multi-train commited on
Commit
47a2cb1
1 Parent(s): 2400f9e

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +2496 -0
README.md CHANGED
@@ -23,9 +23,2505 @@ tags:
23
  - ms_marco
24
  - fever
25
  - hotpot_qa
 
26
  language: en
27
  inference: false
28
  license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
29
  ---
30
 
31
  # hkunlp/instructor-xl
 
23
  - ms_marco
24
  - fever
25
  - hotpot_qa
26
+ - mteb
27
  language: en
28
  inference: false
29
  license: apache-2.0
30
+ model-index:
31
+ - name: final_xl_results
32
+ results:
33
+ - task:
34
+ type: Classification
35
+ dataset:
36
+ type: mteb/amazon_counterfactual
37
+ name: MTEB AmazonCounterfactualClassification (en)
38
+ config: en
39
+ split: test
40
+ revision: e8379541af4e31359cca9fbcf4b00f2671dba205
41
+ metrics:
42
+ - type: accuracy
43
+ value: 85.08955223880596
44
+ - type: ap
45
+ value: 52.66066378722476
46
+ - type: f1
47
+ value: 79.63340218960269
48
+ - task:
49
+ type: Classification
50
+ dataset:
51
+ type: mteb/amazon_polarity
52
+ name: MTEB AmazonPolarityClassification
53
+ config: default
54
+ split: test
55
+ revision: e2d317d38cd51312af73b3d32a06d1a08b442046
56
+ metrics:
57
+ - type: accuracy
58
+ value: 86.542
59
+ - type: ap
60
+ value: 81.92695193008987
61
+ - type: f1
62
+ value: 86.51466132573681
63
+ - task:
64
+ type: Classification
65
+ dataset:
66
+ type: mteb/amazon_reviews_multi
67
+ name: MTEB AmazonReviewsClassification (en)
68
+ config: en
69
+ split: test
70
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
71
+ metrics:
72
+ - type: accuracy
73
+ value: 42.964
74
+ - type: f1
75
+ value: 41.43146249774862
76
+ - task:
77
+ type: Retrieval
78
+ dataset:
79
+ type: arguana
80
+ name: MTEB ArguAna
81
+ config: default
82
+ split: test
83
+ revision: None
84
+ metrics:
85
+ - type: map_at_1
86
+ value: 29.872
87
+ - type: map_at_10
88
+ value: 46.342
89
+ - type: map_at_100
90
+ value: 47.152
91
+ - type: map_at_1000
92
+ value: 47.154
93
+ - type: map_at_3
94
+ value: 41.216
95
+ - type: map_at_5
96
+ value: 44.035999999999994
97
+ - type: mrr_at_1
98
+ value: 30.939
99
+ - type: mrr_at_10
100
+ value: 46.756
101
+ - type: mrr_at_100
102
+ value: 47.573
103
+ - type: mrr_at_1000
104
+ value: 47.575
105
+ - type: mrr_at_3
106
+ value: 41.548
107
+ - type: mrr_at_5
108
+ value: 44.425
109
+ - type: ndcg_at_1
110
+ value: 29.872
111
+ - type: ndcg_at_10
112
+ value: 55.65
113
+ - type: ndcg_at_100
114
+ value: 58.88099999999999
115
+ - type: ndcg_at_1000
116
+ value: 58.951
117
+ - type: ndcg_at_3
118
+ value: 45.0
119
+ - type: ndcg_at_5
120
+ value: 50.09
121
+ - type: precision_at_1
122
+ value: 29.872
123
+ - type: precision_at_10
124
+ value: 8.549
125
+ - type: precision_at_100
126
+ value: 0.991
127
+ - type: precision_at_1000
128
+ value: 0.1
129
+ - type: precision_at_3
130
+ value: 18.658
131
+ - type: precision_at_5
132
+ value: 13.669999999999998
133
+ - type: recall_at_1
134
+ value: 29.872
135
+ - type: recall_at_10
136
+ value: 85.491
137
+ - type: recall_at_100
138
+ value: 99.075
139
+ - type: recall_at_1000
140
+ value: 99.644
141
+ - type: recall_at_3
142
+ value: 55.974000000000004
143
+ - type: recall_at_5
144
+ value: 68.35
145
+ - task:
146
+ type: Clustering
147
+ dataset:
148
+ type: mteb/arxiv-clustering-p2p
149
+ name: MTEB ArxivClusteringP2P
150
+ config: default
151
+ split: test
152
+ revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
153
+ metrics:
154
+ - type: v_measure
155
+ value: 42.452729850641276
156
+ - task:
157
+ type: Clustering
158
+ dataset:
159
+ type: mteb/arxiv-clustering-s2s
160
+ name: MTEB ArxivClusteringS2S
161
+ config: default
162
+ split: test
163
+ revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
164
+ metrics:
165
+ - type: v_measure
166
+ value: 32.21141846480423
167
+ - task:
168
+ type: Reranking
169
+ dataset:
170
+ type: mteb/askubuntudupquestions-reranking
171
+ name: MTEB AskUbuntuDupQuestions
172
+ config: default
173
+ split: test
174
+ revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
175
+ metrics:
176
+ - type: map
177
+ value: 65.34710928952622
178
+ - type: mrr
179
+ value: 77.61124301983028
180
+ - task:
181
+ type: STS
182
+ dataset:
183
+ type: mteb/biosses-sts
184
+ name: MTEB BIOSSES
185
+ config: default
186
+ split: test
187
+ revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
188
+ metrics:
189
+ - type: cos_sim_spearman
190
+ value: 84.15312230525639
191
+ - task:
192
+ type: Classification
193
+ dataset:
194
+ type: mteb/banking77
195
+ name: MTEB Banking77Classification
196
+ config: default
197
+ split: test
198
+ revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
199
+ metrics:
200
+ - type: accuracy
201
+ value: 82.66233766233766
202
+ - type: f1
203
+ value: 82.04175284777669
204
+ - task:
205
+ type: Clustering
206
+ dataset:
207
+ type: mteb/biorxiv-clustering-p2p
208
+ name: MTEB BiorxivClusteringP2P
209
+ config: default
210
+ split: test
211
+ revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
212
+ metrics:
213
+ - type: v_measure
214
+ value: 37.36697339826455
215
+ - task:
216
+ type: Clustering
217
+ dataset:
218
+ type: mteb/biorxiv-clustering-s2s
219
+ name: MTEB BiorxivClusteringS2S
220
+ config: default
221
+ split: test
222
+ revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
223
+ metrics:
224
+ - type: v_measure
225
+ value: 30.551241447593092
226
+ - task:
227
+ type: Retrieval
228
+ dataset:
229
+ type: BeIR/cqadupstack
230
+ name: MTEB CQADupstackAndroidRetrieval
231
+ config: default
232
+ split: test
233
+ revision: None
234
+ metrics:
235
+ - type: map_at_1
236
+ value: 36.797000000000004
237
+ - type: map_at_10
238
+ value: 48.46
239
+ - type: map_at_100
240
+ value: 49.968
241
+ - type: map_at_1000
242
+ value: 50.080000000000005
243
+ - type: map_at_3
244
+ value: 44.71
245
+ - type: map_at_5
246
+ value: 46.592
247
+ - type: mrr_at_1
248
+ value: 45.494
249
+ - type: mrr_at_10
250
+ value: 54.747
251
+ - type: mrr_at_100
252
+ value: 55.43599999999999
253
+ - type: mrr_at_1000
254
+ value: 55.464999999999996
255
+ - type: mrr_at_3
256
+ value: 52.361000000000004
257
+ - type: mrr_at_5
258
+ value: 53.727000000000004
259
+ - type: ndcg_at_1
260
+ value: 45.494
261
+ - type: ndcg_at_10
262
+ value: 54.989
263
+ - type: ndcg_at_100
264
+ value: 60.096000000000004
265
+ - type: ndcg_at_1000
266
+ value: 61.58
267
+ - type: ndcg_at_3
268
+ value: 49.977
269
+ - type: ndcg_at_5
270
+ value: 51.964999999999996
271
+ - type: precision_at_1
272
+ value: 45.494
273
+ - type: precision_at_10
274
+ value: 10.558
275
+ - type: precision_at_100
276
+ value: 1.6049999999999998
277
+ - type: precision_at_1000
278
+ value: 0.203
279
+ - type: precision_at_3
280
+ value: 23.796
281
+ - type: precision_at_5
282
+ value: 16.881
283
+ - type: recall_at_1
284
+ value: 36.797000000000004
285
+ - type: recall_at_10
286
+ value: 66.83
287
+ - type: recall_at_100
288
+ value: 88.34100000000001
289
+ - type: recall_at_1000
290
+ value: 97.202
291
+ - type: recall_at_3
292
+ value: 51.961999999999996
293
+ - type: recall_at_5
294
+ value: 57.940000000000005
295
+ - task:
296
+ type: Retrieval
297
+ dataset:
298
+ type: BeIR/cqadupstack
299
+ name: MTEB CQADupstackEnglishRetrieval
300
+ config: default
301
+ split: test
302
+ revision: None
303
+ metrics:
304
+ - type: map_at_1
305
+ value: 32.597
306
+ - type: map_at_10
307
+ value: 43.424
308
+ - type: map_at_100
309
+ value: 44.78
310
+ - type: map_at_1000
311
+ value: 44.913
312
+ - type: map_at_3
313
+ value: 40.315
314
+ - type: map_at_5
315
+ value: 41.987
316
+ - type: mrr_at_1
317
+ value: 40.382
318
+ - type: mrr_at_10
319
+ value: 49.219
320
+ - type: mrr_at_100
321
+ value: 49.895
322
+ - type: mrr_at_1000
323
+ value: 49.936
324
+ - type: mrr_at_3
325
+ value: 46.996
326
+ - type: mrr_at_5
327
+ value: 48.231
328
+ - type: ndcg_at_1
329
+ value: 40.382
330
+ - type: ndcg_at_10
331
+ value: 49.318
332
+ - type: ndcg_at_100
333
+ value: 53.839999999999996
334
+ - type: ndcg_at_1000
