philschmid HF staff commited on
Commit
c9971ce
1 Parent(s): d1d3576

Upload folder using huggingface_hub

Browse files
Files changed (8) hide show
  1. .gitattributes +1 -0
  2. README.md +2539 -0
  3. config.json +53 -0
  4. model.neuron +3 -0
  5. special_tokens_map.json +37 -0
  6. tokenizer.json +0 -0
  7. tokenizer_config.json +57 -0
  8. vocab.txt +0 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ model.neuron filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,2539 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language:
3
+ - en
4
+ license: mit
5
+ tags:
6
+ - sentence-transformers
7
+ - feature-extraction
8
+ - sentence-similarity
9
+ - transformers
10
+ - mteb
11
+ - inferentia2
12
+ - neuron
13
+ model-index:
14
+ - name: bge-base-en-v1.5
15
+ results:
16
+ - task:
17
+ type: Classification
18
+ dataset:
19
+ name: MTEB AmazonCounterfactualClassification (en)
20
+ type: mteb/amazon_counterfactual
21
+ config: en
22
+ split: test
23
+ revision: e8379541af4e31359cca9fbcf4b00f2671dba205
24
+ metrics:
25
+ - type: accuracy
26
+ value: 76.14925373134328
27
+ - type: ap
28
+ value: 39.32336517995478
29
+ - type: f1
30
+ value: 70.16902252611425
31
+ - task:
32
+ type: Classification
33
+ dataset:
34
+ name: MTEB AmazonPolarityClassification
35
+ type: mteb/amazon_polarity
36
+ config: default
37
+ split: test
38
+ revision: e2d317d38cd51312af73b3d32a06d1a08b442046
39
+ metrics:
40
+ - type: accuracy
41
+ value: 93.386825
42
+ - type: ap
43
+ value: 90.21276917991995
44
+ - type: f1
45
+ value: 93.37741030006174
46
+ - task:
47
+ type: Classification
48
+ dataset:
49
+ name: MTEB AmazonReviewsClassification (en)
50
+ type: mteb/amazon_reviews_multi
51
+ config: en
52
+ split: test
53
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
54
+ metrics:
55
+ - type: accuracy
56
+ value: 48.846000000000004
57
+ - type: f1
58
+ value: 48.14646269778261
59
+ - task:
60
+ type: Retrieval
61
+ dataset:
62
+ name: MTEB ArguAna
63
+ type: arguana
64
+ config: default
65
+ split: test
66
+ revision: None
67
+ metrics:
68
+ - type: map_at_1
69
+ value: 40.754000000000005
70
+ - type: map_at_10
71
+ value: 55.761
72
+ - type: map_at_100
73
+ value: 56.330999999999996
74
+ - type: map_at_1000
75
+ value: 56.333999999999996
76
+ - type: map_at_3
77
+ value: 51.92
78
+ - type: map_at_5
79
+ value: 54.010999999999996
80
+ - type: mrr_at_1
81
+ value: 41.181
82
+ - type: mrr_at_10
83
+ value: 55.967999999999996
84
+ - type: mrr_at_100
85
+ value: 56.538
86
+ - type: mrr_at_1000
87
+ value: 56.542
88
+ - type: mrr_at_3
89
+ value: 51.980000000000004
90
+ - type: mrr_at_5
91
+ value: 54.208999999999996
92
+ - type: ndcg_at_1
93
+ value: 40.754000000000005
94
+ - type: ndcg_at_10
95
+ value: 63.605000000000004
96
+ - type: ndcg_at_100
97
+ value: 66.05199999999999
98
+ - type: ndcg_at_1000
99
+ value: 66.12
100
+ - type: ndcg_at_3
101
+ value: 55.708
102
+ - type: ndcg_at_5
103
+ value: 59.452000000000005
104
+ - type: precision_at_1
105
+ value: 40.754000000000005
106
+ - type: precision_at_10
107
+ value: 8.841000000000001
108
+ - type: precision_at_100
109
+ value: 0.991
110
+ - type: precision_at_1000
111
+ value: 0.1
112
+ - type: precision_at_3
113
+ value: 22.238
114
+ - type: precision_at_5
115
+ value: 15.149000000000001
116
+ - type: recall_at_1
117
+ value: 40.754000000000005
118
+ - type: recall_at_10
119
+ value: 88.407
120
+ - type: recall_at_100
121
+ value: 99.14699999999999
122
+ - type: recall_at_1000
123
+ value: 99.644
124
+ - type: recall_at_3
125
+ value: 66.714
126
+ - type: recall_at_5
127
+ value: 75.747
128
+ - task:
129
+ type: Clustering
130
+ dataset:
131
+ name: MTEB ArxivClusteringP2P
132
+ type: mteb/arxiv-clustering-p2p
133
+ config: default
134
+ split: test
135
+ revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
136
+ metrics:
137
+ - type: v_measure
138
+ value: 48.74884539679369
139
+ - task:
140
+ type: Clustering
141
+ dataset:
142
+ name: MTEB ArxivClusteringS2S
143
+ type: mteb/arxiv-clustering-s2s
144
+ config: default
145
+ split: test
146
+ revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
147
+ metrics:
148
+ - type: v_measure
149
