config: default
2003
+ split: test
2004
+ revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
2005
+ metrics:
2006
+ - type: cos_sim_pearson
2007
+ value: 77.39709143417873
2008
+ - type: cos_sim_spearman
2009
+ value: 74.33024682805708
2010
+ - type: euclidean_pearson
2011
+ value: 76.65457389990631
2012
+ - type: euclidean_spearman
2013
+ value: 74.33023713728515
2014
+ - type: manhattan_pearson
2015
+ value: 76.73342787471654
2016
+ - type: manhattan_spearman
2017
+ value: 74.74461118652161
2018
+ - task:
2019
+ type: STS
2020
+ dataset:
2021
+ type: None
2022
+ name: MTEB STS15
2023
+ config: default
2024
+ split: test
2025
+ revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
2026
+ metrics:
2027
+ - type: cos_sim_pearson
2028
+ value: 79.9395037638594
2029
+ - type: cos_sim_spearman
2030
+ value: 81.01819776486752
2031
+ - type: euclidean_pearson
2032
+ value: 81.03043241994847
2033
+ - type: euclidean_spearman
2034
+ value: 81.01819627953365
2035
+ - type: manhattan_pearson
2036
+ value: 81.68968136619384
2037
+ - type: manhattan_spearman
2038
+ value: 81.82363999592259
2039
+ - task:
2040
+ type: STS
2041
+ dataset:
2042
+ type: None
2043
+ name: MTEB STS16
2044
+ config: default
2045
+ split: test
2046
+ revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
2047
+ metrics:
2048
+ - type: cos_sim_pearson
2049
+ value: 75.243504336461
2050
+ - type: cos_sim_spearman
2051
+ value: 76.61917655422197
2052
+ - type: euclidean_pearson
2053
+ value: 76.26910712210864
2054
+ - type: euclidean_spearman
2055
+ value: 76.62000560376505
2056
+ - type: manhattan_pearson
2057
+ value: 76.91613259757325
2058
+ - type: manhattan_spearman
2059
+ value: 77.4215820608173
2060
+ - task:
2061
+ type: STS
2062
+ dataset:
2063
+ type: None
2064
+ name: MTEB STS17 (en-en)
2065
+ config: en-en
2066
+ split: test
2067
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
2068
+ metrics:
2069
+ - type: cos_sim_pearson
2070
+ value: 82.99178286054092
2071
+ - type: cos_sim_spearman
2072
+ value: 84.2361483019332
2073
+ - type: euclidean_pearson
2074
+ value: 84.30885968598922
2075
+ - type: euclidean_spearman
2076
+ value: 84.23702233300253
2077
+ - type: manhattan_pearson
2078
+ value: 84.64734537899606
2079
+ - type: manhattan_spearman
2080
+ value: 84.71355882886535
2081
+ - task:
2082
+ type: STS
2083
+ dataset:
2084
+ type: None
2085
+ name: MTEB STS22 (en)
2086
+ config: en
2087
+ split: test
2088
+ revision: eea2b4fe26a775864c896887d910b76a8098ad3f
2089
+ metrics:
2090
+ - type: cos_sim_pearson
2091
+ value: 63.18741235485141
2092
+ - type: cos_sim_spearman
2093
+ value: 60.873579764468225
2094
+ - type: euclidean_pearson
2095
+ value: 63.18427359110471
2096
+ - type: euclidean_spearman
2097
+ value: 60.873579764468225
2098
+ - type: manhattan_pearson
2099
+ value: 63.443408253414354
2100
+ - type: manhattan_spearman
2101
+ value: 61.5997912341628
2102
+ - task:
2103
+ type: STS
2104
+ dataset:
2105
+ type: None
2106
+ name: MTEB STSBenchmark
2107
+ config: default
2108
+ split: test
2109
+ revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
2110
+ metrics:
2111
+ - type: cos_sim_pearson
2112
+ value: 77.15144919426055
2113
+ - type: cos_sim_spearman
2114
+ value: 75.76050778643061
2115
+ - type: euclidean_pearson