335
+ value: 55.82899999999999
336
+ - type: ndcg_at_3
337
+ value: 44.914
338
+ - type: ndcg_at_5
339
+ value: 46.798
340
+ - type: precision_at_1
341
+ value: 40.382
342
+ - type: precision_at_10
343
+ value: 9.274000000000001
344
+ - type: precision_at_100
345
+ value: 1.497
346
+ - type: precision_at_1000
347
+ value: 0.198
348
+ - type: precision_at_3
349
+ value: 21.592
350
+ - type: precision_at_5
351
+ value: 15.159
352
+ - type: recall_at_1
353
+ value: 32.597
354
+ - type: recall_at_10
355
+ value: 59.882000000000005
356
+ - type: recall_at_100
357
+ value: 78.446
358
+ - type: recall_at_1000
359
+ value: 90.88000000000001
360
+ - type: recall_at_3
361
+ value: 46.9
362
+ - type: recall_at_5
363
+ value: 52.222
364
+ - task:
365
+ type: Retrieval
366
+ dataset:
367
+ type: BeIR/cqadupstack
368
+ name: MTEB CQADupstackGamingRetrieval
369
+ config: default
370
+ split: test
371
+ revision: None
372
+ metrics:
373
+ - type: map_at_1
374
+ value: 43.8
375
+ - type: map_at_10
376
+ value: 57.293000000000006
377
+ - type: map_at_100
378
+ value: 58.321
379
+ - type: map_at_1000
380
+ value: 58.361
381
+ - type: map_at_3
382
+ value: 53.839999999999996
383
+ - type: map_at_5
384
+ value: 55.838
385
+ - type: mrr_at_1
386
+ value: 49.592000000000006
387
+ - type: mrr_at_10
388
+ value: 60.643
389
+ - type: mrr_at_100
390
+ value: 61.23499999999999
391
+ - type: mrr_at_1000
392
+ value: 61.251999999999995
393
+ - type: mrr_at_3
394
+ value: 58.265
395
+ - type: mrr_at_5
396
+ value: 59.717
397
+ - type: ndcg_at_1
398
+ value: 49.592000000000006
399
+ - type: ndcg_at_10
400
+ value: 63.364
401
+ - type: ndcg_at_100
402
+ value: 67.167
403
+ - type: ndcg_at_1000
404
+ value: 67.867
405
+ - type: ndcg_at_3
406
+ value: 57.912
407
+ - type: ndcg_at_5
408
+ value: 60.697
409
+ - type: precision_at_1
410
+ value: 49.592000000000006
411
+ - type: precision_at_10
412
+ value: 10.088
413
+ - type: precision_at_100
414
+ value: 1.2930000000000001
415
+ - type: precision_at_1000
416
+ value: 0.13899999999999998
417
+ - type: precision_at_3
418
+ value: 25.789
419
+ - type: precision_at_5
420
+ value: 17.541999999999998
421
+ - type: recall_at_1
422
+ value: 43.8
423
+ - type: recall_at_10
424
+ value: 77.635
425
+ - type: recall_at_100
426
+ value: 93.748
427
+ - type: recall_at_1000
428
+ value: 98.468
429
+ - type: recall_at_3
430
+ value: 63.223
431
+ - type: recall_at_5
432
+ value: 70.122
433
+ - task:
434
+ type: Retrieval
435
+ dataset:
436
+ type: BeIR/cqadupstack
437
+ name: MTEB CQADupstackGisRetrieval
438
+ config: default
439
+ split: test
440
+ revision: None
441
+ metrics:
442
+ - type: map_at_1
443
+ value: 27.721
444
+ - type: map_at_10
445
+ value: 35.626999999999995
446
+ - type: map_at_100
447
+ value: 36.719
448
+ - type: map_at_1000
449
+ value: 36.8
450
+ - type: map_at_3
451
+ value: 32.781
452
+ - type: map_at_5
453
+ value: 34.333999999999996
454
+ - type: mrr_at_1
455
+ value: 29.604999999999997
456
+ - type: mrr_at_10
457
+ value: 37.564
458
+ - type: mrr_at_100
459
+ value: 38.505
460
+ - type: mrr_at_1000
461
+ value: 38.565
462
+ - type: mrr_at_3
463
+ value: 34.727000000000004
464
+ - type: mrr_at_5
465
+ value: 36.207
466
+ - type: ndcg_at_1
467
+ value: 29.604999999999997
468
+ - type: ndcg_at_10
469
+ value: 40.575
470
+ - type: ndcg_at_100
471
+ value: 45.613
472
+ - type: ndcg_at_1000
473
+ value: 47.676
474
+ - type: ndcg_at_3
475
+ value: 34.811
476
+ - type: ndcg_at_5
477
+ value: 37.491
478
+ - type: precision_at_1
479
+ value: 29.604999999999997
480
+ - type: precision_at_10
481
+ value: 6.1690000000000005
482
+ - type: precision_at_100
483
+ value: 0.906
484
+ - type: precision_at_1000
485
+ value: 0.11199999999999999
486
+ - type: precision_at_3
487
+ value: 14.237
488
+ - type: precision_at_5
489
+ value: 10.056
490
+ - type: recall_at_1
491
+ value: 27.721
492
+ - type: recall_at_10
493
+ value: 54.041
494
+ - type: recall_at_100
495
+ value: 76.62299999999999
496
+ - type: recall_at_1000
497
+ value: 92.134
498
+ - type: recall_at_3
499
+ value: 38.582
500
+ - type: recall_at_5
501
+ value: 44.989000000000004
502
+ - task:
503
+ type: Retrieval
504
+ dataset:
505
+ type: BeIR/cqadupstack
506
+ name: MTEB CQADupstackMathematicaRetrieval
507
+ config: default
508
+ split: test
509
+ revision: None
510
+ metrics:
511
+ - type: map_at_1
512
+ value: 16.553
513
+ - type: map_at_10
514
+ value: 25.384
515
+ - type: map_at_100
516
+ value: 26.655
517
+ - type: map_at_1000
518
+ value: 26.778000000000002
519
+ - type: map_at_3
520
+ value: 22.733
521
+ - type: map_at_5
522
+ value: 24.119
523
+ - type: mrr_at_1
524
+ value: 20.149
525
+ - type: mrr_at_10
526
+ value: 29.705
527
+ - type: mrr_at_100
528
+ value: 30.672
529
+ - type: mrr_at_1000
530
+ value: 30.737
531
+ - type: mrr_at_3
532
+ value: 27.032
533
+ - type: mrr_at_5
534
+ value: 28.369
535
+ - type: ndcg_at_1
536
+ value: 20.149
537
+ - type: ndcg_at_10
538
+ value: 30.843999999999998
539
+ - type: ndcg_at_100
540
+ value: 36.716
541
+ - type: ndcg_at_1000
542
+ value: 39.495000000000005
543
+ - type: ndcg_at_3
544
+ value: 25.918999999999997
545
+ - type: ndcg_at_5
546
+ value: 27.992
547
+ - type: precision_at_1
548
+ value: 20.149
549
+ - type: precision_at_10
550
+ value: 5.858
551
+ - type: precision_at_100
552
+ value: 1.009
553
+ - type: precision_at_1000
554
+ value: 0.13799999999999998
555
+ - type: precision_at_3
556
+ value: 12.645000000000001
557
+ - type: precision_at_5
558
+ value: 9.179
559
+ - type: recall_at_1
560
+ value: 16.553
561
+ - type: recall_at_10
562
+ value: 43.136
563
+ - type: recall_at_100
564
+ value: 68.562
565
+ - type: recall_at_1000
566
+ value: 88.208
567
+ - type: recall_at_3
568
+ value: 29.493000000000002
569
+ - type: recall_at_5
570
+ value: 34.751
571
+ - task:
572
+ type: Retrieval
573
+ dataset:
574
+ type: BeIR/cqadupstack
575
+ name: MTEB CQADupstackPhysicsRetrieval
576
+ config: default
577
+ split: test
578
+ revision: None
579
+ metrics:
580
+ - type: map_at_1
581
+ value: 28.000999999999998
582
+ - type: map_at_10
583
+ value: 39.004
584
+ - type: map_at_100
585
+ value: 40.461999999999996
586
+ - type: map_at_1000
587
+ value: 40.566
588
+ - type: map_at_3
589
+ value: 35.805
590
+ - type: map_at_5
591
+ value: 37.672
592
+ - type: mrr_at_1
593
+ value: 33.782000000000004
594
+ - type: mrr_at_10
595
+ value: 44.702
596
+ - type: mrr_at_100
597
+ value: 45.528
598
+ - type: mrr_at_1000
599
+ value: 45.576
600
+ - type: mrr_at_3
601
+ value: 42.14
602
+ - type: mrr_at_5
603
+ value: 43.651
604
+ - type: ndcg_at_1
605
+ value: 33.782000000000004
606
+ - type: ndcg_at_10
607
+ value: 45.275999999999996
608
+ - type: ndcg_at_100
609
+ value: 50.888
610
+ - type: ndcg_at_1000
611
+ value: 52.879
612
+ - type: ndcg_at_3
613
+ value: 40.191
614
+ - type: ndcg_at_5
615
+ value: 42.731
616
+ - type: precision_at_1
617
+ value: 33.782000000000004
618
+ - type: precision_at_10
619
+ value: 8.200000000000001
620
+ - type: precision_at_100
621
+ value: 1.287
622
+ - type: precision_at_1000
623
+ value: 0.16199999999999998
624
+ - type: precision_at_3
625
+ value: 19.185
626
+ - type: precision_at_5
627
+ value: 13.667000000000002
628
+ - type: recall_at_1
629
+ value: 28.000999999999998
630
+ - type: recall_at_10
631
+ value: 58.131
632
+ - type: recall_at_100
633
+ value: 80.869
634
+ - type: recall_at_1000
635
+ value: 93.931
636
+ - type: recall_at_3
637
+ value: 44.161
638
+ - type: recall_at_5
639
+ value: 50.592000000000006
640
+ - task:
641
+ type: Retrieval
642
+ dataset:
643
+ type: BeIR/cqadupstack
644
+ name: MTEB CQADupstackProgrammersRetrieval
645
+ config: default
646
+ split: test
647
+ revision: None
648
+ metrics:
649
+ - type: map_at_1
650
+ value: 28.047
651
+ - type: map_at_10
652
+ value: 38.596000000000004
653
+ - type: map_at_100
654
+ value: 40.116
655
+ - type: map_at_1000
656
+ value: 40.232
657
+ - type: map_at_3
658
+ value: 35.205
659
+ - type: map_at_5
660
+ value: 37.076
661
+ - type: mrr_at_1
662
+ value: 34.932