+ value: 42.8075893810716
150
+ - task:
151
+ type: Reranking
152
+ dataset:
153
+ name: MTEB AskUbuntuDupQuestions
154
+ type: mteb/askubuntudupquestions-reranking
155
+ config: default
156
+ split: test
157
+ revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
158
+ metrics:
159
+ - type: map
160
+ value: 62.128470519187736
161
+ - type: mrr
162
+ value: 74.28065778481289
163
+ - task:
164
+ type: STS
165
+ dataset:
166
+ name: MTEB BIOSSES
167
+ type: mteb/biosses-sts
168
+ config: default
169
+ split: test
170
+ revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
171
+ metrics:
172
+ - type: cos_sim_pearson
173
+ value: 89.24629081484655
174
+ - type: cos_sim_spearman
175
+ value: 86.93752309911496
176
+ - type: euclidean_pearson
177
+ value: 87.58589628573816
178
+ - type: euclidean_spearman
179
+ value: 88.05622328825284
180
+ - type: manhattan_pearson
181
+ value: 87.5594959805773
182
+ - type: manhattan_spearman
183
+ value: 88.19658793233961
184
+ - task:
185
+ type: Classification
186
+ dataset:
187
+ name: MTEB Banking77Classification
188
+ type: mteb/banking77
189
+ config: default
190
+ split: test
191
+ revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
192
+ metrics:
193
+ - type: accuracy
194
+ value: 86.9512987012987
195
+ - type: f1
196
+ value: 86.92515357973708
197
+ - task:
198
+ type: Clustering
199
+ dataset:
200
+ name: MTEB BiorxivClusteringP2P
201
+ type: mteb/biorxiv-clustering-p2p
202
+ config: default
203
+ split: test
204
+ revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
205
+ metrics:
206
+ - type: v_measure
207
+ value: 39.10263762928872
208
+ - task:
209
+ type: Clustering
210
+ dataset:
211
+ name: MTEB BiorxivClusteringS2S
212
+ type: mteb/biorxiv-clustering-s2s
213
+ config: default
214
+ split: test
215
+ revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
216
+ metrics:
217
+ - type: v_measure
218
+ value: 36.69711517426737
219
+ - task:
220
+ type: Retrieval
221
+ dataset:
222
+ name: MTEB CQADupstackAndroidRetrieval
223
+ type: BeIR/cqadupstack
224
+ config: default
225
+ split: test
226
+ revision: None
227
+ metrics:
228
+ - type: map_at_1
229
+ value: 32.327
230
+ - type: map_at_10
231
+ value: 44.099
232
+ - type: map_at_100
233
+ value: 45.525
234
+ - type: map_at_1000
235
+ value: 45.641999999999996
236
+ - type: map_at_3
237
+ value: 40.47
238
+ - type: map_at_5
239
+ value: 42.36
240
+ - type: mrr_at_1
241
+ value: 39.199
242
+ - type: mrr_at_10
243
+ value: 49.651
244
+ - type: mrr_at_100
245
+ value: 50.29
246
+ - type: mrr_at_1000
247
+ value: 50.329
248
+ - type: mrr_at_3
249
+ value: 46.924
250
+ - type: mrr_at_5
251
+ value: 48.548
252
+ - type: ndcg_at_1
253
+ value: 39.199
254
+ - type: ndcg_at_10
255
+ value: 50.773
256
+ - type: ndcg_at_100
257
+ value: 55.67999999999999
258
+ - type: ndcg_at_1000
259
+ value: 57.495
260
+ - type: ndcg_at_3
261
+ value: 45.513999999999996
262
+ - type: ndcg_at_5
263
+ value: 47.703
264
+ - type: precision_at_1
265
+ value: 39.199
266
+ - type: precision_at_10
267
+ value: 9.914000000000001
268
+ - type: precision_at_100
269
+ value: 1.5310000000000001
270
+ - type: precision_at_1000
271
+ value: 0.198
272
+ - type: precision_at_3
273
+ value: 21.984
274
+ - type: precision_at_5
275
+ value: 15.737000000000002
276
+ - type: recall_at_1
277
+ value: 32.327
278
+ - type: recall_at_10
279
+ value: 63.743
280
+ - type: recall_at_100
281
+ value: 84.538
282
+ - type: recall_at_1000
283
+ value: 96.089
284
+ - type: recall_at_3
285
+ value: 48.065000000000005
286
+ - type: recall_at_5
287
+ value: 54.519
288
+ - type: map_at_1
289
+ value: 32.671
290
+ - type: map_at_10
291
+ value: 42.954
292
+ - type: map_at_100
293
+ value: 44.151
294
+ - type: map_at_1000
295
+ value: 44.287
296
+ - type: map_at_3
297
+ value: 39.912
298
+ - type: map_at_5
299
+ value: 41.798
300
+ - type: mrr_at_1
301
+ value: 41.465
302
+ - type: mrr_at_10
303
+ value: 49.351
304
+ - type: mrr_at_100
305
+ value: 49.980000000000004
306
+ - type: mrr_at_1000
307
+ value: 50.016000000000005
308
+ - type: mrr_at_3
309
+ value: 47.144000000000005
310
+ - type: mrr_at_5
311
+ value: 48.592999999999996
312
+ - type: ndcg_at_1
313
