twadada commited on
Commit
d173fd8
·
verified ·
1 Parent(s): c95b601

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: fasttext_main_lower
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: 72.92537313432837
18
+ - type: ap
19
+ value: 35.92406337485786
20
+ - type: f1
21
+ value: 67.02887091461996
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: 63.944849999999995
33
+ - type: ap
34
+ value: 59.63729279839117
35
+ - type: f1
36
+ value: 63.22827966847257
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: 31.663999999999998
48
+ - type: f1
49
+ value: 31.01142901535539
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: 14.651
61
+ - type: map_at_10
62
+ value: 24.84
63
+ - type: map_at_100
64
+ value: 25.907999999999998
65
+ - type: map_at_1000
66
+ value: 25.980999999999998
67
+ - type: map_at_3
68
+ value: 21.349
69
+ - type: map_at_5
70
+ value: 23.476
71
+ - type: mrr_at_1
72
+ value: 15.007000000000001
73
+ - type: mrr_at_10
74
+ value: 24.975
75
+ - type: mrr_at_100
76
+ value: 26.043
77
+ - type: mrr_at_1000
78
+ value: 26.116
79
+ - type: mrr_at_3
80
+ value: 21.55
81
+ - type: mrr_at_5
82
+ value: 23.624000000000002
83
+ - type: ndcg_at_1
84
+ value: 14.651
85
+ - type: ndcg_at_10
86
+ value: 30.675
87
+ - type: ndcg_at_100
88
+ value: 36.162
89
+ - type: ndcg_at_1000
90
+ value: 38.214
91
+ - type: ndcg_at_3
92
+ value: 23.571
93
+ - type: ndcg_at_5
94
+ value: 27.406000000000002
95
+ - type: precision_at_1
96
+ value: 14.651
97
+ - type: precision_at_10
98
+ value: 4.936
99
+ - type: precision_at_100
100
+ value: 0.757
101
+ - type: precision_at_1000
102
+ value: 0.092
103
+ - type: precision_at_3
104
+ value: 10.005
105
+ - type: precision_at_5
106
+ value: 7.866
107
+ - type: recall_at_1
108
+ value: 14.651
109
+ - type: recall_at_10
110
+ value: 49.36
111
+ - type: recall_at_100
112
+ value: 75.676
113
+ - type: recall_at_1000
114
+ value: 92.105
115
+ - type: recall_at_3
116
+ value: 30.014000000000003
117
+ - type: recall_at_5
118
+ value: 39.330999999999996
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: 35.330404041952
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: 28.88645728041347
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: 50.148759855706025
152
+ - type: mrr
153
+ value: 63.64430813876797
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: 47.2456819755334
165
+ - type: cos_sim_spearman
166
+ value: 56.87539232993938
167
+ - type: euclidean_pearson
168
+ value: 51.27139431629815
169
+ - type: euclidean_spearman
170
+ value: 56.87539232993938
171
+ - type: manhattan_pearson
172
+ value: 54.61352629478075
173
+ - type: manhattan_spearman
174
+ value: 58.84230461724967
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: 60.3474025974026
186
+ - type: f1
187
+ value: 58.61279983720927
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: 33.53819524955979
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: 26.93233785618298
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: 16.328
221
+ - type: map_at_10
222
+ value: 22.020999999999997
223
+ - type: map_at_100
224
+ value: 23.037
225
+ - type: map_at_1000
226
+ value: 23.188
227
+ - type: map_at_3
228
+ value: 20.252
229
+ - type: map_at_5
230
+ value: 21.401
231
+ - type: mrr_at_1
232
+ value: 21.316
233
+ - type: mrr_at_10
234
+ value: 26.795
235
+ - type: mrr_at_100
236
+ value: 27.626
237
+ - type: mrr_at_1000
238
+ value: 27.721
239
+ - type: mrr_at_3
240
+ value: 25.155
241
+ - type: mrr_at_5
242
+ value: 26.299
243
+ - type: ndcg_at_1
244
+ value: 21.316
245
+ - type: ndcg_at_10
246
+ value: 25.846000000000004
247
+ - type: ndcg_at_100
248
+ value: 30.654999999999998
249
+ - type: ndcg_at_1000
250
+ value: 34.049
251
+ - type: ndcg_at_3
252
+ value: 23.247
253
+ - type: ndcg_at_5
254
+ value: 24.745
255
+ - type: precision_at_1
256
+ value: 21.316
257
+ - type: precision_at_10
258
+ value: 4.95
259
+ - type: precision_at_100
260
+ value: 0.9339999999999999
261
+ - type: precision_at_1000
262
+ value: 0.152
263
+ - type: precision_at_3
264
+ value: 11.540000000000001
265
+ - type: precision_at_5
266
+ value: 8.469
267
+ - type: recall_at_1
268
+ value: 16.328
269
+ - type: recall_at_10
270
+ value: 32.345
271
+ - type: recall_at_100
272
+ value: 54.24099999999999
273
+ - type: recall_at_1000
274
+ value: 77.729
275
+ - type: recall_at_3
276
+ value: 24.11
277
+ - type: recall_at_5
278
+ value: 28.559
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: 13.532
290
+ - type: map_at_10
291
+ value: 18.482000000000003
292
+ - type: map_at_100
293
+ value: 19.279
294
+ - type: map_at_1000
295
+ value: 19.39
296
+ - type: map_at_3
297
+ value: 16.875
298
+ - type: map_at_5
299
+ value: 17.83
300
+ - type: mrr_at_1
301
+ value: 17.516000000000002
302
+ - type: mrr_at_10
303
+ value: 22.781000000000002
304
+ - type: mrr_at_100
305
+ value: 23.439
306
+ - type: mrr_at_1000
307
+ value: 23.513
308
+ - type: mrr_at_3
309
+ value: 21.04
310
+ - type: mrr_at_5
311
+ value: 22.142
312
+ - type: ndcg_at_1
313
+ value: 17.516000000000002
314
+ - type: ndcg_at_10
315
+ value: 21.954
316
+ - type: ndcg_at_100
317
+ value: 25.662000000000003
318
+ - type: ndcg_at_1000
319
+ value: 28.519
320
+ - type: ndcg_at_3
321
+ value: 19.262999999999998
322
+ - type: ndcg_at_5
323
+ value: 20.676
324
+ - type: precision_at_1
325
+ value: 17.516000000000002
326
+ - type: precision_at_10
327
+ value: 4.274
328
+ - type: precision_at_100
329
+ value: 0.775
330
+ - type: precision_at_1000
331
+ value: 0.124
332
+ - type: precision_at_3
333
+ value: 9.447999999999999
334
+ - type: precision_at_5
335
+ value: 7.031999999999999
336
+ - type: recall_at_1
337
+ value: 13.532
338
+ - type: recall_at_10
339
+ value: 27.967
340
+ - type: recall_at_100
341
+ value: 44.232
342
+ - type: recall_at_1000
343
+ value: 64.457
344
+ - type: recall_at_3
345
+ value: 20.454
346
+ - type: recall_at_5
347
+ value: 24.022
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: 18.844
359
+ - type: map_at_10
360
+ value: 25.446
361
+ - type: map_at_100
362
+ value: 26.412999999999997
363
+ - type: map_at_1000
364
+ value: 26.508
365
+ - type: map_at_3
366
+ value: 23.354
367
+ - type: map_at_5
368
+ value: 24.531
369
+ - type: mrr_at_1
370
+ value: 21.755
371
+ - type: mrr_at_10
372
+ value: 28.182000000000002
373
+ - type: mrr_at_100
374
+ value: 29.096
375
+ - type: mrr_at_1000
376
+ value: 29.168
377
+ - type: mrr_at_3
378
+ value: 26.155
379
+ - type: mrr_at_5
380
+ value: 27.349
381
+ - type: ndcg_at_1
382
+ value: 21.755
383
+ - type: ndcg_at_10
384
+ value: 29.421999999999997