663
+ - type: mrr_at_10
664
+ value: 44.496
665
+ - type: mrr_at_100
666
+ value: 45.47
667
+ - type: mrr_at_1000
668
+ value: 45.519999999999996
669
+ - type: mrr_at_3
670
+ value: 41.743
671
+ - type: mrr_at_5
672
+ value: 43.352000000000004
673
+ - type: ndcg_at_1
674
+ value: 34.932
675
+ - type: ndcg_at_10
676
+ value: 44.901
677
+ - type: ndcg_at_100
678
+ value: 50.788999999999994
679
+ - type: ndcg_at_1000
680
+ value: 52.867
681
+ - type: ndcg_at_3
682
+ value: 39.449
683
+ - type: ndcg_at_5
684
+ value: 41.929
685
+ - type: precision_at_1
686
+ value: 34.932
687
+ - type: precision_at_10
688
+ value: 8.311
689
+ - type: precision_at_100
690
+ value: 1.3050000000000002
691
+ - type: precision_at_1000
692
+ value: 0.166
693
+ - type: precision_at_3
694
+ value: 18.836
695
+ - type: precision_at_5
696
+ value: 13.447000000000001
697
+ - type: recall_at_1
698
+ value: 28.047
699
+ - type: recall_at_10
700
+ value: 57.717
701
+ - type: recall_at_100
702
+ value: 82.182
703
+ - type: recall_at_1000
704
+ value: 95.82000000000001
705
+ - type: recall_at_3
706
+ value: 42.448
707
+ - type: recall_at_5
708
+ value: 49.071
709
+ - task:
710
+ type: Retrieval
711
+ dataset:
712
+ type: BeIR/cqadupstack
713
+ name: MTEB CQADupstackRetrieval
714
+ config: default
715
+ split: test
716
+ revision: None
717
+ metrics:
718
+ - type: map_at_1
719
+ value: 27.861250000000005
720
+ - type: map_at_10
721
+ value: 37.529583333333335
722
+ - type: map_at_100
723
+ value: 38.7915
724
+ - type: map_at_1000
725
+ value: 38.90558333333335
726
+ - type: map_at_3
727
+ value: 34.57333333333333
728
+ - type: map_at_5
729
+ value: 36.187166666666656
730
+ - type: mrr_at_1
731
+ value: 32.88291666666666
732
+ - type: mrr_at_10
733
+ value: 41.79750000000001
734
+ - type: mrr_at_100
735
+ value: 42.63183333333333
736
+ - type: mrr_at_1000
737
+ value: 42.68483333333333
738
+ - type: mrr_at_3
739
+ value: 39.313750000000006
740
+ - type: mrr_at_5
741
+ value: 40.70483333333333
742
+ - type: ndcg_at_1
743
+ value: 32.88291666666666
744
+ - type: ndcg_at_10
745
+ value: 43.09408333333333
746
+ - type: ndcg_at_100
747
+ value: 48.22158333333333
748
+ - type: ndcg_at_1000
749
+ value: 50.358000000000004
750
+ - type: ndcg_at_3
751
+ value: 38.129583333333336
752
+ - type: ndcg_at_5
753
+ value: 40.39266666666666
754
+ - type: precision_at_1
755
+ value: 32.88291666666666
756
+ - type: precision_at_10
757
+ value: 7.5584999999999996
758
+ - type: precision_at_100
759
+ value: 1.1903333333333332
760
+ - type: precision_at_1000
761
+ value: 0.15658333333333332
762
+ - type: precision_at_3
763
+ value: 17.495916666666666
764
+ - type: precision_at_5
765
+ value: 12.373833333333332
766
+ - type: recall_at_1
767
+ value: 27.861250000000005
768
+ - type: recall_at_10
769
+ value: 55.215916666666665
770
+ - type: recall_at_100
771
+ value: 77.392
772
+ - type: recall_at_1000
773
+ value: 92.04908333333334
774
+ - type: recall_at_3
775
+ value: 41.37475
776
+ - type: recall_at_5
777
+ value: 47.22908333333333
778
+ - task:
779
+ type: Retrieval
780
+ dataset:
781
+ type: BeIR/cqadupstack
782
+ name: MTEB CQADupstackStatsRetrieval
783
+ config: default
784
+ split: test
785
+ revision: None
786
+ metrics:
787
+ - type: map_at_1
788
+ value: 25.064999999999998
789
+ - type: map_at_10
790
+ value: 31.635999999999996
791
+ - type: map_at_100
792
+ value: 32.596000000000004
793
+ - type: map_at_1000
794
+ value: 32.695
795
+ - type: map_at_3
796
+ value: 29.612
797
+ - type: map_at_5
798
+ value: 30.768
799
+ - type: mrr_at_1
800
+ value: 28.528
801
+ - type: mrr_at_10
802
+ value: 34.717
803
+ - type: mrr_at_100
804
+ value: 35.558
805
+ - type: mrr_at_1000
806
+ value: 35.626000000000005
807
+ - type: mrr_at_3
808
+ value: 32.745000000000005
809
+ - type: mrr_at_5
810
+ value: 33.819
811
+ - type: ndcg_at_1
812
+ value: 28.528
813
+ - type: ndcg_at_10
814
+ value: 35.647
815
+ - type: ndcg_at_100
816
+ value: 40.207
817
+ - type: ndcg_at_1000
818
+ value: 42.695
819
+ - type: ndcg_at_3
820
+ value: 31.878
821
+ - type: ndcg_at_5
822
+ value: 33.634
823
+ - type: precision_at_1
824
+ value: 28.528
825
+ - type: precision_at_10
826
+ value: 5.46
827
+ - type: precision_at_100
828
+ value: 0.84
829
+ - type: precision_at_1000
830
+ value: 0.11399999999999999
831
+ - type: precision_at_3
832
+ value: 13.547999999999998
833
+ - type: precision_at_5
834
+ value: 9.325
835
+ - type: recall_at_1
836
+ value: 25.064999999999998
837
+ - type: recall_at_10
838
+ value: 45.096000000000004
839
+ - type: recall_at_100
840
+ value: 65.658
841
+ - type: recall_at_1000
842
+ value: 84.128
843
+ - type: recall_at_3
844
+ value: 34.337
845
+ - type: recall_at_5
846
+ value: 38.849000000000004
847
+ - task:
848
+ type: Retrieval
849
+ dataset:
850
+ type: BeIR/cqadupstack
851
+ name: MTEB CQADupstackTexRetrieval
852
+ config: default
853
+ split: test
854
+ revision: None
855
+ metrics:
856
+ - type: map_at_1
857
+ value: 17.276
858
+ - type: map_at_10
859
+ value: 24.535
860
+ - type: map_at_100
861
+ value: 25.655
862
+ - type: map_at_1000
863
+ value: 25.782
864
+ - type: map_at_3
865
+ value: 22.228
866
+ - type: map_at_5
867
+ value: 23.612
868
+ - type: mrr_at_1
869
+ value: 21.266
870
+ - type: mrr_at_10
871
+ value: 28.474
872
+ - type: mrr_at_100
873
+ value: 29.398000000000003
874
+ - type: mrr_at_1000
875
+ value: 29.482000000000003
876
+ - type: mrr_at_3
877
+ value: 26.245
878
+ - type: mrr_at_5
879
+ value: 27.624
880
+ - type: ndcg_at_1
881
+ value: 21.266
882
+ - type: ndcg_at_10
883
+ value: 29.087000000000003
884
+ - type: ndcg_at_100
885
+ value: 34.374
886
+ - type: ndcg_at_1000
887
+ value: 37.433
888
+ - type: ndcg_at_3
889
+ value: 25.040000000000003
890
+ - type: ndcg_at_5
891
+ value: 27.116
892
+ - type: precision_at_1
893
+ value: 21.266
894
+ - type: precision_at_10
895
+ value: 5.258
896
+ - type: precision_at_100
897
+ value: 0.9299999999999999
898
+ - type: precision_at_1000
899
+ value: 0.13699999999999998
900
+ - type: precision_at_3
901
+ value: 11.849
902
+ - type: precision_at_5
903
+ value: 8.699
904
+ - type: recall_at_1
905
+ value: 17.276
906
+ - type: recall_at_10
907
+ value: 38.928000000000004
908
+ - type: recall_at_100
909
+ value: 62.529
910
+ - type: recall_at_1000
911
+ value: 84.44800000000001
912
+ - type: recall_at_3
913
+ value: 27.554000000000002
914
+ - type: recall_at_5
915
+ value: 32.915
916
+ - task:
917
+ type: Retrieval
918
+ dataset:
919
+ type: BeIR/cqadupstack
920
+ name: MTEB CQADupstackUnixRetrieval
921
+ config: default
922
+ split: test
923
+ revision: None
924
+ metrics:
925
+ - type: map_at_1
926
+ value: 27.297
927
+ - type: map_at_10
928
+ value: 36.957
929
+ - type: map_at_100
930
+ value: 38.252
931
+ - type: map_at_1000
932
+ value: 38.356
933
+ - type: map_at_3
934
+ value: 34.121
935
+ - type: map_at_5
936
+ value: 35.782000000000004
937
+ - type: mrr_at_1
938
+ value: 32.275999999999996
939
+ - type: mrr_at_10
940
+ value: 41.198
941
+ - type: mrr_at_100
942
+ value: 42.131
943
+ - type: mrr_at_1000
944
+ value: 42.186
945
+ - type: mrr_at_3
946
+ value: 38.557
947
+ - type: mrr_at_5
948
+ value: 40.12
949
+ - type: ndcg_at_1
950
+ value: 32.275999999999996
951
+ - type: ndcg_at_10
952
+ value: 42.516
953
+ - type: ndcg_at_100
954
+ value: 48.15
955
+ - type: ndcg_at_1000
956
+ value: 50.344
957
+ - type: ndcg_at_3
958
+ value: 37.423
959
+ - type: ndcg_at_5
960
+ value: 39.919
961
+ - type: precision_at_1
962
+ value: 32.275999999999996
963
+ - type: precision_at_10
964
+ value: 7.155
965
+ - type: precision_at_100
966
+ value: 1.123
967
+ - type: precision_at_1000
968
+ value: 0.14200000000000002
969
+ - type: precision_at_3
970
+ value: 17.163999999999998
971
+ - type: precision_at_5
972
+ value: 12.127
973
+ - type: recall_at_1
974
+ value: 27.297
975
+ - type: recall_at_10
976
+ value: 55.238
977
+ - type: recall_at_100
978
+ value: 79.2
979
+ - type: recall_at_1000
980
+ value: 94.258
981
+ - type: recall_at_3
982
+ value: 41.327000000000005