+ value: 41.465
314
+ - type: ndcg_at_10
315
+ value: 48.565999999999995
316
+ - type: ndcg_at_100
317
+ value: 52.76499999999999
318
+ - type: ndcg_at_1000
319
+ value: 54.749
320
+ - type: ndcg_at_3
321
+ value: 44.57
322
+ - type: ndcg_at_5
323
+ value: 46.759
324
+ - type: precision_at_1
325
+ value: 41.465
326
+ - type: precision_at_10
327
+ value: 9.107999999999999
328
+ - type: precision_at_100
329
+ value: 1.433
330
+ - type: precision_at_1000
331
+ value: 0.191
332
+ - type: precision_at_3
333
+ value: 21.423000000000002
334
+ - type: precision_at_5
335
+ value: 15.414
336
+ - type: recall_at_1
337
+ value: 32.671
338
+ - type: recall_at_10
339
+ value: 57.738
340
+ - type: recall_at_100
341
+ value: 75.86500000000001
342
+ - type: recall_at_1000
343
+ value: 88.36
344
+ - type: recall_at_3
345
+ value: 45.626
346
+ - type: recall_at_5
347
+ value: 51.812000000000005
348
+ - type: map_at_1
349
+ value: 41.185
350
+ - type: map_at_10
351
+ value: 53.929
352
+ - type: map_at_100
353
+ value: 54.92
354
+ - type: map_at_1000
355
+ value: 54.967999999999996
356
+ - type: map_at_3
357
+ value: 50.70400000000001
358
+ - type: map_at_5
359
+ value: 52.673
360
+ - type: mrr_at_1
361
+ value: 47.398
362
+ - type: mrr_at_10
363
+ value: 57.303000000000004
364
+ - type: mrr_at_100
365
+ value: 57.959
366
+ - type: mrr_at_1000
367
+ value: 57.985
368
+ - type: mrr_at_3
369
+ value: 54.932
370
+ - type: mrr_at_5
371
+ value: 56.464999999999996
372
+ - type: ndcg_at_1
373
+ value: 47.398
374
+ - type: ndcg_at_10
375
+ value: 59.653
376
+ - type: ndcg_at_100
377
+ value: 63.627
378
+ - type: ndcg_at_1000
379
+ value: 64.596
380
+ - type: ndcg_at_3
381
+ value: 54.455
382
+ - type: ndcg_at_5
383
+ value: 57.245000000000005
384
+ - type: precision_at_1
385
+ value: 47.398
386
+ - type: precision_at_10
387
+ value: 9.524000000000001
388
+ - type: precision_at_100
389
+ value: 1.243
390
+ - type: precision_at_1000
391
+ value: 0.13699999999999998
392
+ - type: precision_at_3
393
+ value: 24.389
394
+ - type: precision_at_5
395
+ value: 16.752
396
+ - type: recall_at_1
397
+ value: 41.185
398
+ - type: recall_at_10
399
+ value: 73.193
400
+ - type: recall_at_100
401
+ value: 90.357
402
+ - type: recall_at_1000
403
+ value: 97.253
404
+ - type: recall_at_3
405
+ value: 59.199999999999996
406
+ - type: recall_at_5
407
+ value: 66.118
408
+ - type: map_at_1
409
+ value: 27.27
410
+ - type: map_at_10
411
+ value: 36.223
412
+ - type: map_at_100
413
+ value: 37.218
414
+ - type: map_at_1000
415
+ value: 37.293
416
+ - type: map_at_3
417
+ value: 33.503
418
+ - type: map_at_5
419
+ value: 35.097
420
+ - type: mrr_at_1
421
+ value: 29.492
422
+ - type: mrr_at_10
423
+ value: 38.352000000000004
424
+ - type: mrr_at_100
425
+ value: 39.188
426
+ - type: mrr_at_1000
427
+ value: 39.247
428
+ - type: mrr_at_3
429
+ value: 35.876000000000005
430
+ - type: mrr_at_5
431
+ value: 37.401
432
+ - type: ndcg_at_1
433
+ value: 29.492
434
+ - type: ndcg_at_10
435
+ value: 41.239
436
+ - type: ndcg_at_100
437
+ value: 46.066
438
+ - type: ndcg_at_1000
439
+ value: 47.992000000000004
440
+ - type: ndcg_at_3
441
+ value: 36.11
442
+ - type: ndcg_at_5
443
+ value: 38.772
444
+ - type: precision_at_1
445
+ value: 29.492
446
+ - type: precision_at_10
447
+ value: 6.260000000000001
448
+ - type: precision_at_100
449
+ value: 0.914
450
+ - type: precision_at_1000
451
+ value: 0.11100000000000002
452
+ - type: precision_at_3
453
+ value: 15.104000000000001
454
+ - type: precision_at_5
455
+ value: 10.644
456
+ - type: recall_at_1
457
+ value: 27.27
458
+ - type: recall_at_10
459
+ value: 54.589
460
+ - type: recall_at_100
461
+ value: 76.70700000000001
462
+ - type: recall_at_1000
463
+ value: 91.158
464
+ - type: recall_at_3
465
+ value: 40.974
466
+ - type: recall_at_5
467
+ value: 47.327000000000005
468
+ - type: map_at_1
469
+ value: 17.848
470
+ - type: map_at_10
471
+ value: 26.207
472
+ - type: map_at_100
473
+ value: 27.478
474
+ - type: map_at_1000
475
+ value: 27.602
476
+ - type: map_at_3
477
+ value: 23.405
478
+ - type: map_at_5
479
+ value: 24.98
480
+ - type: mrr_at_1
481
+ value: 21.891
482
+ - type: mrr_at_10
483
+ value: 31.041999999999998