2116
+ value: 77.30073366013343
2117
+ - type: euclidean_spearman
2118
+ value: 75.76052625455534
2119
+ - type: manhattan_pearson
2120
+ value: 77.41746598074477
2121
+ - type: manhattan_spearman
2122
+ value: 75.98770131791319
2123
+ - task:
2124
+ type: Reranking
2125
+ dataset:
2126
+ type: None
2127
+ name: MTEB SciDocsRR
2128
+ config: default
2129
+ split: test
2130
+ revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
2131
+ metrics:
2132
+ - type: map
2133
+ value: 70.66070662385174
2134
+ - type: mrr
2135
+ value: 90.05894523051387
2136
+ - task:
2137
+ type: Retrieval
2138
+ dataset:
2139
+ type: None
2140
+ name: MTEB SciFact
2141
+ config: default
2142
+ split: test
2143
+ revision: 0228b52cf27578f30900b9e5271d331663a030d7
2144
+ metrics:
2145
+ - type: map_at_1
2146
+ value: 31.139
2147
+ - type: map_at_10
2148
+ value: 38.127
2149
+ - type: map_at_100
2150
+ value: 39.216
2151
+ - type: map_at_1000
2152
+ value: 39.290000000000006
2153
+ - type: map_at_3
2154
+ value: 35.667
2155
+ - type: map_at_5
2156
+ value: 37.317
2157
+ - type: mrr_at_1
2158
+ value: 33.333
2159
+ - type: mrr_at_10
2160
+ value: 39.972
2161
+ - type: mrr_at_100
2162
+ value: 40.892
2163
+ - type: mrr_at_1000
2164
+ value: 40.955000000000005
2165
+ - type: mrr_at_3
2166
+ value: 37.889
2167
+ - type: mrr_at_5
2168
+ value: 39.222
2169
+ - type: ndcg_at_1
2170
+ value: 33.333
2171
+ - type: ndcg_at_10
2172
+ value: 42.177
2173
+ - type: ndcg_at_100
2174
+ value: 47.772999999999996
2175
+ - type: ndcg_at_1000
2176
+ value: 49.738
2177
+ - type: ndcg_at_3
2178
+ value: 37.568
2179
+ - type: ndcg_at_5
2180
+ value: 40.294999999999995
2181
+ - type: precision_at_1
2182
+ value: 33.333
2183
+ - type: precision_at_10
2184
+ value: 5.867
2185
+ - type: precision_at_100
2186
+ value: 0.903
2187
+ - type: precision_at_1000
2188
+ value: 0.107
2189
+ - type: precision_at_3
2190
+ value: 14.777999999999999
2191
+ - type: precision_at_5
2192
+ value: 10.4
2193
+ - type: recall_at_1
2194
+ value: 31.139
2195
+ - type: recall_at_10
2196
+ value: 53.056000000000004
2197
+ - type: recall_at_100
2198
+ value: 79.60000000000001
2199
+ - type: recall_at_1000
2200
+ value: 95.133
2201
+ - type: recall_at_3
2202
+ value: 40.75
2203
+ - type: recall_at_5
2204
+ value: 47.417
2205
+ - task:
2206
+ type: PairClassification
2207
+ dataset:
2208
+ type: None
2209
+ name: MTEB SprintDuplicateQuestions
2210
+ config: default
2211
+ split: test
2212
+ revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
2213
+ metrics:
2214
+ - type: cos_sim_accuracy
2215
+ value: 99.63663366336634
2216
+ - type: cos_sim_ap
2217
+ value: 87.41569381811651
2218
+ - type: cos_sim_f1
2219
+ value: 80.8154730789336
2220
+ - type: cos_sim_precision
2221
+ value: 84.66593647316539
2222
+ - type: cos_sim_recall
2223
+ value: 77.3
2224
+ - type: dot_accuracy
2225
+ value: 99.63663366336634
2226
+ - type: dot_ap
2227
+ value: 87.41569381811651
2228
+ - type: dot_f1
2229
+ value: 80.8154730789336
2230
+ - type: dot_precision
2231
+ value: 84.66593647316539
2232
+ - type: dot_recall
2233
+ value: 77.3
2234
+ - type: euclidean_accuracy
2235
+ value: 99.63663366336634
2236
+ - type: euclidean_ap
2237
+ value: 87.41569381811651
2238
+ - type: euclidean_f1
2239