983
+ - type: recall_at_5
984
+ value: 47.588
985
+ - task:
986
+ type: Retrieval
987
+ dataset:
988
+ type: BeIR/cqadupstack
989
+ name: MTEB CQADupstackWebmastersRetrieval
990
+ config: default
991
+ split: test
992
+ revision: None
993
+ metrics:
994
+ - type: map_at_1
995
+ value: 29.142000000000003
996
+ - type: map_at_10
997
+ value: 38.769
998
+ - type: map_at_100
999
+ value: 40.292
1000
+ - type: map_at_1000
1001
+ value: 40.510000000000005
1002
+ - type: map_at_3
1003
+ value: 35.39
1004
+ - type: map_at_5
1005
+ value: 37.009
1006
+ - type: mrr_at_1
1007
+ value: 34.19
1008
+ - type: mrr_at_10
1009
+ value: 43.418
1010
+ - type: mrr_at_100
1011
+ value: 44.132
1012
+ - type: mrr_at_1000
1013
+ value: 44.175
1014
+ - type: mrr_at_3
1015
+ value: 40.547
1016
+ - type: mrr_at_5
1017
+ value: 42.088
1018
+ - type: ndcg_at_1
1019
+ value: 34.19
1020
+ - type: ndcg_at_10
1021
+ value: 45.14
1022
+ - type: ndcg_at_100
1023
+ value: 50.364
1024
+ - type: ndcg_at_1000
1025
+ value: 52.481
1026
+ - type: ndcg_at_3
1027
+ value: 39.466
1028
+ - type: ndcg_at_5
1029
+ value: 41.772
1030
+ - type: precision_at_1
1031
+ value: 34.19
1032
+ - type: precision_at_10
1033
+ value: 8.715
1034
+ - type: precision_at_100
1035
+ value: 1.6150000000000002
1036
+ - type: precision_at_1000
1037
+ value: 0.247
1038
+ - type: precision_at_3
1039
+ value: 18.248
1040
+ - type: precision_at_5
1041
+ value: 13.161999999999999
1042
+ - type: recall_at_1
1043
+ value: 29.142000000000003
1044
+ - type: recall_at_10
1045
+ value: 57.577999999999996
1046
+ - type: recall_at_100
1047
+ value: 81.428
1048
+ - type: recall_at_1000
1049
+ value: 94.017
1050
+ - type: recall_at_3
1051
+ value: 41.402
1052
+ - type: recall_at_5
1053
+ value: 47.695
1054
+ - task:
1055
+ type: Retrieval
1056
+ dataset:
1057
+ type: BeIR/cqadupstack
1058
+ name: MTEB CQADupstackWordpressRetrieval
1059
+ config: default
1060
+ split: test
1061
+ revision: None
1062
+ metrics:
1063
+ - type: map_at_1
1064
+ value: 22.039
1065
+ - type: map_at_10
1066
+ value: 30.669999999999998
1067
+ - type: map_at_100
1068
+ value: 31.682
1069
+ - type: map_at_1000
1070
+ value: 31.794
1071
+ - type: map_at_3
1072
+ value: 28.139999999999997
1073
+ - type: map_at_5
1074
+ value: 29.457
1075
+ - type: mrr_at_1
1076
+ value: 24.399
1077
+ - type: mrr_at_10
1078
+ value: 32.687
1079
+ - type: mrr_at_100
1080
+ value: 33.622
1081
+ - type: mrr_at_1000
1082
+ value: 33.698
1083
+ - type: mrr_at_3
1084
+ value: 30.407
1085
+ - type: mrr_at_5
1086
+ value: 31.552999999999997
1087
+ - type: ndcg_at_1
1088
+ value: 24.399
1089
+ - type: ndcg_at_10
1090
+ value: 35.472
1091
+ - type: ndcg_at_100
1092
+ value: 40.455000000000005
1093
+ - type: ndcg_at_1000
1094
+ value: 43.15
1095
+ - type: ndcg_at_3
1096
+ value: 30.575000000000003
1097
+ - type: ndcg_at_5
1098
+ value: 32.668
1099
+ - type: precision_at_1
1100
+ value: 24.399
1101
+ - type: precision_at_10
1102
+ value: 5.656
1103
+ - type: precision_at_100
1104
+ value: 0.874
1105
+ - type: precision_at_1000
1106
+ value: 0.121
1107
+ - type: precision_at_3
1108
+ value: 13.062000000000001
1109
+ - type: precision_at_5
1110
+ value: 9.242
1111
+ - type: recall_at_1
1112
+ value: 22.039
1113
+ - type: recall_at_10
1114
+ value: 48.379
1115
+ - type: recall_at_100
1116
+ value: 71.11800000000001
1117
+ - type: recall_at_1000
1118
+ value: 91.095
1119
+ - type: recall_at_3
1120
+ value: 35.108
1121
+ - type: recall_at_5
1122
+ value: 40.015
1123
+ - task:
1124
+ type: Retrieval
1125
+ dataset:
1126
+ type: climate-fever
1127
+ name: MTEB ClimateFEVER
1128
+ config: default
1129
+ split: test
1130
+ revision: None
1131
+ metrics:
1132
+ - type: map_at_1
1133
+ value: 10.144
1134
+ - type: map_at_10
1135
+ value: 18.238
1136
+ - type: map_at_100
1137
+ value: 20.143
1138
+ - type: map_at_1000
1139
+ value: 20.346
1140
+ - type: map_at_3
1141
+ value: 14.809
1142
+ - type: map_at_5
1143
+ value: 16.567999999999998
1144
+ - type: mrr_at_1
1145
+ value: 22.671
1146
+ - type: mrr_at_10
1147
+ value: 34.906
1148
+ - type: mrr_at_100
1149
+ value: 35.858000000000004
1150
+ - type: mrr_at_1000
1151
+ value: 35.898
1152
+ - type: mrr_at_3
1153
+ value: 31.238
1154
+ - type: mrr_at_5
1155
+ value: 33.342
1156
+ - type: ndcg_at_1
1157
+ value: 22.671
1158
+ - type: ndcg_at_10
1159
+ value: 26.540000000000003
1160
+ - type: ndcg_at_100
1161
+ value: 34.138000000000005
1162
+ - type: ndcg_at_1000
1163
+ value: 37.72
1164
+ - type: ndcg_at_3
1165
+ value: 20.766000000000002
1166
+ - type: ndcg_at_5
1167
+ value: 22.927
1168
+ - type: precision_at_1
1169
+ value: 22.671
1170
+ - type: precision_at_10
1171
+ value: 8.619
1172
+ - type: precision_at_100
1173
+ value: 1.678
1174
+ - type: precision_at_1000
1175
+ value: 0.23500000000000001
1176
+ - type: precision_at_3
1177
+ value: 15.592
1178
+ - type: precision_at_5
1179
+ value: 12.43
1180
+ - type: recall_at_1
1181
+ value: 10.144
1182
+ - type: recall_at_10
1183
+ value: 33.46
1184
+ - type: recall_at_100
1185
+ value: 59.758
1186
+ - type: recall_at_1000
1187
+ value: 79.704
1188
+ - type: recall_at_3
1189
+ value: 19.604
1190
+ - type: recall_at_5
1191
+ value: 25.367
1192
+ - task:
1193
+ type: Retrieval
1194
+ dataset:
1195
+ type: dbpedia-entity
1196
+ name: MTEB DBPedia
1197
+ config: default
1198
+ split: test
1199
+ revision: None
1200
+ metrics:
1201
+ - type: map_at_1
1202
+ value: 8.654
1203
+ - type: map_at_10
1204
+ value: 18.506
1205
+ - type: map_at_100
1206
+ value: 26.412999999999997
1207
+ - type: map_at_1000
1208
+ value: 28.13
1209
+ - type: map_at_3
1210
+ value: 13.379
1211
+ - type: map_at_5
1212
+ value: 15.529000000000002
1213
+ - type: mrr_at_1
1214
+ value: 66.0
1215
+ - type: mrr_at_10
1216
+ value: 74.13
1217
+ - type: mrr_at_100
1218
+ value: 74.48700000000001
1219
+ - type: mrr_at_1000
1220
+ value: 74.49799999999999
1221
+ - type: mrr_at_3
1222
+ value: 72.75
1223
+ - type: mrr_at_5
1224
+ value: 73.762
1225
+ - type: ndcg_at_1
1226
+ value: 54.50000000000001
1227
+ - type: ndcg_at_10
1228
+ value: 40.236
1229
+ - type: ndcg_at_100
1230
+ value: 44.690999999999995
1231
+ - type: ndcg_at_1000
1232
+ value: 52.195
1233
+ - type: ndcg_at_3
1234
+ value: 45.632
1235
+ - type: ndcg_at_5
1236
+ value: 42.952
1237
+ - type: precision_at_1
1238
+ value: 66.0
1239
+ - type: precision_at_10
1240
+ value: 31.724999999999998
1241
+ - type: precision_at_100
1242
+ value: 10.299999999999999
1243
+ - type: precision_at_1000
1244
+ value: 2.194
1245
+ - type: precision_at_3
1246
+ value: 48.75
1247
+ - type: precision_at_5
1248
+ value: 41.6
1249
+ - type: recall_at_1
1250
+ value: 8.654
1251
+ - type: recall_at_10
1252
+ value: 23.74
1253
+ - type: recall_at_100
1254
+ value: 50.346999999999994
1255
+ - type: recall_at_1000
1256
+ value: 74.376
1257
+ - type: recall_at_3
1258
+ value: 14.636
1259
+ - type: recall_at_5
1260
+ value: 18.009
1261
+ - task:
1262
+ type: Classification
1263
+ dataset:
1264
+ type: mteb/emotion
1265
+ name: MTEB EmotionClassification
1266
+ config: default
1267
+ split: test
1268
+ revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
1269
+ metrics:
1270
+ - type: accuracy
1271
+ value: 53.245
1272
+ - type: f1
1273
+ value: 48.74520523753552
1274
+ - task:
1275
+ type: Retrieval
1276
+ dataset:
1277
+ type: fever
1278
+ name: MTEB FEVER
1279
+ config: default
1280
+ split: test
1281
+ revision: None
1282
+ metrics:
1283
+ - type: map_at_1
1284
+ value: 51.729
1285
+ - type: map_at_10
1286
+ value: 63.904
1287
+ - type: map_at_100
1288
+ value: 64.363
1289
+ - type: map_at_1000
1290
+ value: 64.38199999999999
1291
+ - type: map_at_3
1292
+ value: 61.393
1293
+ - type: map_at_5
1294
+ value: 63.02100000000001
1295
+ - type: mrr_at_1
1296
+ value: 55.686
1297
+ - type: mrr_at_10
1298
+ value: 67.804
1299
+ - type: mrr_at_100
1300
+ value: 68.15299999999999
1301
+ - type: mrr_at_1000
1302
+ value: 68.161
1303
+ - type: mrr_at_3
1304
+ value: 65.494
1305
+ - type: mrr_at_5
1306
+ value: 67.01599999999999
1307