484
+ - type: mrr_at_100
485
+ value: 32.092
486
+ - type: mrr_at_1000
487
+ value: 32.151999999999994
488
+ - type: mrr_at_3
489
+ value: 28.358
490
+ - type: mrr_at_5
491
+ value: 29.969
492
+ - type: ndcg_at_1
493
+ value: 21.891
494
+ - type: ndcg_at_10
495
+ value: 31.585
496
+ - type: ndcg_at_100
497
+ value: 37.531
498
+ - type: ndcg_at_1000
499
+ value: 40.256
500
+ - type: ndcg_at_3
501
+ value: 26.508
502
+ - type: ndcg_at_5
503
+ value: 28.894
504
+ - type: precision_at_1
505
+ value: 21.891
506
+ - type: precision_at_10
507
+ value: 5.795999999999999
508
+ - type: precision_at_100
509
+ value: 0.9990000000000001
510
+ - type: precision_at_1000
511
+ value: 0.13799999999999998
512
+ - type: precision_at_3
513
+ value: 12.769
514
+ - type: precision_at_5
515
+ value: 9.279
516
+ - type: recall_at_1
517
+ value: 17.848
518
+ - type: recall_at_10
519
+ value: 43.452
520
+ - type: recall_at_100
521
+ value: 69.216
522
+ - type: recall_at_1000
523
+ value: 88.102
524
+ - type: recall_at_3
525
+ value: 29.18
526
+ - type: recall_at_5
527
+ value: 35.347
528
+ - type: map_at_1
529
+ value: 30.94
530
+ - type: map_at_10
531
+ value: 41.248000000000005
532
+ - type: map_at_100
533
+ value: 42.495
534
+ - type: map_at_1000
535
+ value: 42.602000000000004
536
+ - type: map_at_3
537
+ value: 37.939
538
+ - type: map_at_5
539
+ value: 39.924
540
+ - type: mrr_at_1
541
+ value: 37.824999999999996
542
+ - type: mrr_at_10
543
+ value: 47.041
544
+ - type: mrr_at_100
545
+ value: 47.83
546
+ - type: mrr_at_1000
547
+ value: 47.878
548
+ - type: mrr_at_3
549
+ value: 44.466
550
+ - type: mrr_at_5
551
+ value: 46.111999999999995
552
+ - type: ndcg_at_1
553
+ value: 37.824999999999996
554
+ - type: ndcg_at_10
555
+ value: 47.223
556
+ - type: ndcg_at_100
557
+ value: 52.394
558
+ - type: ndcg_at_1000
559
+ value: 54.432
560
+ - type: ndcg_at_3
561
+ value: 42.032000000000004
562
+ - type: ndcg_at_5
563
+ value: 44.772
564
+ - type: precision_at_1
565
+ value: 37.824999999999996
566
+ - type: precision_at_10
567
+ value: 8.393
568
+ - type: precision_at_100
569
+ value: 1.2890000000000001
570
+ - type: precision_at_1000
571
+ value: 0.164
572
+ - type: precision_at_3
573
+ value: 19.698
574
+ - type: precision_at_5
575
+ value: 14.013
576
+ - type: recall_at_1
577
+ value: 30.94
578
+ - type: recall_at_10
579
+ value: 59.316
580
+ - type: recall_at_100
581
+ value: 80.783
582
+ - type: recall_at_1000
583
+ value: 94.15400000000001
584
+ - type: recall_at_3
585
+ value: 44.712
586
+ - type: recall_at_5
587
+ value: 51.932
588
+ - type: map_at_1
589
+ value: 27.104
590
+ - type: map_at_10
591
+ value: 36.675999999999995
592
+ - type: map_at_100
593
+ value: 38.076
594
+ - type: map_at_1000
595
+ value: 38.189
596
+ - type: map_at_3
597
+ value: 33.733999999999995
598
+ - type: map_at_5
599
+ value: 35.287
600
+ - type: mrr_at_1
601
+ value: 33.904
602
+ - type: mrr_at_10
603
+ value: 42.55
604
+ - type: mrr_at_100
605
+ value: 43.434
606
+ - type: mrr_at_1000
607
+ value: 43.494
608
+ - type: mrr_at_3
609
+ value: 40.126
610
+ - type: mrr_at_5
611
+ value: 41.473
612
+ - type: ndcg_at_1
613
+ value: 33.904
614
+ - type: ndcg_at_10
615
+ value: 42.414
616
+ - type: ndcg_at_100
617
+ value: 48.203
618
+ - type: ndcg_at_1000
619
+ value: 50.437
620
+ - type: ndcg_at_3
621
+ value: 37.633
622
+ - type: ndcg_at_5
623
+ value: 39.67
624
+ - type: precision_at_1
625
+ value: 33.904
626
+ - type: precision_at_10
627
+ value: 7.82
628
+ - type: precision_at_100
629
+ value: 1.2409999999999999
630
+ - type: precision_at_1000
631
+ value: 0.159
632
+ - type: precision_at_3
633
+ value: 17.884
634
+ - type: precision_at_5
635
+ value: 12.648000000000001
636
+ - type: recall_at_1
637
+ value: 27.104
638
+ - type: recall_at_10
639
+ value: 53.563
640
+ - type: recall_at_100
641
+ value: 78.557
642
+ - type: recall_at_1000
643
+ value: 93.533
644
+ - type: recall_at_3
645
+ value: 39.92
646
+ - type: recall_at_5
647
+ value: 45.457
648
+ - type: map_at_1
649
+ value: 27.707749999999997
650
+ - type: map_at_10
651
+ value: 36.961
652
+ - type: map_at_100
653
+ value: 38.158833333333334
654
+ - type: map_at_1000
655