385
+ - type: ndcg_at_100
386
+ value: 34.215
387
+ - type: ndcg_at_1000
388
+ value: 36.757
389
+ - type: ndcg_at_3
390
+ value: 25.374999999999996
391
+ - type: ndcg_at_5
392
+ value: 27.348
393
+ - type: precision_at_1
394
+ value: 21.755
395
+ - type: precision_at_10
396
+ value: 4.871
397
+ - type: precision_at_100
398
+ value: 0.788
399
+ - type: precision_at_1000
400
+ value: 0.108
401
+ - type: precision_at_3
402
+ value: 11.285
403
+ - type: precision_at_5
404
+ value: 8.025
405
+ - type: recall_at_1
406
+ value: 18.844
407
+ - type: recall_at_10
408
+ value: 38.932
409
+ - type: recall_at_100
410
+ value: 60.587
411
+ - type: recall_at_1000
412
+ value: 79.53099999999999
413
+ - type: recall_at_3
414
+ value: 28.072999999999997
415
+ - type: recall_at_5
416
+ value: 32.885
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: 7.228999999999999
428
+ - type: map_at_10
429
+ value: 10.242999999999999
430
+ - type: map_at_100
431
+ value: 10.766
432
+ - type: map_at_1000
433
+ value: 10.864
434
+ - type: map_at_3
435
+ value: 9.231
436
+ - type: map_at_5
437
+ value: 9.782
438
+ - type: mrr_at_1
439
+ value: 7.91
440
+ - type: mrr_at_10
441
+ value: 11.044
442
+ - type: mrr_at_100
443
+ value: 11.600000000000001
444
+ - type: mrr_at_1000
445
+ value: 11.697000000000001
446
+ - type: mrr_at_3
447
+ value: 10.019
448
+ - type: mrr_at_5
449
+ value: 10.584
450
+ - type: ndcg_at_1
451
+ value: 7.91
452
+ - type: ndcg_at_10
453
+ value: 12.149000000000001
454
+ - type: ndcg_at_100
455
+ value: 15.177
456
+ - type: ndcg_at_1000
457
+ value: 18.240000000000002
458
+ - type: ndcg_at_3
459
+ value: 10.097000000000001
460
+ - type: ndcg_at_5
461
+ value: 11.058
462
+ - type: precision_at_1
463
+ value: 7.91
464
+ - type: precision_at_10
465
+ value: 1.966
466
+ - type: precision_at_100
467
+ value: 0.376
468
+ - type: precision_at_1000
469
+ value: 0.067
470
+ - type: precision_at_3
471
+ value: 4.331
472
+ - type: precision_at_5
473
+ value: 3.1189999999999998
474
+ - type: recall_at_1
475
+ value: 7.228999999999999
476
+ - type: recall_at_10
477
+ value: 17.360999999999997
478
+ - type: recall_at_100
479
+ value: 31.967000000000002
480
+ - type: recall_at_1000
481
+ value: 56.284
482
+ - type: recall_at_3
483
+ value: 11.692
484
+ - type: recall_at_5
485
+ value: 14.084
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: 3.666
497
+ - type: map_at_10
498
+ value: 5.902
499
+ - type: map_at_100
500
+ value: 6.436
501
+ - type: map_at_1000
502
+ value: 6.529
503
+ - type: map_at_3
504
+ value: 5.0729999999999995
505
+ - type: map_at_5
506
+ value: 5.466
507
+ - type: mrr_at_1
508
+ value: 4.726
509
+ - type: mrr_at_10
510
+ value: 7.59
511
+ - type: mrr_at_100
512
+ value: 8.190999999999999
513
+ - type: mrr_at_1000
514
+ value: 8.275
515
+ - type: mrr_at_3
516
+ value: 6.426
517
+ - type: mrr_at_5
518
+ value: 6.973
519
+ - type: ndcg_at_1
520
+ value: 4.726
521
+ - type: ndcg_at_10
522
+ value: 7.707999999999999
523
+ - type: ndcg_at_100
524
+ value: 10.688
525
+ - type: ndcg_at_1000
526
+ value: 13.5
527
+ - type: ndcg_at_3
528
+ value: 5.865
529
+ - type: ndcg_at_5
530
+ value: 6.58
531
+ - type: precision_at_1
532
+ value: 4.726
533
+ - type: precision_at_10
534
+ value: 1.592
535
+ - type: precision_at_100
536
+ value: 0.356
537
+ - type: precision_at_1000
538
+ value: 0.06899999999999999
539
+ - type: precision_at_3
540
+ value: 2.861
541
+ - type: precision_at_5
542
+ value: 2.189
543
+ - type: recall_at_1
544
+ value: 3.666
545
+ - type: recall_at_10
546
+ value: 11.700000000000001
547
+ - type: recall_at_100
548
+ value: 25.474000000000004
549
+ - type: recall_at_1000
550
+ value: 46.483000000000004
551
+ - type: recall_at_3
552
+ value: 6.749
553
+ - type: recall_at_5
554
+ value: 8.461
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: 12.57
566
+ - type: map_at_10
567
+ value: 16.923
568
+ - type: map_at_100
569
+ value: 17.78
570
+ - type: map_at_1000
571
+ value: 17.909
572
+ - type: map_at_3
573
+ value: 15.143
574
+ - type: map_at_5
575
+ value: 16.145
576
+ - type: mrr_at_1
577
+ value: 15.303
578
+ - type: mrr_at_10
579
+ value: 20.379
580
+ - type: mrr_at_100
581
+ value: 21.169
582
+ - type: mrr_at_1000
583
+ value: 21.257
584
+ - type: mrr_at_3
585
+ value: 18.479
586
+ - type: mrr_at_5
587
+ value: 19.548
588
+ - type: ndcg_at_1
589
+ value: 15.303
590
+ - type: ndcg_at_10
591
+ value: 20.308999999999997
592
+ - type: ndcg_at_100
593
+ value: 24.740000000000002
594
+ - type: ndcg_at_1000
595
+ value: 28.031
596
+ - type: ndcg_at_3
597
+ value: 17.03
598
+ - type: ndcg_at_5
599
+ value: 18.614
600
+ - type: precision_at_1
601
+ value: 15.303
602
+ - type: precision_at_10
603
+ value: 3.821
604
+ - type: precision_at_100
605
+ value: 0.741
606
+ - type: precision_at_1000
607
+ value: 0.12
608
+ - type: precision_at_3
609
+ value: 7.988
610
+ - type: precision_at_5
611
+ value: 5.987
612
+ - type: recall_at_1
613
+ value: 12.57
614
+ - type: recall_at_10
615
+ value: 27.267000000000003
616
+ - type: recall_at_100
617
+ value: 46.995
618
+ - type: recall_at_1000
619
+ value: 70.743
620
+ - type: recall_at_3
621
+ value: 18.13
622
+ - type: recall_at_5
623
+ value: 22.16
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: 8.965
635
+ - type: map_at_10
636
+ value: 11.955
637
+ - type: map_at_100
638
+ value: 12.82
639
+ - type: map_at_1000
640
+ value: 12.937999999999999
641
+ - type: map_at_3
642
+ value: 10.545
643
+ - type: map_at_5
644
+ value: 11.39
645
+ - type: mrr_at_1
646
+ value: 11.073
647
+ - type: mrr_at_10
648
+ value: 14.684
649
+ - type: mrr_at_100
650
+ value: 15.487
651
+ - type: mrr_at_1000
652
+ value: 15.583
653
+ - type: mrr_at_3
654
+ value: 12.995000000000001
655
+ - type: mrr_at_5
656
+ value: 14.022000000000002
657
+ - type: ndcg_at_1
658
+ value: 11.073
659
+ - type: ndcg_at_10
660
+ value: 14.511
661
+ - type: ndcg_at_100
662
+ value: 19.187
663
+ - type: ndcg_at_1000
664
+ value: 22.643
665
+ - type: ndcg_at_3
666
+ value: 11.736
667
+ - type: ndcg_at_5
668
+ value: 13.184000000000001
669
+ - type: precision_at_1
670
+ value: 11.073
671
+ - type: precision_at_10
672
+ value: 2.705
673
+ - type: precision_at_100
674
+ value: 0.614
675
+ - type: precision_at_1000
676
+ value: 0.109
677
+ - type: precision_at_3
678
+ value: 5.4030000000000005
679
+ - type: precision_at_5
680
+ value: 4.224
681
+ - type: recall_at_1
682
+ value: 8.965
683
+ - type: recall_at_10
684
+ value: 19.739
685
+ - type: recall_at_100
686
+ value: 41.118
687
+ - type: recall_at_1000
688
+ value: 66.338
689
+ - type: recall_at_3