+ - type: ndcg_at_1
1308
+ value: 55.686
1309
+ - type: ndcg_at_10
1310
+ value: 70.025
1311
+ - type: ndcg_at_100
1312
+ value: 72.011
1313
+ - type: ndcg_at_1000
1314
+ value: 72.443
1315
+ - type: ndcg_at_3
1316
+ value: 65.32900000000001
1317
+ - type: ndcg_at_5
1318
+ value: 68.05600000000001
1319
+ - type: precision_at_1
1320
+ value: 55.686
1321
+ - type: precision_at_10
1322
+ value: 9.358
1323
+ - type: precision_at_100
1324
+ value: 1.05
1325
+ - type: precision_at_1000
1326
+ value: 0.11
1327
+ - type: precision_at_3
1328
+ value: 26.318
1329
+ - type: precision_at_5
1330
+ value: 17.321
1331
+ - type: recall_at_1
1332
+ value: 51.729
1333
+ - type: recall_at_10
1334
+ value: 85.04
1335
+ - type: recall_at_100
1336
+ value: 93.777
1337
+ - type: recall_at_1000
1338
+ value: 96.824
1339
+ - type: recall_at_3
1340
+ value: 72.521
1341
+ - type: recall_at_5
1342
+ value: 79.148
1343
+ - task:
1344
+ type: Retrieval
1345
+ dataset:
1346
+ type: fiqa
1347
+ name: MTEB FiQA2018
1348
+ config: default
1349
+ split: test
1350
+ revision: None
1351
+ metrics:
1352
+ - type: map_at_1
1353
+ value: 23.765
1354
+ - type: map_at_10
1355
+ value: 39.114
1356
+ - type: map_at_100
1357
+ value: 40.987
1358
+ - type: map_at_1000
1359
+ value: 41.155
1360
+ - type: map_at_3
1361
+ value: 34.028000000000006
1362
+ - type: map_at_5
1363
+ value: 36.925000000000004
1364
+ - type: mrr_at_1
1365
+ value: 46.451
1366
+ - type: mrr_at_10
1367
+ value: 54.711
1368
+ - type: mrr_at_100
1369
+ value: 55.509
1370
+ - type: mrr_at_1000
1371
+ value: 55.535000000000004
1372
+ - type: mrr_at_3
1373
+ value: 52.649
1374
+ - type: mrr_at_5
1375
+ value: 53.729000000000006
1376
+ - type: ndcg_at_1
1377
+ value: 46.451
1378
+ - type: ndcg_at_10
1379
+ value: 46.955999999999996
1380
+ - type: ndcg_at_100
1381
+ value: 53.686
1382
+ - type: ndcg_at_1000
1383
+ value: 56.230000000000004
1384
+ - type: ndcg_at_3
1385
+ value: 43.374
1386
+ - type: ndcg_at_5
1387
+ value: 44.372
1388
+ - type: precision_at_1
1389
+ value: 46.451
1390
+ - type: precision_at_10
1391
+ value: 13.256
1392
+ - type: precision_at_100
1393
+ value: 2.019
1394
+ - type: precision_at_1000
1395
+ value: 0.247
1396
+ - type: precision_at_3
1397
+ value: 29.115000000000002
1398
+ - type: precision_at_5
1399
+ value: 21.389
1400
+ - type: recall_at_1
1401
+ value: 23.765
1402
+ - type: recall_at_10
1403
+ value: 53.452999999999996
1404
+ - type: recall_at_100
1405
+ value: 78.828
1406
+ - type: recall_at_1000
1407
+ value: 93.938
1408
+ - type: recall_at_3
1409
+ value: 39.023
1410
+ - type: recall_at_5
1411
+ value: 45.18
1412
+ - task:
1413
+ type: Retrieval
1414
+ dataset:
1415
+ type: hotpotqa
1416
+ name: MTEB HotpotQA
1417
+ config: default
1418
+ split: test
1419
+ revision: None
1420
+ metrics:
1421
+ - type: map_at_1
1422
+ value: 31.918000000000003
1423
+ - type: map_at_10
1424
+ value: 46.741
1425
+ - type: map_at_100
1426
+ value: 47.762
1427
+ - type: map_at_1000
1428
+ value: 47.849000000000004
1429
+ - type: map_at_3
1430
+ value: 43.578
1431
+ - type: map_at_5
1432
+ value: 45.395
1433
+ - type: mrr_at_1
1434
+ value: 63.834999999999994
1435
+ - type: mrr_at_10
1436
+ value: 71.312
1437
+ - type: mrr_at_100
1438
+ value: 71.695
1439
+ - type: mrr_at_1000
1440
+ value: 71.714
1441
+ - type: mrr_at_3
1442
+ value: 69.82000000000001
1443
+ - type: mrr_at_5
1444
+ value: 70.726
1445
+ - type: ndcg_at_1
1446
+ value: 63.834999999999994
1447
+ - type: ndcg_at_10
1448
+ value: 55.879999999999995
1449
+ - type: ndcg_at_100
1450
+ value: 59.723000000000006
1451
+ - type: ndcg_at_1000
1452
+ value: 61.49400000000001
1453
+ - type: ndcg_at_3
1454
+ value: 50.964
1455
+ - type: ndcg_at_5
1456
+ value: 53.47
1457
+ - type: precision_at_1
1458
+ value: 63.834999999999994
1459
+ - type: precision_at_10
1460
+ value: 11.845
1461
+ - type: precision_at_100
1462
+ value: 1.4869999999999999
1463
+ - type: precision_at_1000
1464
+ value: 0.172
1465
+ - type: precision_at_3
1466
+ value: 32.158
1467
+ - type: precision_at_5
1468
+ value: 21.278
1469
+ - type: recall_at_1
1470
+ value: 31.918000000000003
1471
+ - type: recall_at_10
1472
+ value: 59.223000000000006
1473
+ - type: recall_at_100
1474
+ value: 74.328
1475
+ - type: recall_at_1000
1476
+ value: 86.05000000000001
1477
+ - type: recall_at_3
1478
+ value: 48.238
1479
+ - type: recall_at_5
1480
+ value: 53.193999999999996
1481
+ - task:
1482
+ type: Classification
1483
+ dataset:
1484
+ type: mteb/imdb
1485
+ name: MTEB ImdbClassification
1486
+ config: default
1487
+ split: test
1488
+ revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
1489
+ metrics:
1490
+ - type: accuracy
1491
+ value: 79.7896
1492
+ - type: ap
1493
+ value: 73.65166029460288
1494
+ - type: f1
1495
+ value: 79.71794693711813
1496
+ - task:
1497
+ type: Retrieval
1498
+ dataset:
1499
+ type: msmarco
1500
+ name: MTEB MSMARCO
1501
+ config: default
1502
+ split: dev
1503
+ revision: None
1504
+ metrics:
1505
+ - type: map_at_1
1506
+ value: 22.239
1507
+ - type: map_at_10
1508
+ value: 34.542
1509
+ - type: map_at_100
1510
+ value: 35.717999999999996
1511
+ - type: map_at_1000
1512
+ value: 35.764
1513
+ - type: map_at_3
1514
+ value: 30.432
1515
+ - type: map_at_5
1516
+ value: 32.81
1517
+ - type: mrr_at_1
1518
+ value: 22.908
1519
+ - type: mrr_at_10
1520
+ value: 35.127
1521
+ - type: mrr_at_100
1522
+ value: 36.238
1523
+ - type: mrr_at_1000
1524
+ value: 36.278
1525
+ - type: mrr_at_3
1526
+ value: 31.076999999999998
1527
+ - type: mrr_at_5
1528
+ value: 33.419
1529
+ - type: ndcg_at_1
1530
+ value: 22.908
1531
+ - type: ndcg_at_10
1532
+ value: 41.607
1533
+ - type: ndcg_at_100
1534
+ value: 47.28
1535
+ - type: ndcg_at_1000
1536
+ value: 48.414
1537
+ - type: ndcg_at_3
1538
+ value: 33.253
1539
+ - type: ndcg_at_5
1540
+ value: 37.486000000000004
1541
+ - type: precision_at_1
1542
+ value: 22.908
1543
+ - type: precision_at_10
1544
+ value: 6.645
1545
+ - type: precision_at_100
1546
+ value: 0.9490000000000001
1547
+ - type: precision_at_1000
1548
+ value: 0.105
1549
+ - type: precision_at_3
1550
+ value: 14.130999999999998
1551
+ - type: precision_at_5
1552
+ value: 10.616
1553
+ - type: recall_at_1
1554
+ value: 22.239
1555
+ - type: recall_at_10
1556
+ value: 63.42
1557
+ - type: recall_at_100
1558
+ value: 89.696
1559
+ - type: recall_at_1000
1560
+ value: 98.351
1561
+ - type: recall_at_3
1562
+ value: 40.77
1563
+ - type: recall_at_5
1564
+ value: 50.93
1565
+ - task:
1566
+ type: Classification
1567
+ dataset:
1568
+ type: mteb/mtop_domain
1569
+ name: MTEB MTOPDomainClassification (en)
1570
+ config: en
1571
+ split: test
1572
+ revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
1573
+ metrics:
1574
+ - type: accuracy
1575
+ value: 95.06839945280439
1576
+ - type: f1
1577
+ value: 94.74276398224072
1578
+ - task:
1579
+ type: Classification
1580
+ dataset:
1581
+ type: mteb/mtop_intent
1582
+ name: MTEB MTOPIntentClassification (en)
1583
+ config: en
1584
+ split: test
1585
+ revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1586
+ metrics:
1587
+ - type: accuracy
1588
+ value: 72.25718194254446
1589
+ - type: f1
1590
+ value: 53.91164489161391
1591
+ - task:
1592
+ type: Classification
1593
+ dataset:
1594
+ type: mteb/amazon_massive_intent
1595
+ name: MTEB MassiveIntentClassification (en)
1596
+ config: en
1597
+ split: test
1598
+ revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
1599
+ metrics:
1600
+ - type: accuracy
1601
+ value: 71.47948890383323
1602
+ - type: f1
1603
+ value: 69.98520247230257
1604
+ - task:
1605
+ type: Classification
1606
+ dataset:
1607
+ type: mteb/amazon_massive_scenario
1608
+ name: MTEB MassiveScenarioClassification (en)
1609
+ config: en
1610
+ split: test
1611
+ revision: 7d571f92784cd94a019292a1f45445077d0ef634
1612
+ metrics:
1613
+ - type: accuracy
1614
+ value: 76.46603900470748
1615
+ - type: f1
1616
+ value: 76.44111526065399
1617
+ - task:
1618
+ type: Clustering
1619
+ dataset:
1620
+ type: mteb/medrxiv-clustering-p2p
1621