+ value: 38.270333333333326
656
+ - type: map_at_3
657
+ value: 34.07183333333334
658
+ - type: map_at_5
659
+ value: 35.69533333333334
660
+ - type: mrr_at_1
661
+ value: 32.81875
662
+ - type: mrr_at_10
663
+ value: 41.293
664
+ - type: mrr_at_100
665
+ value: 42.116499999999995
666
+ - type: mrr_at_1000
667
+ value: 42.170249999999996
668
+ - type: mrr_at_3
669
+ value: 38.83983333333333
670
+ - type: mrr_at_5
671
+ value: 40.29775
672
+ - type: ndcg_at_1
673
+ value: 32.81875
674
+ - type: ndcg_at_10
675
+ value: 42.355
676
+ - type: ndcg_at_100
677
+ value: 47.41374999999999
678
+ - type: ndcg_at_1000
679
+ value: 49.5805
680
+ - type: ndcg_at_3
681
+ value: 37.52825
682
+ - type: ndcg_at_5
683
+ value: 39.83266666666667
684
+ - type: precision_at_1
685
+ value: 32.81875
686
+ - type: precision_at_10
687
+ value: 7.382416666666666
688
+ - type: precision_at_100
689
+ value: 1.1640833333333334
690
+ - type: precision_at_1000
691
+ value: 0.15383333333333335
692
+ - type: precision_at_3
693
+ value: 17.134166666666665
694
+ - type: precision_at_5
695
+ value: 12.174833333333336
696
+ - type: recall_at_1
697
+ value: 27.707749999999997
698
+ - type: recall_at_10
699
+ value: 53.945
700
+ - type: recall_at_100
701
+ value: 76.191
702
+ - type: recall_at_1000
703
+ value: 91.101
704
+ - type: recall_at_3
705
+ value: 40.39083333333334
706
+ - type: recall_at_5
707
+ value: 46.40083333333333
708
+ - type: map_at_1
709
+ value: 26.482
710
+ - type: map_at_10
711
+ value: 33.201
712
+ - type: map_at_100
713
+ value: 34.107
714
+ - type: map_at_1000
715
+ value: 34.197
716
+ - type: map_at_3
717
+ value: 31.174000000000003
718
+ - type: map_at_5
719
+ value: 32.279
720
+ - type: mrr_at_1
721
+ value: 29.908
722
+ - type: mrr_at_10
723
+ value: 36.235
724
+ - type: mrr_at_100
725
+ value: 37.04
726
+ - type: mrr_at_1000
727
+ value: 37.105
728
+ - type: mrr_at_3
729
+ value: 34.355999999999995
730
+ - type: mrr_at_5
731
+ value: 35.382999999999996
732
+ - type: ndcg_at_1
733
+ value: 29.908
734
+ - type: ndcg_at_10
735
+ value: 37.325
736
+ - type: ndcg_at_100
737
+ value: 41.795
738
+ - type: ndcg_at_1000
739
+ value: 44.105
740
+ - type: ndcg_at_3
741
+ value: 33.555
742
+ - type: ndcg_at_5
743
+ value: 35.266999999999996
744
+ - type: precision_at_1
745
+ value: 29.908
746
+ - type: precision_at_10
747
+ value: 5.721
748
+ - type: precision_at_100
749
+ value: 0.8630000000000001
750
+ - type: precision_at_1000
751
+ value: 0.11299999999999999
752
+ - type: precision_at_3
753
+ value: 14.008000000000001
754
+ - type: precision_at_5
755
+ value: 9.754999999999999
756
+ - type: recall_at_1
757
+ value: 26.482
758
+ - type: recall_at_10
759
+ value: 47.072
760
+ - type: recall_at_100
761
+ value: 67.27
762
+ - type: recall_at_1000
763
+ value: 84.371
764
+ - type: recall_at_3
765
+ value: 36.65
766
+ - type: recall_at_5
767
+ value: 40.774
768
+ - type: map_at_1
769
+ value: 18.815
770
+ - type: map_at_10
771
+ value: 26.369999999999997
772
+ - type: map_at_100
773
+ value: 27.458
774
+ - type: map_at_1000
775
+ value: 27.588
776
+ - type: map_at_3
777
+ value: 23.990000000000002
778
+ - type: map_at_5
779
+ value: 25.345000000000002
780
+ - type: mrr_at_1
781
+ value: 22.953000000000003
782
+ - type: mrr_at_10
783
+ value: 30.342999999999996
784
+ - type: mrr_at_100
785
+ value: 31.241000000000003
786
+ - type: mrr_at_1000
787
+ value: 31.319000000000003
788
+ - type: mrr_at_3
789
+ value: 28.16
790
+ - type: mrr_at_5
791
+ value: 29.406
792
+ - type: ndcg_at_1
793
+ value: 22.953000000000003
794
+ - type: ndcg_at_10
795
+ value: 31.151
796
+ - type: ndcg_at_100
797
+ value: 36.309000000000005
798
+ - type: ndcg_at_1000
799
+ value: 39.227000000000004
800
+ - type: ndcg_at_3
801
+ value: 26.921
802
+ - type: ndcg_at_5
803
+ value: 28.938000000000002
804
+ - type: precision_at_1
805
+ value: 22.953000000000003
806
+ - type: precision_at_10
807
+ value: 5.602
808
+ - type: precision_at_100
809
+ value: 0.9530000000000001
810
+ - type: precision_at_1000
811
+ value: 0.13899999999999998
812
+ - type: precision_at_3
813
+ value: 12.606
814
+ - type: precision_at_5
815
+ value: 9.119
816
+ - type: recall_at_1
817