690
+ value: 12.456
691
+ - type: recall_at_5
692
+ value: 15.921
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: 10.108083333333333
704
+ - type: map_at_10
705
+ value: 13.991999999999999
706
+ - type: map_at_100
707
+ value: 14.732333333333333
708
+ - type: map_at_1000
709
+ value: 14.844750000000001
710
+ - type: map_at_3
711
+ value: 12.643666666666666
712
+ - type: map_at_5
713
+ value: 13.403166666666666
714
+ - type: mrr_at_1
715
+ value: 12.410499999999999
716
+ - type: mrr_at_10
717
+ value: 16.612333333333332
718
+ - type: mrr_at_100
719
+ value: 17.314500000000002
720
+ - type: mrr_at_1000
721
+ value: 17.400916666666667
722
+ - type: mrr_at_3
723
+ value: 15.176250000000003
724
+ - type: mrr_at_5
725
+ value: 15.996083333333337
726
+ - type: ndcg_at_1
727
+ value: 12.410499999999999
728
+ - type: ndcg_at_10
729
+ value: 16.770000000000003
730
+ - type: ndcg_at_100
731
+ value: 20.619166666666665
732
+ - type: ndcg_at_1000
733
+ value: 23.642416666666666
734
+ - type: ndcg_at_3
735
+ value: 14.258999999999997
736
+ - type: ndcg_at_5
737
+ value: 15.456583333333333
738
+ - type: precision_at_1
739
+ value: 12.410499999999999
740
+ - type: precision_at_10
741
+ value: 3.072416666666667
742
+ - type: precision_at_100
743
+ value: 0.6025833333333332
744
+ - type: precision_at_1000
745
+ value: 0.10208333333333332
746
+ - type: precision_at_3
747
+ value: 6.697916666666666
748
+ - type: precision_at_5
749
+ value: 4.908416666666667
750
+ - type: recall_at_1
751
+ value: 10.108083333333333
752
+ - type: recall_at_10
753
+ value: 22.638333333333332
754
+ - type: recall_at_100
755
+ value: 40.4035
756
+ - type: recall_at_1000
757
+ value: 62.729666666666674
758
+ - type: recall_at_3
759
+ value: 15.552249999999997
760
+ - type: recall_at_5
761
+ value: 18.653
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: 6.938999999999999
773
+ - type: map_at_10
774
+ value: 10.834000000000001
775
+ - type: map_at_100
776
+ value: 11.478
777
+ - type: map_at_1000
778
+ value: 11.552
779
+ - type: map_at_3
780
+ value: 9.661999999999999
781
+ - type: map_at_5
782
+ value: 10.316
783
+ - type: mrr_at_1
784
+ value: 8.436
785
+ - type: mrr_at_10
786
+ value: 12.531
787
+ - type: mrr_at_100
788
+ value: 13.165
789
+ - type: mrr_at_1000
790
+ value: 13.229
791
+ - type: mrr_at_3
792
+ value: 11.324
793
+ - type: mrr_at_5
794
+ value: 11.953
795
+ - type: ndcg_at_1
796
+ value: 8.436
797
+ - type: ndcg_at_10
798
+ value: 13.264999999999999
799
+ - type: ndcg_at_100
800
+ value: 16.637
801
+ - type: ndcg_at_1000
802
+ value: 18.681
803
+ - type: ndcg_at_3
804
+ value: 10.993
805
+ - type: ndcg_at_5
806
+ value: 12.033000000000001
807
+ - type: precision_at_1
808
+ value: 8.436
809
+ - type: precision_at_10
810
+ value: 2.408
811
+ - type: precision_at_100
812
+ value: 0.44600000000000006
813
+ - type: precision_at_1000
814
+ value: 0.067
815
+ - type: precision_at_3
816
+ value: 5.215
817
+ - type: precision_at_5
818
+ value: 3.804
819
+ - type: recall_at_1
820
+ value: 6.938999999999999
821
+ - type: recall_at_10
822
+ value: 19.154
823
+ - type: recall_at_100
824
+ value: 34.833
825
+ - type: recall_at_1000
826
+ value: 50.275999999999996
827
+ - type: recall_at_3
828
+ value: 12.740000000000002
829
+ - type: recall_at_5
830
+ value: 15.473999999999998
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: 4.916
842
+ - type: map_at_10
843
+ value: 7.295
844
+ - type: map_at_100
845
+ value: 7.793
846
+ - type: map_at_1000
847
+ value: 7.886
848
+ - type: map_at_3
849
+ value: 6.462
850
+ - type: map_at_5
851
+ value: 6.927
852
+ - type: mrr_at_1
853
+ value: 6.607
854
+ - type: mrr_at_10
855
+ value: 9.322999999999999
856
+ - type: mrr_at_100
857
+ value: 9.847
858
+ - type: mrr_at_1000
859
+ value: 9.932
860
+ - type: mrr_at_3
861
+ value: 8.368
862
+ - type: mrr_at_5
863
+ value: 8.905000000000001
864
+ - type: ndcg_at_1
865
+ value: 6.607
866
+ - type: ndcg_at_10
867
+ value: 9.123000000000001
868
+ - type: ndcg_at_100
869
+ value: 11.846
870
+ - type: ndcg_at_1000
871
+ value: 14.732000000000001
872
+ - type: ndcg_at_3
873
+ value: 7.5520000000000005
874
+ - type: ndcg_at_5
875
+ value: 8.272
876
+ - type: precision_at_1
877
+ value: 6.607
878
+ - type: precision_at_10
879
+ value: 1.796
880
+ - type: precision_at_100
881
+ value: 0.379
882
+ - type: precision_at_1000
883
+ value: 0.074
884
+ - type: precision_at_3
885
+ value: 3.739
886
+ - type: precision_at_5
887
+ value: 2.815
888
+ - type: recall_at_1
889
+ value: 4.916
890
+ - type: recall_at_10
891
+ value: 12.773000000000001
892
+ - type: recall_at_100
893
+ value: 25.465
894
+ - type: recall_at_1000
895
+ value: 47.243
896
+ - type: recall_at_3
897
+ value: 8.272
898
+ - type: recall_at_5
899
+ value: 10.162
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: 9.5
911
+ - type: map_at_10
912
+ value: 12.776000000000002
913
+ - type: map_at_100
914
+ value: 13.444
915
+ - type: map_at_1000
916
+ value: 13.547999999999998
917
+ - type: map_at_3
918
+ value: 11.858
919
+ - type: map_at_5
920
+ value: 12.231
921
+ - type: mrr_at_1
922
+ value: 11.66
923
+ - type: mrr_at_10
924
+ value: 15.454
925
+ - type: mrr_at_100
926
+ value: 16.137999999999998
927
+ - type: mrr_at_1000
928
+ value: 16.233
929
+ - type: mrr_at_3
930
+ value: 14.427999999999999
931
+ - type: mrr_at_5
932
+ value: 14.81
933
+ - type: ndcg_at_1
934
+ value: 11.66
935
+ - type: ndcg_at_10
936
+ value: 15.27
937
+ - type: ndcg_at_100
938
+ value: 18.965
939
+ - type: ndcg_at_1000
940
+ value: 22.177
941
+ - type: ndcg_at_3
942
+ value: 13.431000000000001
943
+ - type: ndcg_at_5
944
+ value: 13.944999999999999
945
+ - type: precision_at_1
946
+ value: 11.66
947
+ - type: precision_at_10
948
+ value: 2.603
949
+ - type: precision_at_100
950
+ value: 0.504
951
+ - type: precision_at_1000
952
+ value: 0.087
953
+ - type: precision_at_3
954
+ value: 6.281000000000001
955
+ - type: precision_at_5
956
+ value: 4.179
957
+ - type: recall_at_1
958
+ value: 9.5
959
+ - type: recall_at_10
960
+ value: 20.514
961
+ - type: recall_at_100
962
+ value: 37.724000000000004
963
+ - type: recall_at_1000
964
+ value: 62.098
965
+ - type: recall_at_3
966
+ value: 15.034
967
+ - type: recall_at_5
968
+ value: 16.506999999999998
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: 12.277000000000001
980
+ - type: map_at_10
981
+ value: 16.07
982
+ - type: map_at_100
983
+ value: 16.958000000000002
984
+ - type: map_at_1000
985
+ value: 17.142
986
+ - type: map_at_3
987
+ value: 14.457999999999998
988
+ - type: map_at_5
989
+ value: 15.283
990