+ name: MTEB MedrxivClusteringP2P
1622
+ config: default
1623
+ split: test
1624
+ revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
1625
+ metrics:
1626
+ - type: v_measure
1627
+ value: 33.19106070798198
1628
+ - task:
1629
+ type: Clustering
1630
+ dataset:
1631
+ type: mteb/medrxiv-clustering-s2s
1632
+ name: MTEB MedrxivClusteringS2S
1633
+ config: default
1634
+ split: test
1635
+ revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
1636
+ metrics:
1637
+ - type: v_measure
1638
+ value: 30.78772205248094
1639
+ - task:
1640
+ type: Reranking
1641
+ dataset:
1642
+ type: mteb/mind_small
1643
+ name: MTEB MindSmallReranking
1644
+ config: default
1645
+ split: test
1646
+ revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
1647
+ metrics:
1648
+ - type: map
1649
+ value: 31.811231631488507
1650
+ - type: mrr
1651
+ value: 32.98200485378021
1652
+ - task:
1653
+ type: Retrieval
1654
+ dataset:
1655
+ type: nfcorpus
1656
+ name: MTEB NFCorpus
1657
+ config: default
1658
+ split: test
1659
+ revision: None
1660
+ metrics:
1661
+ - type: map_at_1
1662
+ value: 6.9
1663
+ - type: map_at_10
1664
+ value: 13.703000000000001
1665
+ - type: map_at_100
1666
+ value: 17.251
1667
+ - type: map_at_1000
1668
+ value: 18.795
1669
+ - type: map_at_3
1670
+ value: 10.366999999999999
1671
+ - type: map_at_5
1672
+ value: 11.675
1673
+ - type: mrr_at_1
1674
+ value: 47.059
1675
+ - type: mrr_at_10
1676
+ value: 55.816
1677
+ - type: mrr_at_100
1678
+ value: 56.434
1679
+ - type: mrr_at_1000
1680
+ value: 56.467
1681
+ - type: mrr_at_3
1682
+ value: 53.973000000000006
1683
+ - type: mrr_at_5
1684
+ value: 55.257999999999996
1685
+ - type: ndcg_at_1
1686
+ value: 44.737
1687
+ - type: ndcg_at_10
1688
+ value: 35.997
1689
+ - type: ndcg_at_100
1690
+ value: 33.487
1691
+ - type: ndcg_at_1000
1692
+ value: 41.897
1693
+ - type: ndcg_at_3
1694
+ value: 41.18
1695
+ - type: ndcg_at_5
1696
+ value: 38.721
1697
+ - type: precision_at_1
1698
+ value: 46.129999999999995
1699
+ - type: precision_at_10
1700
+ value: 26.533
1701
+ - type: precision_at_100
1702
+ value: 8.706
1703
+ - type: precision_at_1000
1704
+ value: 2.16
1705
+ - type: precision_at_3
1706
+ value: 38.493
1707
+ - type: precision_at_5
1708
+ value: 33.189
1709
+ - type: recall_at_1
1710
+ value: 6.9
1711
+ - type: recall_at_10
1712
+ value: 17.488999999999997
1713
+ - type: recall_at_100
1714
+ value: 34.583000000000006
1715
+ - type: recall_at_1000
1716
+ value: 64.942
1717
+ - type: recall_at_3
1718
+ value: 11.494
1719
+ - type: recall_at_5
1720
+ value: 13.496
1721
+ - task:
1722
+ type: Retrieval
1723
+ dataset:
1724
+ type: nq
1725
+ name: MTEB NQ
1726
+ config: default
1727
+ split: test
1728
+ revision: None
1729
+ metrics:
1730
+ - type: map_at_1
1731
+ value: 33.028999999999996
1732
+ - type: map_at_10
1733
+ value: 49.307
1734
+ - type: map_at_100
1735
+ value: 50.205
1736
+ - type: map_at_1000
1737
+ value: 50.23
1738
+ - type: map_at_3
1739
+ value: 44.782
1740
+ - type: map_at_5
1741
+ value: 47.599999999999994
1742
+ - type: mrr_at_1
1743
+ value: 37.108999999999995
1744
+ - type: mrr_at_10
1745
+ value: 51.742999999999995
1746
+ - type: mrr_at_100
1747
+ value: 52.405
1748
+ - type: mrr_at_1000
1749
+ value: 52.422000000000004
1750
+ - type: mrr_at_3
1751
+ value: 48.087999999999994
1752
+ - type: mrr_at_5
1753
+ value: 50.414
1754
+ - type: ndcg_at_1
1755
+ value: 37.08
1756
+ - type: ndcg_at_10
1757
+ value: 57.236
1758
+ - type: ndcg_at_100
1759
+ value: 60.931999999999995
1760
+ - type: ndcg_at_1000
1761
+ value: 61.522
1762
+ - type: ndcg_at_3
1763
+ value: 48.93
1764
+ - type: ndcg_at_5
1765
+ value: 53.561
1766
+ - type: precision_at_1
1767
+ value: 37.08
1768
+ - type: precision_at_10
1769
+ value: 9.386
1770
+ - type: precision_at_100
1771
+ value: 1.1480000000000001
1772
+ - type: precision_at_1000
1773
+ value: 0.12
1774
+ - type: precision_at_3
1775
+ value: 22.258
1776
+ - type: precision_at_5
1777
+ value: 16.025
1778
+ - type: recall_at_1
1779
+ value: 33.028999999999996
1780
+ - type: recall_at_10
1781
+ value: 78.805
1782
+ - type: recall_at_100
1783
+ value: 94.643
1784
+ - type: recall_at_1000
1785
+ value: 99.039
1786
+ - type: recall_at_3
1787
+ value: 57.602
1788
+ - type: recall_at_5
1789
+ value: 68.253
1790
+ - task:
1791
+ type: Retrieval
1792
+ dataset:
1793
+ type: quora
1794
+ name: MTEB QuoraRetrieval
1795
+ config: default
1796
+ split: test
1797
+ revision: None
1798
+ metrics:
1799
+ - type: map_at_1
1800
+ value: 71.122
1801
+ - type: map_at_10
1802
+ value: 85.237
1803
+ - type: map_at_100
1804
+ value: 85.872
1805
+ - type: map_at_1000
1806
+ value: 85.885
1807
+ - type: map_at_3
1808
+ value: 82.27499999999999
1809
+ - type: map_at_5
1810
+ value: 84.13199999999999
1811
+ - type: mrr_at_1
1812
+ value: 81.73
1813
+ - type: mrr_at_10
1814
+ value: 87.834
1815
+ - type: mrr_at_100
1816
+ value: 87.92
1817
+ - type: mrr_at_1000
1818
+ value: 87.921
1819
+ - type: mrr_at_3
1820
+ value: 86.878
1821
+ - type: mrr_at_5
1822
+ value: 87.512
1823
+ - type: ndcg_at_1
1824
+ value: 81.73
1825
+ - type: ndcg_at_10
1826
+ value: 88.85499999999999
1827
+ - type: ndcg_at_100
1828
+ value: 89.992
1829
+ - type: ndcg_at_1000
1830
+ value: 90.07
1831
+ - type: ndcg_at_3
1832
+ value: 85.997
1833
+ - type: ndcg_at_5
1834
+ value: 87.55199999999999
1835
+ - type: precision_at_1
1836
+ value: 81.73
1837
+ - type: precision_at_10
1838
+ value: 13.491
1839
+ - type: precision_at_100
1840
+ value: 1.536
1841
+ - type: precision_at_1000
1842
+ value: 0.157
1843
+ - type: precision_at_3
1844
+ value: 37.623
1845
+ - type: precision_at_5
1846
+ value: 24.742
1847
+ - type: recall_at_1
1848
+ value: 71.122
1849
+ - type: recall_at_10
1850
+ value: 95.935
1851
+ - type: recall_at_100
1852
+ value: 99.657
1853
+ - type: recall_at_1000
1854
+ value: 99.996
1855
+ - type: recall_at_3
1856
+ value: 87.80799999999999
1857
+ - type: recall_at_5
1858
+ value: 92.161
1859
+ - task:
1860
+ type: Clustering
1861
+ dataset:
1862
+ type: mteb/reddit-clustering
1863
+ name: MTEB RedditClustering
1864
+ config: default
1865
+ split: test
1866
+ revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
1867
+ metrics:
1868
+ - type: v_measure
1869
+ value: 63.490029238193756
1870
+ - task:
1871
+ type: Clustering
1872
+ dataset:
1873
+ type: mteb/reddit-clustering-p2p
1874
+ name: MTEB RedditClusteringP2P
1875
+ config: default
1876
+ split: test
1877
+ revision: 282350215ef01743dc01b456c7f5241fa8937f16
1878
+ metrics:
1879
+ - type: v_measure
1880
+ value: 65.13153408508836
1881
+ - task:
1882
+ type: Retrieval
1883
+ dataset:
1884
+ type: scidocs
1885
+ name: MTEB SCIDOCS
1886
+ config: default
1887
+ split: test
1888
+ revision: None
1889
+ metrics:
1890
+ - type: map_at_1
1891
+ value: 4.202999999999999
1892
+ - type: map_at_10
1893
+ value: 10.174
1894
+ - type: map_at_100
1895
+ value: 12.138
1896
+ - type: map_at_1000
1897
+ value: 12.418
1898
+ - type: map_at_3
1899
+ value: 7.379
1900
+ - type: map_at_5
1901
+ value: 8.727
1902
+ - type: mrr_at_1
1903
+ value: 20.7
1904
+ - type: mrr_at_10
1905
+ value: 30.389
1906
+ - type: mrr_at_100
1907
+ value: 31.566
1908
+ - type: mrr_at_1000
1909
+ value: 31.637999999999998
1910
+ - type: mrr_at_3
1911
+ value: 27.133000000000003
1912
+ - type: mrr_at_5
1913
+ value: 29.078
1914
+ - type: ndcg_at_1
1915
+ value: 20.7
1916
+ - type: ndcg_at_10
1917
+ value: 17.355999999999998
1918
+ - type: ndcg_at_100
1919
+ value: 25.151
1920
+ - type: ndcg_at_1000
1921
+ value: 30.37
1922
+ - type: ndcg_at_3
1923
+ value: 16.528000000000002
1924
+ - type: ndcg_at_5
1925
+ value: 14.396999999999998
1926
+ - type: precision_at_1
1927
+ value: 20.7
1928
+ - type: precision_at_10
1929
+ value: 8.98
1930
+ - type: precision_at_100
1931
+ value: 2.015
1932
+ - type: precision_at_1000
1933
+ value: 0.327
1934
+ - type: precision_at_3
1935
+ value: 15.367
1936
+ - type: precision_at_5
1937
+ value: 12.559999999999999
1938
+ - type: recall_at_1
1939
+ value: 4.202999999999999
1940