+ value: 18.815
818
+ - type: recall_at_10
819
+ value: 41.574
820
+ - type: recall_at_100
821
+ value: 64.84400000000001
822
+ - type: recall_at_1000
823
+ value: 85.406
824
+ - type: recall_at_3
825
+ value: 29.694
826
+ - type: recall_at_5
827
+ value: 34.935
828
+ - type: map_at_1
829
+ value: 27.840999999999998
830
+ - type: map_at_10
831
+ value: 36.797999999999995
832
+ - type: map_at_100
833
+ value: 37.993
834
+ - type: map_at_1000
835
+ value: 38.086999999999996
836
+ - type: map_at_3
837
+ value: 34.050999999999995
838
+ - type: map_at_5
839
+ value: 35.379
840
+ - type: mrr_at_1
841
+ value: 32.649
842
+ - type: mrr_at_10
843
+ value: 41.025
844
+ - type: mrr_at_100
845
+ value: 41.878
846
+ - type: mrr_at_1000
847
+ value: 41.929
848
+ - type: mrr_at_3
849
+ value: 38.573
850
+ - type: mrr_at_5
851
+ value: 39.715
852
+ - type: ndcg_at_1
853
+ value: 32.649
854
+ - type: ndcg_at_10
855
+ value: 42.142
856
+ - type: ndcg_at_100
857
+ value: 47.558
858
+ - type: ndcg_at_1000
859
+ value: 49.643
860
+ - type: ndcg_at_3
861
+ value: 37.12
862
+ - type: ndcg_at_5
863
+ value: 38.983000000000004
864
+ - type: precision_at_1
865
+ value: 32.649
866
+ - type: precision_at_10
867
+ value: 7.08
868
+ - type: precision_at_100
869
+ value: 1.1039999999999999
870
+ - type: precision_at_1000
871
+ value: 0.13899999999999998
872
+ - type: precision_at_3
873
+ value: 16.698
874
+ - type: precision_at_5
875
+ value: 11.511000000000001
876
+ - type: recall_at_1
877
+ value: 27.840999999999998
878
+ - type: recall_at_10
879
+ value: 54.245
880
+ - type: recall_at_100
881
+ value: 77.947
882
+ - type: recall_at_1000
883
+ value: 92.36999999999999
884
+ - type: recall_at_3
885
+ value: 40.146
886
+ - type: recall_at_5
887
+ value: 44.951
888
+ - type: map_at_1
889
+ value: 26.529000000000003
890
+ - type: map_at_10
891
+ value: 35.010000000000005
892
+ - type: map_at_100
893
+ value: 36.647
894
+ - type: map_at_1000
895
+ value: 36.857
896
+ - type: map_at_3
897
+ value: 31.968000000000004
898
+ - type: map_at_5
899
+ value: 33.554
900
+ - type: mrr_at_1
901
+ value: 31.818
902
+ - type: mrr_at_10
903
+ value: 39.550999999999995
904
+ - type: mrr_at_100
905
+ value: 40.54
906
+ - type: mrr_at_1000
907
+ value: 40.596
908
+ - type: mrr_at_3
909
+ value: 36.726
910
+ - type: mrr_at_5
911
+ value: 38.416
912
+ - type: ndcg_at_1
913
+ value: 31.818
914
+ - type: ndcg_at_10
915
+ value: 40.675
916
+ - type: ndcg_at_100
917
+ value: 46.548
918
+ - type: ndcg_at_1000
919
+ value: 49.126
920
+ - type: ndcg_at_3
921
+ value: 35.829
922
+ - type: ndcg_at_5
923
+ value: 38.0
924
+ - type: precision_at_1
925
+ value: 31.818
926
+ - type: precision_at_10
927
+ value: 7.826
928
+ - type: precision_at_100
929
+ value: 1.538
930
+ - type: precision_at_1000
931
+ value: 0.24
932
+ - type: precision_at_3
933
+ value: 16.601
934
+ - type: precision_at_5
935
+ value: 12.095
936
+ - type: recall_at_1
937
+ value: 26.529000000000003
938
+ - type: recall_at_10
939
+ value: 51.03
940
+ - type: recall_at_100
941
+ value: 77.556
942
+ - type: recall_at_1000
943
+ value: 93.804
944
+ - type: recall_at_3
945
+ value: 36.986000000000004
946
+ - type: recall_at_5
947
+ value: 43.096000000000004
948
+ - type: map_at_1
949
+ value: 23.480999999999998
950
+ - type: map_at_10
951
+ value: 30.817
952
+ - type: map_at_100
953
+ value: 31.838
954
+ - type: map_at_1000
955
+ value: 31.932
956
+ - type: map_at_3
957
+ value: 28.011999999999997
958
+ - type: map_at_5
959
+ value: 29.668
960
+ - type: mrr_at_1
961
+ value: 25.323
962
+ - type: mrr_at_10
963
+ value: 33.072
964
+ - type: mrr_at_100
965
+ value: 33.926
966
+ - type: mrr_at_1000
967
+ value: 33.993
968
+ - type: mrr_at_3
969
+ value: 30.436999999999998
970
+ - type: mrr_at_5
971
+ value: 32.092
972
+ - type: ndcg_at_1
973
+ value: 25.323
974
+ - type: ndcg_at_10
975
+ value: 35.514
976
+ - type: ndcg_at_100
977
+ value: 40.489000000000004
978
+ - type: ndcg_at_1000
979
+ value: 42.908
980
+ - type: ndcg_at_3
981
+ value: 30.092000000000002
982
+ - type: ndcg_at_5
983
+ value: 32.989000000000004
984
+ - type: precision_at_1
985
+ value: 25.323
986
+ - type: precision_at_10
987
+ value: 5.545