+ - type: mrr_at_1
991
+ value: 15.415000000000001
992
+ - type: mrr_at_10
993
+ value: 19.624
994
+ - type: mrr_at_100
995
+ value: 20.434
996
+ - type: mrr_at_1000
997
+ value: 20.525
998
+ - type: mrr_at_3
999
+ value: 18.083
1000
+ - type: mrr_at_5
1001
+ value: 18.903
1002
+ - type: ndcg_at_1
1003
+ value: 15.415000000000001
1004
+ - type: ndcg_at_10
1005
+ value: 19.429
1006
+ - type: ndcg_at_100
1007
+ value: 23.767
1008
+ - type: ndcg_at_1000
1009
+ value: 27.415
1010
+ - type: ndcg_at_3
1011
+ value: 16.73
1012
+ - type: ndcg_at_5
1013
+ value: 17.882
1014
+ - type: precision_at_1
1015
+ value: 15.415000000000001
1016
+ - type: precision_at_10
1017
+ value: 3.794
1018
+ - type: precision_at_100
1019
+ value: 0.8869999999999999
1020
+ - type: precision_at_1000
1021
+ value: 0.173
1022
+ - type: precision_at_3
1023
+ value: 7.971
1024
+ - type: precision_at_5
1025
+ value: 5.731
1026
+ - type: recall_at_1
1027
+ value: 12.277000000000001
1028
+ - type: recall_at_10
1029
+ value: 25.441999999999997
1030
+ - type: recall_at_100
1031
+ value: 46.048
1032
+ - type: recall_at_1000
1033
+ value: 71.329
1034
+ - type: recall_at_3
1035
+ value: 17.055999999999997
1036
+ - type: recall_at_5
1037
+ value: 20.53
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: 6.531000000000001
1049
+ - type: map_at_10
1050
+ value: 9.957
1051
+ - type: map_at_100
1052
+ value: 10.584
1053
+ - type: map_at_1000
1054
+ value: 10.683
1055
+ - type: map_at_3
1056
+ value: 8.811
1057
+ - type: map_at_5
1058
+ value: 9.536
1059
+ - type: mrr_at_1
1060
+ value: 7.2090000000000005
1061
+ - type: mrr_at_10
1062
+ value: 10.961
1063
+ - type: mrr_at_100
1064
+ value: 11.582
1065
+ - type: mrr_at_1000
1066
+ value: 11.677999999999999
1067
+ - type: mrr_at_3
1068
+ value: 9.643
1069
+ - type: mrr_at_5
1070
+ value: 10.465
1071
+ - type: ndcg_at_1
1072
+ value: 7.2090000000000005
1073
+ - type: ndcg_at_10
1074
+ value: 12.254
1075
+ - type: ndcg_at_100
1076
+ value: 15.891
1077
+ - type: ndcg_at_1000
1078
+ value: 18.965
1079
+ - type: ndcg_at_3
1080
+ value: 9.789
1081
+ - type: ndcg_at_5
1082
+ value: 11.142000000000001
1083
+ - type: precision_at_1
1084
+ value: 7.2090000000000005
1085
+ - type: precision_at_10
1086
+ value: 2.089
1087
+ - type: precision_at_100
1088
+ value: 0.43099999999999994
1089
+ - type: precision_at_1000
1090
+ value: 0.075
1091
+ - type: precision_at_3
1092
+ value: 4.313000000000001
1093
+ - type: precision_at_5
1094
+ value: 3.327
1095
+ - type: recall_at_1
1096
+ value: 6.531000000000001
1097
+ - type: recall_at_10
1098
+ value: 18.465999999999998
1099
+ - type: recall_at_100
1100
+ value: 36.158
1101
+ - type: recall_at_1000
1102
+ value: 60.245000000000005
1103
+ - type: recall_at_3
1104
+ value: 11.860999999999999
1105
+ - type: recall_at_5
1106
+ value: 15.071000000000002
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: 5.463
1118
+ - type: map_at_10
1119
+ value: 9.592
1120
+ - type: map_at_100
1121
+ value: 10.724
1122
+ - type: map_at_1000
1123
+ value: 10.892
1124
+ - type: map_at_3
1125
+ value: 7.866
1126
+ - type: map_at_5
1127
+ value: 8.658000000000001
1128
+ - type: mrr_at_1
1129
+ value: 12.899
1130
+ - type: mrr_at_10
1131
+ value: 20.073
1132
+ - type: mrr_at_100
1133
+ value: 21.05
1134
+ - type: mrr_at_1000
1135
+ value: 21.126
1136
+ - type: mrr_at_3
1137
+ value: 17.438000000000002
1138
+ - type: mrr_at_5
1139
+ value: 18.756999999999998
1140
+ - type: ndcg_at_1
1141
+ value: 12.899
1142
+ - type: ndcg_at_10
1143
+ value: 14.539
1144
+ - type: ndcg_at_100
1145
+ value: 19.903000000000002
1146
+ - type: ndcg_at_1000
1147
+ value: 23.485
1148
+ - type: ndcg_at_3
1149
+ value: 11.225999999999999
1150
+ - type: ndcg_at_5
1151
+ value: 12.232
1152
+ - type: precision_at_1
1153
+ value: 12.899
1154
+ - type: precision_at_10
1155
+ value: 4.8340000000000005
1156
+ - type: precision_at_100
1157
+ value: 1.053
1158
+ - type: precision_at_1000
1159
+ value: 0.16999999999999998
1160
+ - type: precision_at_3
1161
+ value: 8.512
1162
+ - type: precision_at_5
1163
+ value: 6.683999999999999
1164
+ - type: recall_at_1
1165
+ value: 5.463
1166
+ - type: recall_at_10
1167
+ value: 18.383
1168
+ - type: recall_at_100
1169
+ value: 37.592999999999996
1170
+ - type: recall_at_1000
1171
+ value: 58.12199999999999
1172
+ - type: recall_at_3
1173
+ value: 10.388
1174
+ - type: recall_at_5
1175
+ value: 13.197999999999999
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: 2.386
1187
+ - type: map_at_10
1188
+ value: 5.118
1189
+ - type: map_at_100
1190
+ value: 6.997000000000001
1191
+ - type: map_at_1000
1192
+ value: 7.5520000000000005
1193
+ - type: map_at_3
1194
+ value: 3.8019999999999996
1195
+ - type: map_at_5
1196
+ value: 4.38
1197
+ - type: mrr_at_1
1198
+ value: 28.000000000000004
1199
+ - type: mrr_at_10
1200
+ value: 36.482
1201
+ - type: mrr_at_100
1202
+ value: 37.284
1203
+ - type: mrr_at_1000
1204
+ value: 37.338
1205
+ - type: mrr_at_3
1206
+ value: 33.875
1207
+ - type: mrr_at_5
1208
+ value: 35.3
1209
+ - type: ndcg_at_1
1210
+ value: 19.625
1211
+ - type: ndcg_at_10
1212
+ value: 14.543000000000001
1213
+ - type: ndcg_at_100
1214
+ value: 16.511
1215
+ - type: ndcg_at_1000
1216
+ value: 21.855
1217
+ - type: ndcg_at_3
1218
+ value: 16.842
1219
+ - type: ndcg_at_5
1220
+ value: 15.405
1221
+ - type: precision_at_1
1222
+ value: 28.000000000000004
1223
+ - type: precision_at_10
1224
+ value: 13.15
1225
+ - type: precision_at_100
1226
+ value: 4.192
1227
+ - type: precision_at_1000
1228
+ value: 0.918
1229
+ - type: precision_at_3
1230
+ value: 20.833
1231
+ - type: precision_at_5
1232
+ value: 16.950000000000003
1233
+ - type: recall_at_1
1234
+ value: 2.386
1235
+ - type: recall_at_10
1236
+ value: 8.482000000000001
1237
+ - type: recall_at_100
1238
+ value: 20.44
1239
+ - type: recall_at_1000
1240
+ value: 39.257
1241
+ - type: recall_at_3
1242
+ value: 4.739
1243
+ - type: recall_at_5
1244
+ value: 6.1370000000000005
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: 32.865
1256
+ - type: f1
1257
+ value: 30.37449911679073
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: 7.928
1269
+ - type: map_at_10
1270
+ value: 11.763
1271
+ - type: map_at_100
1272
+ value: 12.429
1273
+ - type: map_at_1000
1274
+ value: 12.499
1275
+ - type: map_at_3
1276
+ value: 10.452
1277
+ - type: map_at_5
1278
+ value: 11.162999999999998
1279
+ - type: mrr_at_1
1280
+ value: 8.371
1281
+ - type: mrr_at_10
1282
+ value: 12.357
1283
+ - type: mrr_at_100
1284
+ value: 13.061
1285
+ - type: mrr_at_1000
1286
+ value: 13.129
1287
+ - type: mrr_at_3