+ - type: recall_at_10
1941
+ value: 18.197
1942
+ - type: recall_at_100
1943
+ value: 40.903
1944
+ - type: recall_at_1000
1945
+ value: 66.427
1946
+ - type: recall_at_3
1947
+ value: 9.362
1948
+ - type: recall_at_5
1949
+ value: 12.747
1950
+ - task:
1951
+ type: STS
1952
+ dataset:
1953
+ type: mteb/sickr-sts
1954
+ name: MTEB SICK-R
1955
+ config: default
1956
+ split: test
1957
+ revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
1958
+ metrics:
1959
+ - type: cos_sim_spearman
1960
+ value: 81.69890989765257
1961
+ - task:
1962
+ type: STS
1963
+ dataset:
1964
+ type: mteb/sts12-sts
1965
+ name: MTEB STS12
1966
+ config: default
1967
+ split: test
1968
+ revision: a0d554a64d88156834ff5ae9920b964011b16384
1969
+ metrics:
1970
+ - type: cos_sim_spearman
1971
+ value: 75.31953790551489
1972
+ - task:
1973
+ type: STS
1974
+ dataset:
1975
+ type: mteb/sts13-sts
1976
+ name: MTEB STS13
1977
+ config: default
1978
+ split: test
1979
+ revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
1980
+ metrics:
1981
+ - type: cos_sim_spearman
1982
+ value: 87.44050861280759
1983
+ - task:
1984
+ type: STS
1985
+ dataset:
1986
+ type: mteb/sts14-sts
1987
+ name: MTEB STS14
1988
+ config: default
1989
+ split: test
1990
+ revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
1991
+ metrics:
1992
+ - type: cos_sim_spearman
1993
+ value: 81.86922869270393
1994
+ - task:
1995
+ type: STS
1996
+ dataset:
1997
+ type: mteb/sts15-sts
1998
+ name: MTEB STS15
1999
+ config: default
2000
+ split: test
2001
+ revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
2002
+ metrics:
2003
+ - type: cos_sim_spearman
2004
+ value: 88.9399170304284
2005
+ - task:
2006
+ type: STS
2007
+ dataset:
2008
+ type: mteb/sts16-sts
2009
+ name: MTEB STS16
2010
+ config: default
2011
+ split: test
2012
+ revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
2013
+ metrics:
2014
+ - type: cos_sim_spearman
2015
+ value: 85.38015314088582
2016
+ - task:
2017
+ type: STS
2018
+ dataset:
2019
+ type: mteb/sts17-crosslingual-sts
2020
+ name: MTEB STS17 (en-en)
2021
+ config: en-en
2022
+ split: test
2023
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
2024
+ metrics:
2025
+ - type: cos_sim_spearman
2026
+ value: 90.53653527788835
2027
+ - task:
2028
+ type: STS
2029
+ dataset:
2030
+ type: mteb/sts22-crosslingual-sts
2031
+ name: MTEB STS22 (en)
2032
+ config: en
2033
+ split: test
2034
+ revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
2035
+ metrics:
2036
+ - type: cos_sim_spearman
2037
+ value: 68.64526474250209
2038
+ - task:
2039
+ type: STS
2040
+ dataset:
2041
+ type: mteb/stsbenchmark-sts
2042
+ name: MTEB STSBenchmark
2043
+ config: default
2044
+ split: test
2045
+ revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
2046
+ metrics:
2047
+ - type: cos_sim_spearman
2048
+ value: 86.56156983963042
2049
+ - task:
2050
+ type: Reranking
2051
+ dataset:
2052
+ type: mteb/scidocs-reranking
2053
+ name: MTEB SciDocsRR
2054
+ config: default
2055
+ split: test
2056
+ revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
2057
+ metrics:
2058
+ - type: map
2059
+ value: 79.48610254648003
2060
+ - type: mrr
2061
+ value: 94.02481505422682
2062
+ - task:
2063
+ type: Retrieval
2064
+ dataset:
2065
+ type: scifact
2066
+ name: MTEB SciFact
2067
+ config: default
2068
+ split: test
2069
+ revision: None
2070
+ metrics:
2071
+ - type: map_at_1
2072
+ value: 48.983
2073
+ - type: map_at_10
2074
+ value: 59.077999999999996
2075
+ - type: map_at_100
2076
+ value: 59.536
2077
+ - type: map_at_1000
2078
+ value: 59.575
2079
+ - type: map_at_3
2080
+ value: 55.691
2081
+ - type: map_at_5
2082
+ value: 57.410000000000004
2083
+ - type: mrr_at_1
2084
+ value: 51.666999999999994
2085
+ - type: mrr_at_10
2086
+ value: 60.427
2087
+ - type: mrr_at_100
2088
+ value: 60.763
2089
+ - type: mrr_at_1000
2090
+ value: 60.79900000000001
2091
+ - type: mrr_at_3
2092
+ value: 57.556
2093
+ - type: mrr_at_5
2094
+ value: 59.089000000000006
2095
+ - type: ndcg_at_1
2096
+ value: 51.666999999999994
2097
+ - type: ndcg_at_10
2098
+ value: 64.559
2099
+ - type: ndcg_at_100
2100
+ value: 66.58
2101
+ - type: ndcg_at_1000
2102
+ value: 67.64
2103
+ - type: ndcg_at_3
2104
+ value: 58.287
2105
+ - type: ndcg_at_5
2106
+ value: 61.001000000000005
2107
+ - type: precision_at_1
2108
+ value: 51.666999999999994
2109
+ - type: precision_at_10
2110
+ value: 9.067
2111
+ - type: precision_at_100
2112
+ value: 1.0170000000000001
2113
+ - type: precision_at_1000
2114
+ value: 0.11100000000000002
2115
+ - type: precision_at_3
2116
+ value: 23.0
2117
+ - type: precision_at_5
2118
+ value: 15.6
2119
+ - type: recall_at_1
2120
+ value: 48.983
2121
+ - type: recall_at_10
2122
+ value: 80.289
2123
+ - type: recall_at_100
2124
+ value: 89.43299999999999
2125
+ - type: recall_at_1000
2126
+ value: 97.667
2127
+ - type: recall_at_3
2128
+ value: 62.978
2129
+ - type: recall_at_5
2130
+ value: 69.872
2131
+ - task:
2132
+ type: PairClassification
2133
+ dataset:
2134
+ type: mteb/sprintduplicatequestions-pairclassification
2135
+ name: MTEB SprintDuplicateQuestions
2136
+ config: default
2137
+ split: test
2138
+ revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
2139
+ metrics:
2140
+ - type: cos_sim_accuracy
2141
+ value: 99.79009900990098
2142
+ - type: cos_sim_ap
2143
+ value: 94.94115052608419
2144
+ - type: cos_sim_f1
2145
+ value: 89.1260162601626
2146
+ - type: cos_sim_precision
2147
+ value: 90.599173553719
2148
+ - type: cos_sim_recall
2149
+ value: 87.7
2150
+ - type: dot_accuracy
2151
+ value: 99.79009900990098
2152
+ - type: dot_ap
2153
+ value: 94.94115052608419
2154
+ - type: dot_f1
2155
+ value: 89.1260162601626
2156
+ - type: dot_precision
2157
+ value: 90.599173553719
2158
+ - type: dot_recall
2159
+ value: 87.7
2160
+ - type: euclidean_accuracy
2161
+ value: 99.79009900990098
2162
+ - type: euclidean_ap
2163
+ value: 94.94115052608419
2164
+ - type: euclidean_f1
2165
+ value: 89.1260162601626
2166
+ - type: euclidean_precision
2167
+ value: 90.599173553719
2168
+ - type: euclidean_recall
2169
+ value: 87.7
2170
+ - type: manhattan_accuracy
2171
+ value: 99.7940594059406
2172
+ - type: manhattan_ap
2173
+ value: 94.95271414642431
2174
+ - type: manhattan_f1
2175
+ value: 89.24508790072387
2176
+ - type: manhattan_precision
2177
+ value: 92.3982869379015
2178
+ - type: manhattan_recall
2179
+ value: 86.3
2180
+ - type: max_accuracy
2181
+ value: 99.7940594059406
2182
+ - type: max_ap
2183
+ value: 94.95271414642431
2184
+ - type: max_f1
2185
+ value: 89.24508790072387
2186
+ - task:
2187
+ type: Clustering
2188
+ dataset:
2189
+ type: mteb/stackexchange-clustering
2190
+ name: MTEB StackExchangeClustering
2191
+ config: default
2192
+ split: test
2193
+ revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
2194
+ metrics:
2195
+ - type: v_measure
2196
+ value: 68.43866571935851
2197
+ - task:
2198
+ type: Clustering
2199
+ dataset:
2200
+ type: mteb/stackexchange-clustering-p2p
2201
+ name: MTEB StackExchangeClusteringP2P
2202
+ config: default
2203
+ split: test
2204
+ revision: 815ca46b2622cec33ccafc3735d572c266efdb44
2205
+ metrics:
2206
+ - type: v_measure
2207
+ value: 35.16579026551532
2208
+ - task:
2209
+ type: Reranking
2210
+ dataset:
2211
+ type: mteb/stackoverflowdupquestions-reranking
2212
+ name: MTEB StackOverflowDupQuestions
2213
+ config: default
2214
+ split: test
2215
+ revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
2216
+ metrics:
2217
+ - type: map
2218
+ value: 52.518952473513934
2219
+ - type: mrr
2220
+ value: 53.292457134368895
2221
+ - task:
2222
+ type: Summarization
2223
+ dataset:
2224
+ type: mteb/summeval
2225
+ name: MTEB SummEval
2226
+ config: default
2227
+ split: test
2228
+ revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
2229
+ metrics:
2230
+ - type: cos_sim_pearson
2231
+ value: 31.12529588316604
2232
+ - type: cos_sim_spearman
2233
+ value: 32.31662126895294
2234
+ - type: dot_pearson
2235
+ value: 31.125303796647056
2236
+ - type: dot_spearman