+ value: 80.8154730789336
2240
+ - type: euclidean_precision
2241
+ value: 84.66593647316539
2242
+ - type: euclidean_recall
2243
+ value: 77.3
2244
+ - type: manhattan_accuracy
2245
+ value: 99.6930693069307
2246
+ - type: manhattan_ap
2247
+ value: 90.67306262109962
2248
+ - type: manhattan_f1
2249
+ value: 84.03707518022657
2250
+ - type: manhattan_precision
2251
+ value: 86.62420382165605
2252
+ - type: manhattan_recall
2253
+ value: 81.6
2254
+ - type: max_accuracy
2255
+ value: 99.6930693069307
2256
+ - type: max_ap
2257
+ value: 90.67306262109962
2258
+ - type: max_f1
2259
+ value: 84.03707518022657
2260
+ - task:
2261
+ type: Clustering
2262
+ dataset:
2263
+ type: None
2264
+ name: MTEB StackExchangeClustering
2265
+ config: default
2266
+ split: test
2267
+ revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
2268
+ metrics:
2269
+ - type: v_measure
2270
+ value: 36.46819467809413
2271
+ - task:
2272
+ type: Clustering
2273
+ dataset:
2274
+ type: None
2275
+ name: MTEB StackExchangeClusteringP2P
2276
+ config: default
2277
+ split: test
2278
+ revision: 815ca46b2622cec33ccafc3735d572c266efdb44
2279
+ metrics:
2280
+ - type: v_measure
2281
+ value: 29.142679626551587
2282
+ - task:
2283
+ type: Reranking
2284
+ dataset:
2285
+ type: None
2286
+ name: MTEB StackOverflowDupQuestions
2287
+ config: default
2288
+ split: test
2289
+ revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
2290
+ metrics:
2291
+ - type: map
2292
+ value: 43.08118718504021
2293
+ - type: mrr
2294
+ value: 43.547356442577026
2295
+ - task:
2296
+ type: Summarization
2297
+ dataset:
2298
+ type: None
2299
+ name: MTEB SummEval
2300
+ config: default
2301
+ split: test
2302
+ revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
2303
+ metrics:
2304
+ - type: cos_sim_pearson
2305
+ value: 30.26989671913281
2306
+ - type: cos_sim_spearman
2307
+ value: 30.01993799277349
2308
+ - type: dot_pearson
2309
+ value: 30.26989672303903
2310
+ - type: dot_spearman
2311
+ value: 30.03106981258351
2312
+ - task:
2313
+ type: Retrieval
2314
+ dataset:
2315
+ type: None
2316
+ name: MTEB TRECCOVID
2317
+ config: default
2318
+ split: test
2319
+ revision: None
2320
+ metrics:
2321
+ - type: map_at_1
2322
+ value: 0.133
2323
+ - type: map_at_10
2324
+ value: 0.707
2325
+ - type: map_at_100
2326
+ value: 3.759
2327
+ - type: map_at_1000
2328
+ value: 9.02
2329
+ - type: map_at_3
2330
+ value: 0.27399999999999997
2331
+ - type: map_at_5
2332
+ value: 0.4
2333
+ - type: mrr_at_1
2334
+ value: 54.0
2335
+ - type: mrr_at_10
2336
+ value: 61.147
2337
+ - type: mrr_at_100
2338
+ value: 62.076
2339
+ - type: mrr_at_1000
2340
+ value: 62.076
2341
+ - type: mrr_at_3
2342
+ value: 57.99999999999999
2343
+ - type: mrr_at_5
2344
+ value: 59.3
2345
+ - type: ndcg_at_1
2346
+ value: 44.0
2347
+ - type: ndcg_at_10
2348
+ value: 36.039
2349
+ - type: ndcg_at_100
2350
+ value: 28.122999999999998
2351
+ - type: ndcg_at_1000
2352
+ value: 25.650000000000002
2353
+ - type: ndcg_at_3
2354
+ value: 38.173
2355
+ - type: ndcg_at_5
2356
+ value: 37.35
2357
+ - type: precision_at_1
2358
+ value: 52.0
2359
+ - type: precision_at_10
2360
+ value: 39.4
2361
+ - type: precision_at_100
2362
+ value: 29.82
2363
+ - type: precision_at_1000
2364
+ value: 12.690000000000001