1288
+ value: 11.016
1289
+ - type: mrr_at_5
1290
+ value: 11.729000000000001
1291
+ - type: ndcg_at_1
1292
+ value: 8.371
1293
+ - type: ndcg_at_10
1294
+ value: 14.182
1295
+ - type: ndcg_at_100
1296
+ value: 17.771
1297
+ - type: ndcg_at_1000
1298
+ value: 19.872
1299
+ - type: ndcg_at_3
1300
+ value: 11.434999999999999
1301
+ - type: ndcg_at_5
1302
+ value: 12.708
1303
+ - type: precision_at_1
1304
+ value: 8.371
1305
+ - type: precision_at_10
1306
+ value: 2.283
1307
+ - type: precision_at_100
1308
+ value: 0.42100000000000004
1309
+ - type: precision_at_1000
1310
+ value: 0.062
1311
+ - type: precision_at_3
1312
+ value: 4.8500000000000005
1313
+ - type: precision_at_5
1314
+ value: 3.5700000000000003
1315
+ - type: recall_at_1
1316
+ value: 7.928
1317
+ - type: recall_at_10
1318
+ value: 21.287
1319
+ - type: recall_at_100
1320
+ value: 38.393
1321
+ - type: recall_at_1000
1322
+ value: 54.925000000000004
1323
+ - type: recall_at_3
1324
+ value: 13.725000000000001
1325
+ - type: recall_at_5
1326
+ value: 16.798
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: 4.37
1338
+ - type: map_at_10
1339
+ value: 7.382
1340
+ - type: map_at_100
1341
+ value: 8.193
1342
+ - type: map_at_1000
1343
+ value: 8.349
1344
+ - type: map_at_3
1345
+ value: 6.361
1346
+ - type: map_at_5
1347
+ value: 6.814000000000001
1348
+ - type: mrr_at_1
1349
+ value: 8.642
1350
+ - type: mrr_at_10
1351
+ value: 13.352
1352
+ - type: mrr_at_100
1353
+ value: 14.288
1354
+ - type: mrr_at_1000
1355
+ value: 14.394000000000002
1356
+ - type: mrr_at_3
1357
+ value: 11.728
1358
+ - type: mrr_at_5
1359
+ value: 12.592999999999998
1360
+ - type: ndcg_at_1
1361
+ value: 8.642
1362
+ - type: ndcg_at_10
1363
+ value: 10.464
1364
+ - type: ndcg_at_100
1365
+ value: 14.921000000000001
1366
+ - type: ndcg_at_1000
1367
+ value: 19.106
1368
+ - type: ndcg_at_3
1369
+ value: 8.564
1370
+ - type: ndcg_at_5
1371
+ value: 9.186
1372
+ - type: precision_at_1
1373
+ value: 8.642
1374
+ - type: precision_at_10
1375
+ value: 2.978
1376
+ - type: precision_at_100
1377
+ value: 0.738
1378
+ - type: precision_at_1000
1379
+ value: 0.14300000000000002
1380
+ - type: precision_at_3
1381
+ value: 5.71
1382
+ - type: precision_at_5
1383
+ value: 4.352
1384
+ - type: recall_at_1
1385
+ value: 4.37
1386
+ - type: recall_at_10
1387
+ value: 13.794
1388
+ - type: recall_at_100
1389
+ value: 31.596000000000004
1390
+ - type: recall_at_1000
1391
+ value: 58.724
1392
+ - type: recall_at_3
1393
+ value: 8.401
1394
+ - type: recall_at_5
1395
+ value: 10.266
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: 8.596
1407
+ - type: map_at_10
1408
+ value: 11.951
1409
+ - type: map_at_100
1410
+ value: 12.478
1411
+ - type: map_at_1000
1412
+ value: 12.558
1413
+ - type: map_at_3
1414
+ value: 10.870000000000001
1415
+ - type: map_at_5
1416
+ value: 11.476
1417
+ - type: mrr_at_1
1418
+ value: 17.191000000000003
1419
+ - type: mrr_at_10
1420
+ value: 21.662
1421
+ - type: mrr_at_100
1422
+ value: 22.249
1423
+ - type: mrr_at_1000
1424
+ value: 22.319
1425
+ - type: mrr_at_3
1426
+ value: 20.227
1427
+ - type: mrr_at_5
1428
+ value: 21.047
1429
+ - type: ndcg_at_1
1430
+ value: 17.191000000000003
1431
+ - type: ndcg_at_10
1432
+ value: 15.939
1433
+ - type: ndcg_at_100
1434
+ value: 18.711
1435
+ - type: ndcg_at_1000
1436
+ value: 20.942
1437
+ - type: ndcg_at_3
1438
+ value: 13.642999999999999
1439
+ - type: ndcg_at_5
1440
+ value: 14.767
1441
+ - type: precision_at_1
1442
+ value: 17.191000000000003
1443
+ - type: precision_at_10
1444
+ value: 3.633
1445
+ - type: precision_at_100
1446
+ value: 0.587
1447
+ - type: precision_at_1000
1448
+ value: 0.089
1449
+ - type: precision_at_3
1450
+ value: 8.643
1451
+ - type: precision_at_5
1452
+ value: 6.077
1453
+ - type: recall_at_1
1454
+ value: 8.596
1455
+ - type: recall_at_10
1456
+ value: 18.163
1457
+ - type: recall_at_100
1458
+ value: 29.359
1459
+ - type: recall_at_1000
1460
+ value: 44.348
1461
+ - type: recall_at_3
1462
+ value: 12.964
1463
+ - type: recall_at_5
1464
+ value: 15.192
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: 63.91439999999999
1476
+ - type: ap
1477
+ value: 59.096879955371705
1478
+ - type: f1
1479
+ value: 63.65122028830217
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: 4.728000000000001
1491
+ - type: map_at_10
1492
+ value: 7.846
1493
+ - type: map_at_100
1494
+ value: 8.577
1495
+ - type: map_at_1000
1496
+ value: 8.669
1497
+ - type: map_at_3
1498
+ value: 6.601
1499
+ - type: map_at_5
1500
+ value: 7.239
1501
+ - type: mrr_at_1
1502
+ value: 4.857
1503
+ - type: mrr_at_10
1504
+ value: 8.056000000000001
1505
+ - type: mrr_at_100
1506
+ value: 8.792
1507
+ - type: mrr_at_1000
1508
+ value: 8.882
1509
+ - type: mrr_at_3
1510
+ value: 6.776999999999999
1511
+ - type: mrr_at_5
1512
+ value: 7.430000000000001
1513
+ - type: ndcg_at_1
1514
+ value: 4.842
1515
+ - type: ndcg_at_10
1516
+ value: 9.908999999999999
1517
+ - type: ndcg_at_100
1518
+ value: 14.008999999999999
1519
+ - type: ndcg_at_1000
1520
+ value: 16.833000000000002
1521
+ - type: ndcg_at_3
1522
+ value: 7.276000000000001
1523
+ - type: ndcg_at_5
1524
+ value: 8.434
1525
+ - type: precision_at_1
1526
+ value: 4.842
1527
+ - type: precision_at_10
1528
+ value: 1.699
1529
+ - type: precision_at_100
1530
+ value: 0.384
1531
+ - type: precision_at_1000
1532
+ value: 0.063
1533
+ - type: precision_at_3
1534
+ value: 3.114
1535
+ - type: precision_at_5
1536
+ value: 2.45
1537
+ - type: recall_at_1
1538
+ value: 4.728000000000001
1539
+ - type: recall_at_10
1540
+ value: 16.375
1541
+ - type: recall_at_100
1542
+ value: 36.644
1543
+ - type: recall_at_1000
1544
+ value: 59.394999999999996
1545
+ - type: recall_at_3
1546
+ value: 9.062000000000001
1547
+ - type: recall_at_5
1548
+ value: 11.866999999999999
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: 85.20291837665299
1560
+ - type: f1
1561
+ value: 84.70904496376967
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: 56.529867761057915
1573
+ - type: f1
1574
+ value: 37.68950362422533
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: 56.38870208473436
1586
+ - type: f1
1587
+ value: 53.66913773017876
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: 64.53597848016139
1599
+ - type: f1
1600
+ value: 62.79623963098659
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: 27.17951777550973
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: 25.59311527698471
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: 28.965933039410707
1634
+ - type: mrr
1635
+ value: 29.71860627679794