2237
+ value: 32.31662126895294
2238
+ - task:
2239
+ type: Retrieval
2240
+ dataset:
2241
+ type: trec-covid
2242
+ name: MTEB TRECCOVID
2243
+ config: default
2244
+ split: test
2245
+ revision: None
2246
+ metrics:
2247
+ - type: map_at_1
2248
+ value: 0.219
2249
+ - type: map_at_10
2250
+ value: 1.7469999999999999
2251
+ - type: map_at_100
2252
+ value: 10.177999999999999
2253
+ - type: map_at_1000
2254
+ value: 26.108999999999998
2255
+ - type: map_at_3
2256
+ value: 0.64
2257
+ - type: map_at_5
2258
+ value: 0.968
2259
+ - type: mrr_at_1
2260
+ value: 82.0
2261
+ - type: mrr_at_10
2262
+ value: 89.067
2263
+ - type: mrr_at_100
2264
+ value: 89.067
2265
+ - type: mrr_at_1000
2266
+ value: 89.067
2267
+ - type: mrr_at_3
2268
+ value: 88.333
2269
+ - type: mrr_at_5
2270
+ value: 88.73299999999999
2271
+ - type: ndcg_at_1
2272
+ value: 78.0
2273
+ - type: ndcg_at_10
2274
+ value: 71.398
2275
+ - type: ndcg_at_100
2276
+ value: 55.574999999999996
2277
+ - type: ndcg_at_1000
2278
+ value: 51.771
2279
+ - type: ndcg_at_3
2280
+ value: 77.765
2281
+ - type: ndcg_at_5
2282
+ value: 73.614
2283
+ - type: precision_at_1
2284
+ value: 82.0
2285
+ - type: precision_at_10
2286
+ value: 75.4
2287
+ - type: precision_at_100
2288
+ value: 58.040000000000006
2289
+ - type: precision_at_1000
2290
+ value: 23.516000000000002
2291
+ - type: precision_at_3
2292
+ value: 84.0
2293
+ - type: precision_at_5
2294
+ value: 78.4
2295
+ - type: recall_at_1
2296
+ value: 0.219
2297
+ - type: recall_at_10
2298
+ value: 1.958
2299
+ - type: recall_at_100
2300
+ value: 13.797999999999998
2301
+ - type: recall_at_1000
2302
+ value: 49.881
2303
+ - type: recall_at_3
2304
+ value: 0.672
2305
+ - type: recall_at_5
2306
+ value: 1.0370000000000001
2307
+ - task:
2308
+ type: Retrieval
2309
+ dataset:
2310
+ type: webis-touche2020
2311
+ name: MTEB Touche2020
2312
+ config: default
2313
+ split: test
2314
+ revision: None
2315
+ metrics:
2316
+ - type: map_at_1
2317
+ value: 1.8610000000000002
2318
+ - type: map_at_10
2319
+ value: 8.705
2320
+ - type: map_at_100
2321
+ value: 15.164
2322
+ - type: map_at_1000
2323
+ value: 16.78
2324
+ - type: map_at_3
2325
+ value: 4.346
2326
+ - type: map_at_5
2327
+ value: 6.151
2328
+ - type: mrr_at_1
2329
+ value: 22.448999999999998
2330
+ - type: mrr_at_10
2331
+ value: 41.556
2332
+ - type: mrr_at_100
2333
+ value: 42.484
2334
+ - type: mrr_at_1000
2335
+ value: 42.494
2336
+ - type: mrr_at_3
2337
+ value: 37.755
2338
+ - type: mrr_at_5
2339
+ value: 40.102
2340
+ - type: ndcg_at_1
2341
+ value: 21.429000000000002
2342
+ - type: ndcg_at_10
2343
+ value: 23.439
2344
+ - type: ndcg_at_100
2345
+ value: 36.948
2346
+ - type: ndcg_at_1000
2347
+ value: 48.408
2348
+ - type: ndcg_at_3
2349
+ value: 22.261
2350
+ - type: ndcg_at_5
2351
+ value: 23.085
2352
+ - type: precision_at_1
2353
+ value: 22.448999999999998
2354
+ - type: precision_at_10
2355
+ value: 21.633
2356
+ - type: precision_at_100
2357
+ value: 8.02
2358
+ - type: precision_at_1000
2359
+ value: 1.5939999999999999
2360
+ - type: precision_at_3
2361
+ value: 23.810000000000002
2362
+ - type: precision_at_5
2363
+ value: 24.490000000000002
2364
+ - type: recall_at_1
2365
+ value: 1.8610000000000002
2366
+ - type: recall_at_10
2367
+ value: 15.876000000000001
2368
+ - type: recall_at_100
2369
+ value: 50.300999999999995
2370
+ - type: recall_at_1000
2371
+ value: 86.098
2372
+ - type: recall_at_3
2373
+ value: 5.892
2374
+ - type: recall_at_5
2375
+ value: 9.443
2376
+ - task:
2377
+ type: Classification
2378
+ dataset:
2379
+ type: mteb/toxic_conversations_50k
2380
+ name: MTEB ToxicConversationsClassification
2381
+ config: default
2382
+ split: test
2383
+ revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
2384
+ metrics:
2385
+ - type: accuracy
2386
+ value: 70.3264
2387
+ - type: ap
2388
+ value: 13.249577616243794
2389
+ - type: f1
2390
+ value: 53.621518367695685
2391
+ - task:
2392
+ type: Classification
2393
+ dataset:
2394
+ type: mteb/tweet_sentiment_extraction
2395
+ name: MTEB TweetSentimentExtractionClassification
2396
+ config: default
2397
+ split: test
2398
+ revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
2399
+ metrics:
2400
+ - type: accuracy
2401
+ value: 61.57611771363894
2402
+ - type: f1
2403
+ value: 61.79797478568639
2404
+ - task:
2405
+ type: Clustering
2406
+ dataset:
2407
+ type: mteb/twentynewsgroups-clustering
2408
+ name: MTEB TwentyNewsgroupsClustering
2409
+ config: default
2410
+ split: test
2411
+ revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
2412
+ metrics:
2413
+ - type: v_measure
2414
+ value: 53.38315344479284
2415
+ - task:
2416
+ type: PairClassification
2417
+ dataset:
2418
+ type: mteb/twittersemeval2015-pairclassification
2419
+ name: MTEB TwitterSemEval2015
2420
+ config: default
2421
+ split: test
2422
+ revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
2423
+ metrics:
2424
+ - type: cos_sim_accuracy
2425
+ value: 87.55438993860642
2426
+ - type: cos_sim_ap
2427
+ value: 77.98702600017738
2428
+ - type: cos_sim_f1
2429
+ value: 71.94971653931476
2430
+ - type: cos_sim_precision
2431
+ value: 67.50693802035153
2432
+ - type: cos_sim_recall
2433
+ value: 77.01846965699208
2434
+ - type: dot_accuracy
2435
+ value: 87.55438993860642
2436
+ - type: dot_ap
2437
+ value: 77.98702925907986
2438
+ - type: dot_f1
2439
+ value: 71.94971653931476
2440
+ - type: dot_precision
2441
+ value: 67.50693802035153
2442
+ - type: dot_recall
2443
+ value: 77.01846965699208
2444
+ - type: euclidean_accuracy
2445
+ value: 87.55438993860642
2446
+ - type: euclidean_ap
2447
+ value: 77.98702951957925
2448
+ - type: euclidean_f1
2449
+ value: 71.94971653931476
2450
+ - type: euclidean_precision
2451
+ value: 67.50693802035153
2452
+ - type: euclidean_recall
2453
+ value: 77.01846965699208
2454
+ - type: manhattan_accuracy
2455
+ value: 87.54246885617214
2456
+ - type: manhattan_ap
2457
+ value: 77.95531413902947
2458
+ - type: manhattan_f1
2459
+ value: 71.93605683836589
2460
+ - type: manhattan_precision
2461
+ value: 69.28152492668622
2462
+ - type: manhattan_recall
2463
+ value: 74.80211081794195
2464
+ - type: max_accuracy
2465
+ value: 87.55438993860642
2466
+ - type: max_ap
2467
+ value: 77.98702951957925
2468
+ - type: max_f1
2469
+ value: 71.94971653931476
2470
+ - task:
2471
+ type: PairClassification
2472
+ dataset:
2473
+ type: mteb/twitterurlcorpus-pairclassification
2474
+ name: MTEB TwitterURLCorpus
2475
+ config: default
2476
+ split: test
2477
+ revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
2478
+ metrics:
2479
+ - type: cos_sim_accuracy
2480
+ value: 89.47296930182016
2481
+ - type: cos_sim_ap
2482
+ value: 86.92853616302108
2483
+ - type: cos_sim_f1
2484
+ value: 79.35138351681047
2485
+ - type: cos_sim_precision
2486
+ value: 76.74820143884892
2487
+ - type: cos_sim_recall
2488
+ value: 82.13735756082538
2489
+ - type: dot_accuracy
2490
+ value: 89.47296930182016
2491
+ - type: dot_ap
2492
+ value: 86.92854339601595
2493
+ - type: dot_f1
2494
+ value: 79.35138351681047
2495
+ - type: dot_precision
2496
+ value: 76.74820143884892
2497
+ - type: dot_recall
2498
+ value: 82.13735756082538
2499
+ - type: euclidean_accuracy
2500
+ value: 89.47296930182016
2501
+ - type: euclidean_ap
2502
+ value: 86.92854191061649
2503
+ - type: euclidean_f1
2504
+ value: 79.35138351681047
2505
+ - type: euclidean_precision
2506
+ value: 76.74820143884892
2507
+ - type: euclidean_recall
2508
+ value: 82.13735756082538
2509
+ - type: manhattan_accuracy
2510
+ value: 89.47685023479644
2511
+ - type: manhattan_ap
2512
+ value: 86.90063722679578
2513
+ - type: manhattan_f1
2514
+ value: 79.30753865502702
2515
+ - type: manhattan_precision
2516
+ value: 76.32066068631639
2517
+ - type: manhattan_recall
2518
+ value: 82.53772713273791
2519
+ - type: max_accuracy
2520
+ value: 89.47685023479644
2521
+ - type: max_ap
2522
+ value: 86.92854339601595
2523
+ - type: max_f1
2524
+ value: 79.35138351681047
2525
  ---
2526
 
2527
  # hkunlp/instructor-xl