2365
+ - type: precision_at_3
2366
+ value: 42.0
2367
+ - type: precision_at_5
2368
+ value: 40.400000000000006
2369
+ - type: recall_at_1
2370
+ value: 0.133
2371
+ - type: recall_at_10
2372
+ value: 0.897
2373
+ - type: recall_at_100
2374
+ value: 6.336
2375
+ - type: recall_at_1000
2376
+ value: 24.990000000000002
2377
+ - type: recall_at_3
2378
+ value: 0.301
2379
+ - type: recall_at_5
2380
+ value: 0.462
2381
+ - task:
2382
+ type: Retrieval
2383
+ dataset:
2384
+ type: None
2385
+ name: MTEB Touche2020
2386
+ config: default
2387
+ split: test
2388
+ revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
2389
+ metrics:
2390
+ - type: map_at_1
2391
+ value: 2.664
2392
+ - type: map_at_10
2393
+ value: 8.95
2394
+ - type: map_at_100
2395
+ value: 14.699000000000002
2396
+ - type: map_at_1000
2397
+ value: 16.275000000000002
2398
+ - type: map_at_3
2399
+ value: 4.963
2400
+ - type: map_at_5
2401
+ value: 6.707000000000001
2402
+ - type: mrr_at_1
2403
+ value: 36.735
2404
+ - type: mrr_at_10
2405
+ value: 48.016
2406
+ - type: mrr_at_100
2407
+ value: 48.826
2408
+ - type: mrr_at_1000
2409
+ value: 48.826
2410
+ - type: mrr_at_3
2411
+ value: 44.558
2412
+ - type: mrr_at_5
2413
+ value: 46.394999999999996
2414
+ - type: ndcg_at_1
2415
+ value: 33.672999999999995
2416
+ - type: ndcg_at_10
2417
+ value: 21.981
2418
+ - type: ndcg_at_100
2419
+ value: 35.227000000000004
2420
+ - type: ndcg_at_1000
2421
+ value: 46.428999999999995
2422
+ - type: ndcg_at_3
2423
+ value: 27.496
2424
+ - type: ndcg_at_5
2425
+ value: 24.886
2426
+ - type: precision_at_1
2427
+ value: 36.735
2428
+ - type: precision_at_10
2429
+ value: 19.184
2430
+ - type: precision_at_100
2431
+ value: 7.754999999999999
2432
+ - type: precision_at_1000
2433
+ value: 1.486
2434
+ - type: precision_at_3
2435
+ value: 27.891
2436
+ - type: precision_at_5
2437
+ value: 24.898
2438
+ - type: recall_at_1
2439
+ value: 2.664
2440
+ - type: recall_at_10
2441
+ value: 13.309999999999999
2442
+ - type: recall_at_100
2443
+ value: 46.727000000000004
2444
+ - type: recall_at_1000
2445
+ value: 81.158
2446
+ - type: recall_at_3
2447
+ value: 5.872
2448
+ - type: recall_at_5
2449
+ value: 8.694
2450
+ - task:
2451
+ type: Classification
2452
+ dataset:
2453
+ type: None
2454
+ name: MTEB ToxicConversationsClassification
2455
+ config: default
2456
+ split: test
2457
+ revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
2458
+ metrics:
2459
+ - type: accuracy
2460
+ value: 69.86019999999999
2461
+ - type: ap
2462
+ value: 13.439585186117995
2463
+ - type: f1
2464
+ value: 53.53111224664294
2465
+ - task:
2466
+ type: Classification
2467
+ dataset:
2468
+ type: None
2469
+ name: MTEB TweetSentimentExtractionClassification
2470
+ config: default
2471
+ split: test
2472
+ revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
2473
+ metrics:
2474
+ - type: accuracy
2475
+ value: 53.539898132427844
2476
+ - type: f1
2477
+ value: 53.736121370681076
2478
+ - task:
2479
+ type: Clustering
2480
+ dataset:
2481
+ type: None
2482
+ name: MTEB TwentyNewsgroupsClustering
2483
+ config: default
2484
+ split: test
2485
+ revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
2486
+ metrics:
2487
+ - type: v_measure
2488
+ value: 33.790329189415395
2489