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: 3.497
1647
+ - type: map_at_10
1648
+ value: 7.195
1649
+ - type: map_at_100
1650
+ value: 8.738999999999999
1651
+ - type: map_at_1000
1652
+ value: 9.934999999999999
1653
+ - type: map_at_3
1654
+ value: 5.572
1655
+ - type: map_at_5
1656
+ value: 6.311
1657
+ - type: mrr_at_1
1658
+ value: 26.935
1659
+ - type: mrr_at_10
1660
+ value: 38.634
1661
+ - type: mrr_at_100
1662
+ value: 39.236
1663
+ - type: mrr_at_1000
1664
+ value: 39.308
1665
+ - type: mrr_at_3
1666
+ value: 35.759
1667
+ - type: mrr_at_5
1668
+ value: 37.183
1669
+ - type: ndcg_at_1
1670
+ value: 25.697
1671
+ - type: ndcg_at_10
1672
+ value: 21.618000000000002
1673
+ - type: ndcg_at_100
1674
+ value: 20.832
1675
+ - type: ndcg_at_1000
1676
+ value: 30.742000000000004
1677
+ - type: ndcg_at_3
1678
+ value: 23.904
1679
+ - type: ndcg_at_5
1680
+ value: 22.922
1681
+ - type: precision_at_1
1682
+ value: 26.935
1683
+ - type: precision_at_10
1684
+ value: 15.851
1685
+ - type: precision_at_100
1686
+ value: 5.5329999999999995
1687
+ - type: precision_at_1000
1688
+ value: 1.886
1689
+ - type: precision_at_3
1690
+ value: 22.497
1691
+ - type: precision_at_5
1692
+ value: 19.752
1693
+ - type: recall_at_1
1694
+ value: 3.497
1695
+ - type: recall_at_10
1696
+ value: 11.411999999999999
1697
+ - type: recall_at_100
1698
+ value: 23.757
1699
+ - type: recall_at_1000
1700
+ value: 58.314
1701
+ - type: recall_at_3
1702
+ value: 6.814000000000001
1703
+ - type: recall_at_5
1704
+ value: 8.36
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: 6.4430000000000005
1716
+ - type: map_at_10
1717
+ value: 10.884
1718
+ - type: map_at_100
1719
+ value: 11.689
1720
+ - type: map_at_1000
1721
+ value: 11.772
1722
+ - type: map_at_3
1723
+ value: 9.109
1724
+ - type: map_at_5
1725
+ value: 10.075000000000001
1726
+ - type: mrr_at_1
1727
+ value: 7.445
1728
+ - type: mrr_at_10
1729
+ value: 12.103
1730
+ - type: mrr_at_100
1731
+ value: 12.882
1732
+ - type: mrr_at_1000
1733
+ value: 12.956999999999999
1734
+ - type: mrr_at_3
1735
+ value: 10.294
1736
+ - type: mrr_at_5
1737
+ value: 11.292
1738
+ - type: ndcg_at_1
1739
+ value: 7.445
1740
+ - type: ndcg_at_10
1741
+ value: 13.949
1742
+ - type: ndcg_at_100
1743
+ value: 18.285999999999998
1744
+ - type: ndcg_at_1000
1745
+ value: 20.738
1746
+ - type: ndcg_at_3
1747
+ value: 10.302999999999999
1748
+ - type: ndcg_at_5
1749
+ value: 12.052
1750
+ - type: precision_at_1
1751
+ value: 7.445
1752
+ - type: precision_at_10
1753
+ value: 2.648
1754
+ - type: precision_at_100
1755
+ value: 0.516
1756
+ - type: precision_at_1000
1757
+ value: 0.075
1758
+ - type: precision_at_3
1759
+ value: 4.896
1760
+ - type: precision_at_5
1761
+ value: 3.9170000000000003
1762
+ - type: recall_at_1
1763
+ value: 6.4430000000000005
1764
+ - type: recall_at_10
1765
+ value: 22.296
1766
+ - type: recall_at_100
1767
+ value: 42.903000000000006
1768
+ - type: recall_at_1000
1769
+ value: 61.988
1770
+ - type: recall_at_3
1771
+ value: 12.617999999999999
1772
+ - type: recall_at_5
1773
+ value: 16.77
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: 54.93599999999999
1785
+ - type: map_at_10
1786
+ value: 66.461
1787
+ - type: map_at_100
1788
+ value: 67.274
1789
+ - type: map_at_1000
1790
+ value: 67.31899999999999
1791
+ - type: map_at_3
1792
+ value: 63.742
1793
+ - type: map_at_5
1794
+ value: 65.347
1795
+ - type: mrr_at_1
1796
+ value: 63.28
1797
+ - type: mrr_at_10
1798
+ value: 71.163
1799
+ - type: mrr_at_100
1800
+ value: 71.53
1801
+ - type: mrr_at_1000
1802
+ value: 71.54599999999999
1803
+ - type: mrr_at_3
1804
+ value: 69.50699999999999
1805
+ - type: mrr_at_5
1806
+ value: 70.52000000000001
1807
+ - type: ndcg_at_1
1808
+ value: 63.33
1809
+ - type: ndcg_at_10
1810
+ value: 71.439
1811
+ - type: ndcg_at_100
1812
+ value: 74.154
1813
+ - type: ndcg_at_1000
1814
+ value: 74.90400000000001
1815
+ - type: ndcg_at_3
1816
+ value: 67.723
1817
+ - type: ndcg_at_5
1818
+ value: 69.549
1819
+ - type: precision_at_1
1820
+ value: 63.33
1821
+ - type: precision_at_10
1822
+ value: 10.81
1823
+ - type: precision_at_100
1824
+ value: 1.3390000000000002
1825
+ - type: precision_at_1000
1826
+ value: 0.147
1827
+ - type: precision_at_3
1828
+ value: 29.38
1829
+ - type: precision_at_5
1830
+ value: 19.432
1831
+ - type: recall_at_1
1832
+ value: 54.93599999999999
1833
+ - type: recall_at_10
1834
+ value: 81.259
1835
+ - type: recall_at_100
1836
+ value: 92.15100000000001
1837
+ - type: recall_at_1000
1838
+ value: 96.994
1839
+ - type: recall_at_3
1840
+ value: 70.499
1841
+ - type: recall_at_5
1842
+ value: 75.575
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: 28.528725482087307
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: 39.02529299655054
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: 2.078
1876
+ - type: map_at_10
1877
+ value: 5.050000000000001
1878
+ - type: map_at_100
1879
+ value: 6.0440000000000005
1880
+ - type: map_at_1000
1881
+ value: 6.261
1882
+ - type: map_at_3
1883
+ value: 3.763
1884
+ - type: map_at_5
1885
+ value: 4.376
1886
+ - type: mrr_at_1
1887
+ value: 10.2
1888
+ - type: mrr_at_10
1889
+ value: 17.36
1890
+ - type: mrr_at_100
1891
+ value: 18.403
1892
+ - type: mrr_at_1000
1893
+ value: 18.52
1894
+ - type: mrr_at_3
1895
+ value: 14.899999999999999
1896
+ - type: mrr_at_5
1897
+ value: 16.13
1898
+ - type: ndcg_at_1
1899
+ value: 10.2
1900
+ - type: ndcg_at_10
1901
+ value: 9.398
1902
+ - type: ndcg_at_100
1903
+ value: 14.48
1904
+ - type: ndcg_at_1000
1905
+ value: 19.551
1906
+ - type: ndcg_at_3
1907
+ value: 8.790000000000001
1908
+ - type: ndcg_at_5
1909
+ value: 7.669
1910
+ - type: precision_at_1
1911
+ value: 10.2
1912
+ - type: precision_at_10
1913
+ value: 4.9399999999999995
1914
+ - type: precision_at_100
1915
+ value: 1.25
1916
+ - type: precision_at_1000
1917
+ value: 0.248
1918
+ - type: precision_at_3
1919
+ value: 8.267
1920
+ - type: precision_at_5
1921
+ value: 6.74
1922
+ - type: recall_at_1
1923
+ value: 2.078
1924
+ - type: recall_at_10
1925
+ value: 10.025
1926
+ - type: recall_at_100
1927
+ value: 25.346999999999998
1928
+ - type: recall_at_1000
1929
+ value: 50.393
1930
+ - type: recall_at_3
1931
+ value: 5.038
1932
+ - type: recall_at_5
1933
+ value: 6.851999999999999
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: 70.69485438461535
1945
+ - type: cos_sim_spearman
1946
+ value: 60.7079462281202
1947
+ - type: euclidean_pearson
1948
+ value: 66.34648734074841
1949
+ - type: euclidean_spearman
1950
+ value: 60.70819668068561
1951