988
+ - type: precision_at_100
989
+ value: 0.861
990
+ - type: precision_at_1000
991
+ value: 0.117
992
+ - type: precision_at_3
993
+ value: 12.446
994
+ - type: precision_at_5
995
+ value: 9.131
996
+ - type: recall_at_1
997
+ value: 23.480999999999998
998
+ - type: recall_at_10
999
+ value: 47.825
1000
+ - type: recall_at_100
1001
+ value: 70.652
1002
+ - type: recall_at_1000
1003
+ value: 88.612
1004
+ - type: recall_at_3
1005
+ value: 33.537
1006
+ - type: recall_at_5
1007
+ value: 40.542
1008
+ - task:
1009
+ type: Retrieval
1010
+ dataset:
1011
+ name: MTEB ClimateFEVER
1012
+ type: climate-fever
1013
+ config: default
1014
+ split: test
1015
+ revision: None
1016
+ metrics:
1017
+ - type: map_at_1
1018
+ value: 13.333999999999998
1019
+ - type: map_at_10
1020
+ value: 22.524
1021
+ - type: map_at_100
1022
+ value: 24.506
1023
+ - type: map_at_1000
1024
+ value: 24.715
1025
+ - type: map_at_3
1026
+ value: 19.022
1027
+ - type: map_at_5
1028
+ value: 20.693
1029
+ - type: mrr_at_1
1030
+ value: 29.186
1031
+ - type: mrr_at_10
1032
+ value: 41.22
1033
+ - type: mrr_at_100
1034
+ value: 42.16
1035
+ - type: mrr_at_1000
1036
+ value: 42.192
1037
+ - type: mrr_at_3
1038
+ value: 38.013000000000005
1039
+ - type: mrr_at_5
1040
+ value: 39.704
1041
+ - type: ndcg_at_1
1042
+ value: 29.186
1043
+ - type: ndcg_at_10
1044
+ value: 31.167
1045
+ - type: ndcg_at_100
1046
+ value: 38.879000000000005
1047
+ - type: ndcg_at_1000
1048
+ value: 42.376000000000005
1049
+ - type: ndcg_at_3
1050
+ value: 25.817
1051
+ - type: ndcg_at_5
1052
+ value: 27.377000000000002
1053
+ - type: precision_at_1
1054
+ value: 29.186
1055
+ - type: precision_at_10
1056
+ value: 9.693999999999999
1057
+ - type: precision_at_100
1058
+ value: 1.8030000000000002
1059
+ - type: precision_at_1000
1060
+ value: 0.246
1061
+ - type: precision_at_3
1062
+ value: 19.11
1063
+ - type: precision_at_5
1064
+ value: 14.344999999999999
1065
+ - type: recall_at_1
1066
+ value: 13.333999999999998
1067
+ - type: recall_at_10
1068
+ value: 37.092000000000006
1069
+ - type: recall_at_100
1070
+ value: 63.651
1071
+ - type: recall_at_1000
1072
+ value: 83.05
1073
+ - type: recall_at_3
1074
+ value: 23.74
1075
+ - type: recall_at_5
1076
+ value: 28.655
1077
+ - task:
1078
+ type: Retrieval
1079
+ dataset:
1080
+ name: MTEB DBPedia
1081
+ type: dbpedia-entity
1082
+ config: default
1083
+ split: test
1084
+ revision: None
1085
+ metrics:
1086
+ - type: map_at_1
1087
+ value: 9.151
1088
+ - type: map_at_10
1089
+ value: 19.653000000000002
1090
+ - type: map_at_100
1091
+ value: 28.053
1092
+ - type: map_at_1000
1093
+ value: 29.709000000000003
1094
+ - type: map_at_3
1095
+ value: 14.191
1096
+ - type: map_at_5
1097
+ value: 16.456
1098
+ - type: mrr_at_1
1099
+ value: 66.25
1100
+ - type: mrr_at_10
1101
+ value: 74.4
1102
+ - type: mrr_at_100
1103
+ value: 74.715
1104
+ - type: mrr_at_1000
1105
+ value: 74.726
1106
+ - type: mrr_at_3
1107
+ value: 72.417
1108
+ - type: mrr_at_5
1109
+ value: 73.667
1110
+ - type: ndcg_at_1
1111
+ value: 54.25
1112
+ - type: ndcg_at_10
1113
+ value: 40.77
1114
+ - type: ndcg_at_100
1115
+ value: 46.359
1116
+ - type: ndcg_at_1000
1117
+ value: 54.193000000000005
1118
+ - type: ndcg_at_3
1119
+ value: 44.832
1120
+ - type: ndcg_at_5
1121
+ value: 42.63
1122
+ - type: precision_at_1
1123
+ value: 66.25
1124
+ - type: precision_at_10
1125
+ value: 32.175
1126
+ - type: precision_at_100
1127
+ value: 10.668
1128
+ - type: precision_at_1000
1129
+ value: 2.067
1130
+ - type: precision_at_3
1131
+ value: 47.667
1132
+ - type: precision_at_5
1133
+ value: 41.3
1134
+ - type: recall_at_1
1135
+ value: 9.151
1136
+ - type: recall_at_10
1137
+ value: 25.003999999999998
1138
+ - type: recall_at_100
1139
+ value: 52.976
1140
+ - type: recall_at_1000
1141
+ value: 78.315
1142
+ - type: recall_at_3
1143
+ value: 15.487
1144
+ - type: recall_at_5
1145
+ value: 18.999
1146
+ - task:
1147
+ type: Classification
1148
+ dataset:
1149
+ name: MTEB EmotionClassification
1150
+ type: mteb/emotion
1151
+ config: default
1152
+ split: test
1153
+ revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
1154
+ metrics:
1155
+ - type: accuracy