+ - task:
2490
+ type: PairClassification
2491
+ dataset:
2492
+ type: None
2493
+ name: MTEB TwitterSemEval2015
2494
+ config: default
2495
+ split: test
2496
+ revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
2497
+ metrics:
2498
+ - type: cos_sim_accuracy
2499
+ value: 83.59063002920665
2500
+ - type: cos_sim_ap
2501
+ value: 65.1646758019036
2502
+ - type: cos_sim_f1
2503
+ value: 61.95799041886746
2504
+ - type: cos_sim_precision
2505
+ value: 57.96368650884855
2506
+ - type: cos_sim_recall
2507
+ value: 66.54353562005278
2508
+ - type: dot_accuracy
2509
+ value: 83.59063002920665
2510
+ - type: dot_ap
2511
+ value: 65.1646758019036
2512
+ - type: dot_f1
2513
+ value: 61.95799041886746
2514
+ - type: dot_precision
2515
+ value: 57.96368650884855
2516
+ - type: dot_recall
2517
+ value: 66.54353562005278
2518
+ - type: euclidean_accuracy
2519
+ value: 83.59063002920665
2520
+ - type: euclidean_ap
2521
+ value: 65.1646758019036
2522
+ - type: euclidean_f1
2523
+ value: 61.95799041886746
2524
+ - type: euclidean_precision
2525
+ value: 57.96368650884855
2526
+ - type: euclidean_recall
2527
+ value: 66.54353562005278
2528
+ - type: manhattan_accuracy
2529
+ value: 83.29856350956668
2530
+ - type: manhattan_ap
2531
+ value: 63.803561536283404
2532
+ - type: manhattan_f1
2533
+ value: 60.45279383429673
2534
+ - type: manhattan_precision
2535
+ value: 55.60478511298184
2536
+ - type: manhattan_recall
2537
+ value: 66.2269129287599
2538
+ - type: max_accuracy
2539
+ value: 83.59063002920665
2540
+ - type: max_ap
2541
+ value: 65.1646758019036
2542
+ - type: max_f1
2543
+ value: 61.95799041886746
2544
+ - task:
2545
+ type: PairClassification
2546
+ dataset:
2547
+ type: None
2548
+ name: MTEB TwitterURLCorpus
2549
+ config: default
2550
+ split: test
2551
+ revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
2552
+ metrics:
2553
+ - type: cos_sim_accuracy
2554
+ value: 87.46264602010324
2555
+ - type: cos_sim_ap
2556
+ value: 82.64331601180713
2557
+ - type: cos_sim_f1
2558
+ value: 74.66489420627008
2559
+ - type: cos_sim_precision
2560
+ value: 71.73774214148868
2561
+ - type: cos_sim_recall
2562
+ value: 77.8410840776101
2563
+ - type: dot_accuracy
2564
+ value: 87.46264602010324
2565
+ - type: dot_ap
2566
+ value: 82.64331811121104
2567
+ - type: dot_f1
2568
+ value: 74.66489420627008
2569
+ - type: dot_precision
2570
+ value: 71.73774214148868
2571
+ - type: dot_recall
2572
+ value: 77.8410840776101
2573
+ - type: euclidean_accuracy
2574
+ value: 87.46264602010324
2575
+ - type: euclidean_ap
2576
+ value: 82.64331792274162
2577
+ - type: euclidean_f1
2578
+ value: 74.66489420627008
2579
+ - type: euclidean_precision
2580
+ value: 71.73774214148868
2581
+ - type: euclidean_recall
2582
+ value: 77.8410840776101
2583
+ - type: manhattan_accuracy
2584
+ value: 87.35203943027904
2585
+ - type: manhattan_ap
2586
+ value: 82.69548093072707
2587
+ - type: manhattan_f1
2588
+ value: 74.90158915293776
2589
+ - type: manhattan_precision
2590
+ value: 71.1171096345515
2591
+ - type: manhattan_recall
2592
+ value: 79.11148752694795
2593
+ - type: max_accuracy
2594
+ value: 87.46264602010324
2595
+ - type: max_ap
2596
+ value: 82.69548093072707
2597
+ - type: max_f1
2598
+ value: 74.90158915293776
2599
+ ---