+ - type: manhattan_pearson
1952
+ value: 67.08589891209486
1953
+ - type: manhattan_spearman
1954
+ value: 61.037259945651165
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: 62.63440086574824
1966
+ - type: cos_sim_spearman
1967
+ value: 57.22862459567004
1968
+ - type: euclidean_pearson
1969
+ value: 61.33135391980671
1970
+ - type: euclidean_spearman
1971
+ value: 57.2287396395971
1972
+ - type: manhattan_pearson
1973
+ value: 63.538353299276665
1974
+ - type: manhattan_spearman
1975
+ value: 59.31604272847601
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: 66.99729287299299
1987
+ - type: cos_sim_spearman
1988
+ value: 69.20264774948375
1989
+ - type: euclidean_pearson
1990
+ value: 68.83879433164682
1991
+ - type: euclidean_spearman
1992
+ value: 69.20257380705361
1993
+ - type: manhattan_pearson
1994
+ value: 68.82235273988779
1995
+ - type: manhattan_spearman
1996
+ value: 69.12895594376502
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: 63.43542239265359
2008
+ - type: cos_sim_spearman
2009
+ value: 62.75650954855537
2010
+ - type: euclidean_pearson
2011
+ value: 63.87500752354951
2012
+ - type: euclidean_spearman
2013
+ value: 62.75647357698498
2014
+ - type: manhattan_pearson
2015
+ value: 64.30854220561612
2016
+ - type: manhattan_spearman
2017
+ value: 63.221533112975756
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: 70.3113558570832
2029
+ - type: cos_sim_spearman
2030
+ value: 72.99345938388264
2031
+ - type: euclidean_pearson
2032
+ value: 72.46131589134022
2033
+ - type: euclidean_spearman
2034
+ value: 72.99345776180552
2035
+ - type: manhattan_pearson
2036
+ value: 72.98365443642383
2037
+ - type: manhattan_spearman
2038
+ value: 73.52773752441843
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: 59.508816955942734
2050
+ - type: cos_sim_spearman
2051
+ value: 64.16476610475141
2052
+ - type: euclidean_pearson
2053
+ value: 63.49096301327081
2054
+ - type: euclidean_spearman
2055
+ value: 64.16559631894077
2056
+ - type: manhattan_pearson
2057
+ value: 63.756149631030304
2058
+ - type: manhattan_spearman
2059
+ value: 64.26840399223137
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: 67.68609826979123
2071
+ - type: cos_sim_spearman
2072
+ value: 71.8432324170499
2073
+ - type: euclidean_pearson
2074
+ value: 70.78716630279412
2075
+ - type: euclidean_spearman
2076
+ value: 71.84411358655781
2077
+ - type: manhattan_pearson
2078
+ value: 71.1878199213668
2079
+ - type: manhattan_spearman
2080
+ value: 71.86475568531382
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: 37.9433386647078
2092
+ - type: cos_sim_spearman
2093
+ value: 52.54985995593481
2094
+ - type: euclidean_pearson
2095
+ value: 46.11105905665655
2096
+ - type: euclidean_spearman
2097
+ value: 52.54985995593481
2098
+ - type: manhattan_pearson
2099
+ value: 46.41925532506553
2100
+ - type: manhattan_spearman
2101
+ value: 52.88777657839048
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: 60.69914968545304
2113
+ - type: cos_sim_spearman
2114
+ value: 60.16961331310221
2115
+ - type: euclidean_pearson
2116
+ value: 62.24558593778339
2117
+ - type: euclidean_spearman
2118
+ value: 60.16965021618944
2119
+ - type: manhattan_pearson
2120
+ value: 62.75643658834279
2121
+ - type: manhattan_spearman
2122
+ value: 60.537294014043894
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: 67.86284091295416
2134
+ - type: mrr
2135
+ value: 88.32576192870312
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: 24.778
2147
+ - type: map_at_10
2148
+ value: 32.706
2149
+ - type: map_at_100
2150
+ value: 33.571
2151
+ - type: map_at_1000
2152
+ value: 33.678000000000004
2153
+ - type: map_at_3
2154
+ value: 29.976999999999997
2155
+ - type: map_at_5
2156
+ value: 31.594
2157
+ - type: mrr_at_1
2158
+ value: 25.667
2159
+ - type: mrr_at_10
2160
+ value: 33.932
2161
+ - type: mrr_at_100
2162
+ value: 34.698
2163
+ - type: mrr_at_1000
2164
+ value: 34.788000000000004
2165
+ - type: mrr_at_3
2166
+ value: 31.278
2167
+ - type: mrr_at_5
2168
+ value: 32.861000000000004
2169
+ - type: ndcg_at_1
2170
+ value: 25.667
2171
+ - type: ndcg_at_10
2172
+ value: 37.522
2173
+ - type: ndcg_at_100
2174
+ value: 42.132
2175
+ - type: ndcg_at_1000
2176
+ value: 44.702999999999996
2177
+ - type: ndcg_at_3
2178
+ value: 31.948
2179
+ - type: ndcg_at_5
2180
+ value: 34.867
2181
+ - type: precision_at_1
2182
+ value: 25.667
2183
+ - type: precision_at_10
2184
+ value: 5.567
2185
+ - type: precision_at_100
2186
+ value: 0.827
2187
+ - type: precision_at_1000
2188
+ value: 0.105
2189
+ - type: precision_at_3
2190
+ value: 13.0
2191
+ - type: precision_at_5
2192
+ value: 9.4
2193
+ - type: recall_at_1
2194
+ value: 24.778
2195
+ - type: recall_at_10
2196
+ value: 51.471999999999994
2197
+ - type: recall_at_100
2198
+ value: 73.47200000000001
2199
+ - type: recall_at_1000
2200
+ value: 93.01700000000001
2201
+ - type: recall_at_3
2202
+ value: 36.222
2203
+ - type: recall_at_5
2204
+ value: 43.389
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: 99.48514851485149
2216
+ - type: cos_sim_ap
2217
+ value: 75.38722575287751
2218
+ - type: cos_sim_f1
2219
+ value: 70.21505376344086
2220
+ - type: cos_sim_precision
2221
+ value: 75.93023255813954
2222
+ - type: cos_sim_recall
2223
+ value: 65.3
2224
+ - type: dot_accuracy
2225
+ value: 99.48514851485149
2226
+ - type: dot_ap
2227
+ value: 75.38722575287751
2228
+ - type: dot_f1
2229
+ value: 70.21505376344086
2230
+ - type: dot_precision
2231
+ value: 75.93023255813954
2232
+ - type: dot_recall
2233
+ value: 65.3
2234
+ - type: euclidean_accuracy
2235
+ value: 99.48514851485149
2236
+ - type: euclidean_ap
2237
+ value: 75.38722575287751
2238
+ - type: euclidean_f1
2239
+ value: 70.21505376344086
2240
+ - type: euclidean_precision
2241
+ value: 75.93023255813954
2242
+ - type: euclidean_recall
2243
+ value: 65.3
2244
+ - type: manhattan_accuracy
2245
+ value: 99.51782178217822
2246
+ - type: manhattan_ap
2247
+ value: 78.5581368006355
2248
+ - type: manhattan_f1
2249
+ value: 72.85333333333335
2250
+ - type: manhattan_precision
2251
+ value: 78.05714285714286
2252
+ - type: manhattan_recall
2253
+ value: 68.30000000000001
2254
+ - type: max_accuracy
2255
+ value: 99.51782178217822
2256
+ - type: max_ap
2257
+ value: 78.5581368006355
2258
+ - type: max_f1
2259
+ value: 72.85333333333335
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: 41.454786971313716
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: 27.982742328787946
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: 39.80307350579408
2293
+ - type: mrr
2294
+ value: 39.984641583906296
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: 30.508810779370265
2306
+ - type: cos_sim_spearman
2307
+ value: 31.41267324195085
2308
+ - type: dot_pearson
2309
+ value: 30.50881077275705
2310
+ - type: dot_spearman
2311
+ value: 31.409127482666634
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: 0.127
2323
+ - type: map_at_10
2324
+ value: 0.79
2325
+ - type: map_at_100
2326
+ value: 3.549
2327
+ - type: map_at_1000
2328
+ value: 8.137
2329
+ - type: map_at_3
2330
+ value: 0.32299999999999995
2331
+ - type: map_at_5
2332
+ value: 0.44200000000000006
2333
+ - type: mrr_at_1
2334
+ value: 56.00000000000001
2335
+ - type: mrr_at_10
2336
+ value: 66.777
2337
+ - type: mrr_at_100
2338
+ value: 67.09
2339
+ - type: mrr_at_1000
2340
+ value: 67.09
2341
+ - type: mrr_at_3
2342
+ value: 65.0
2343
+ - type: mrr_at_5
2344
+ value: 65.4
2345
+ - type: ndcg_at_1
2346
+ value: 48.0
2347
+ - type: ndcg_at_10
2348
+ value: 41.178
2349
+ - type: ndcg_at_100
2350
+ value: 28.372000000000003
2351
+ - type: ndcg_at_1000
2352
+ value: 24.953
2353
+ - type: ndcg_at_3
2354
+ value: 44.285000000000004
2355
+ - type: ndcg_at_5
2356
+ value: 42.074
2357
+ - type: precision_at_1
2358
+ value: 56.00000000000001
2359
+ - type: precision_at_10
2360
+ value: 45.4
2361
+ - type: precision_at_100
2362
+ value: 29.34
2363
+ - type: precision_at_1000
2364
+ value: 12.112
2365
+ - type: precision_at_3
2366
+ value: 49.333
2367
+ - type: precision_at_5
2368
+ value: 45.2
2369
+ - type: recall_at_1
2370
+ value: 0.127
2371
+ - type: recall_at_10
2372
+ value: 1.0739999999999998
2373
+ - type: recall_at_100
2374
+ value: 6.36
2375
+ - type: recall_at_1000
2376
+ value: 24.374000000000002
2377
+ - type: recall_at_3
2378
+ value: 0.372
2379
+ - type: recall_at_5
2380
+ value: 0.528
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: 1.353
2392
+ - type: map_at_10
2393
+ value: 3.871
2394
+ - type: map_at_100
2395
+ value: 6.507000000000001
2396
+ - type: map_at_1000
2397
+ value: 7.982
2398
+ - type: map_at_3
2399
+ value: 2.249
2400
+ - type: map_at_5
2401
+ value: 3.0140000000000002
2402
+ - type: mrr_at_1
2403
+ value: 18.367
2404
+ - type: mrr_at_10
2405
+ value: 27.947
2406
+ - type: mrr_at_100
2407
+ value: 30.349999999999998
2408
+ - type: mrr_at_1000
2409
+ value: 30.372
2410
+ - type: mrr_at_3
2411
+ value: 23.469
2412
+ - type: mrr_at_5
2413
+ value: 26.429000000000002
2414
+ - type: ndcg_at_1
2415
+ value: 16.326999999999998
2416
+ - type: ndcg_at_10
2417
+ value: 11.886
2418
+ - type: ndcg_at_100
2419
+ value: 20.929000000000002
2420
+ - type: ndcg_at_1000
2421
+ value: 34.422999999999995
2422
+ - type: ndcg_at_3
2423
+ value: 12.806999999999999
2424
+ - type: ndcg_at_5
2425
+ value: 12.879999999999999
2426
+ - type: precision_at_1
2427
+ value: 18.367
2428
+ - type: precision_at_10
2429
+ value: 11.224
2430
+ - type: precision_at_100
2431
+ value: 5.061
2432
+ - type: precision_at_1000
2433
+ value: 1.341
2434
+ - type: precision_at_3
2435
+ value: 13.605
2436
+ - type: precision_at_5
2437
+ value: 13.877999999999998
2438
+ - type: recall_at_1
2439
+ value: 1.353
2440
+ - type: recall_at_10
2441
+ value: 7.654
2442
+ - type: recall_at_100
2443
+ value: 31.558000000000003
2444
+ - type: recall_at_1000
2445
+ value: 72.898
2446
+ - type: recall_at_3
2447
+ value: 2.964
2448
+ - type: recall_at_5
2449
+ value: 4.874
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: 69.8528
2461
+ - type: ap
2462
+ value: 13.242246154786407
2463
+ - type: f1
2464
+ value: 53.36206582019686
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: 52.292020373514426
2476
+ - type: f1
2477
+ value: 52.43359560180576
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: 31.730793809823094
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: 82.0826131012696
2500
+ - type: cos_sim_ap
2501
+ value: 58.927117152392015
2502
+ - type: cos_sim_f1
2503
+ value: 57.50386797318205
2504
+ - type: cos_sim_precision
2505
+ value: 56.227937468482104
2506
+ - type: cos_sim_recall
2507
+ value: 58.839050131926115
2508
+ - type: dot_accuracy
2509
+ value: 82.0826131012696
2510
+ - type: dot_ap
2511
+ value: 58.927117152392015
2512
+ - type: dot_f1
2513
+ value: 57.50386797318205
2514
+ - type: dot_precision
2515
+ value: 56.227937468482104
2516
+ - type: dot_recall
2517
+ value: 58.839050131926115
2518
+ - type: euclidean_accuracy
2519
+ value: 82.0826131012696
2520
+ - type: euclidean_ap
2521
+ value: 58.927117152392015
2522
+ - type: euclidean_f1
2523
+ value: 57.50386797318205
2524
+ - type: euclidean_precision
2525
+ value: 56.227937468482104
2526
+ - type: euclidean_recall
2527
+ value: 58.839050131926115
2528
+ - type: manhattan_accuracy
2529
+ value: 82.02300768909816
2530
+ - type: manhattan_ap
2531
+ value: 58.522165728999134
2532
+ - type: manhattan_f1
2533
+ value: 57.4462890625
2534
+ - type: manhattan_precision
2535
+ value: 53.45297592003635
2536
+ - type: manhattan_recall
2537
+ value: 62.0844327176781
2538
+ - type: max_accuracy
2539
+ value: 82.0826131012696
2540
+ - type: max_ap
2541
+ value: 58.927117152392015
2542
+ - type: max_f1
2543
+ value: 57.50386797318205
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: 86.2459735320371
2555
+ - type: cos_sim_ap
2556
+ value: 78.90275828118249
2557
+ - type: cos_sim_f1
2558
+ value: 71.35335558027438
2559
+ - type: cos_sim_precision
2560
+ value: 68.81705049349162
2561
+ - type: cos_sim_recall
2562
+ value: 74.08376963350786
2563
+ - type: dot_accuracy
2564
+ value: 86.2459735320371
2565
+ - type: dot_ap
2566
+ value: 78.90275960892674
2567
+ - type: dot_f1
2568
+ value: 71.35335558027438
2569
+ - type: dot_precision
2570
+ value: 68.81705049349162
2571
+ - type: dot_recall
2572
+ value: 74.08376963350786
2573
+ - type: euclidean_accuracy
2574
+ value: 86.2459735320371
2575
+ - type: euclidean_ap
2576
+ value: 78.90275805900576
2577
+ - type: euclidean_f1
2578
+ value: 71.35335558027438
2579
+ - type: euclidean_precision
2580
+ value: 68.81705049349162
2581
+ - type: euclidean_recall
2582
+ value: 74.08376963350786
2583
+ - type: manhattan_accuracy
2584
+ value: 86.16835487251136
2585
+ - type: manhattan_ap
2586
+ value: 78.84683659402509
2587
+ - type: manhattan_f1
2588
+ value: 71.18720602069612
2589
+ - type: manhattan_precision
2590
+ value: 69.61801722234489
2591
+ - type: manhattan_recall
2592
+ value: 72.82876501385894
2593
+ - type: max_accuracy
2594
+ value: 86.2459735320371
2595
+ - type: max_ap
2596
+ value: 78.90275960892674
2597
+ - type: max_f1
2598
+ value: 71.35335558027438
2599
+ ---