1156
+ value: 51.89999999999999
1157
+ - type: f1
1158
+ value: 46.47777925067403
1159
+ - task:
1160
+ type: Retrieval
1161
+ dataset:
1162
+ name: MTEB FEVER
1163
+ type: fever
1164
+ config: default
1165
+ split: test
1166
+ revision: None
1167
+ metrics:
1168
+ - type: map_at_1
1169
+ value: 73.706
1170
+ - type: map_at_10
1171
+ value: 82.423
1172
+ - type: map_at_100
1173
+ value: 82.67999999999999
1174
+ - type: map_at_1000
1175
+ value: 82.694
1176
+ - type: map_at_3
1177
+ value: 81.328
1178
+ - type: map_at_5
1179
+ value: 82.001
1180
+ - type: mrr_at_1
1181
+ value: 79.613
1182
+ - type: mrr_at_10
1183
+ value: 87.07000000000001
1184
+ - type: mrr_at_100
1185
+ value: 87.169
1186
+ - type: mrr_at_1000
1187
+ value: 87.17
1188
+ - type: mrr_at_3
1189
+ value: 86.404
1190
+ - type: mrr_at_5
1191
+ value: 86.856
1192
+ - type: ndcg_at_1
1193
+ value: 79.613
1194
+ - type: ndcg_at_10
1195
+ value: 86.289
1196
+ - type: ndcg_at_100
1197
+ value: 87.201
1198
+ - type: ndcg_at_1000
1199
+ value: 87.428
1200
+ - type: ndcg_at_3
1201
+ value: 84.625
1202
+ - type: ndcg_at_5
1203
+ value: 85.53699999999999
1204
+ - type: precision_at_1
1205
+ value: 79.613
1206
+ - type: precision_at_10
1207
+ value: 10.399
1208
+ - type: precision_at_100
1209
+ value: 1.1079999999999999
1210
+ - type: precision_at_1000
1211
+ value: 0.11499999999999999
1212
+ - type: precision_at_3
1213
+ value: 32.473
1214
+ - type: precision_at_5
1215
+ value: 20.132
1216
+ - type: recall_at_1
1217
+ value: 73.706
1218
+ - type: recall_at_10
1219
+ value: 93.559
1220
+ - type: recall_at_100
1221
+ value: 97.188
1222
+ - type: recall_at_1000
1223
+ value: 98.555
1224
+ - type: recall_at_3
1225
+ value: 88.98700000000001
1226
+ - type: recall_at_5
1227
+ value: 91.373
1228
+ - task:
1229
+ type: Retrieval
1230
+ dataset:
1231
+ name: MTEB FiQA2018
1232
+ type: fiqa
1233
+ config: default
1234
+ split: test
1235
+ revision: None
1236
+ metrics:
1237
+ - type: map_at_1
1238
+ value: 19.841
1239
+ - type: map_at_10
1240
+ value: 32.643
1241
+ - type: map_at_100
1242
+ value: 34.575
1243
+ - type: map_at_1000
1244
+ value: 34.736
1245
+ - type: map_at_3
1246
+ value: 28.317999999999998
1247
+ - type: map_at_5
1248
+ value: 30.964000000000002
1249
+ - type: mrr_at_1
1250
+ value: 39.660000000000004
1251
+ - type: mrr_at_10
1252
+ value: 48.620000000000005
1253
+ - type: mrr_at_100
1254
+ value: 49.384
1255
+ - type: mrr_at_1000
1256
+ value: 49.415
1257
+ - type: mrr_at_3
1258
+ value: 45.988
1259
+ - type: mrr_at_5
1260
+ value: 47.361
1261
+ - type: ndcg_at_1
1262
+ value: 39.660000000000004
1263
+ - type: ndcg_at_10
1264
+ value: 40.646
1265
+ - type: ndcg_at_100
1266
+ value: 47.657
1267
+ - type: ndcg_at_1000
1268
+ value: 50.428
1269
+ - type: ndcg_at_3
1270
+ value: 36.689
1271
+ - type: ndcg_at_5
1272
+ value: 38.211
1273
+ - type: precision_at_1
1274
+ value: 39.660000000000004
1275
+ - type: precision_at_10
1276
+ value: 11.235000000000001
1277
+ - type: precision_at_100
1278
+ value: 1.8530000000000002
1279
+ - type: precision_at_1000
1280
+ value: 0.23600000000000002
1281
+ - type: precision_at_3
1282
+ value: 24.587999999999997
1283
+ - type: precision_at_5
1284
+ value: 18.395
1285
+ - type: recall_at_1
1286
+ value: 19.841
1287
+ - type: recall_at_10
1288
+ value: 48.135
1289
+ - type: recall_at_100
1290
+ value: 74.224
1291
+ - type: recall_at_1000
1292
+ value: 90.826
1293
+ - type: recall_at_3
1294
+ value: 33.536
1295
+ - type: recall_at_5
1296
+ value: 40.311
1297
+ - task:
1298
+ type: Retrieval
1299
+ dataset:
1300
+ name: MTEB HotpotQA
1301
+ type: hotpotqa
1302
+ config: default
1303
+ split: test
1304
+ revision: None
1305
+ metrics:
1306
+ - type: map_at_1
1307
+ value: 40.358
1308
+ - type: map_at_10
1309
+ value: 64.497
1310
+ - type: map_at_100
1311
+ value: 65.362
1312
+ - type: map_at_1000
1313
+ value: 65.41900000000001
1314
+ - type: map_at_3
1315
+ value: 61.06700000000001
1316
+ - type: map_at_5
1317
+ value: 63.317
1318
+ - type: mrr_at_1
1319
+ value: 80.716
1320
+ - type: mrr_at_10
1321
+ value: 86.10799999999999
1322
+ - type: mrr_at_100
1323
+ value: 86.265
1324
+ - type: mrr_at_1000
1325
+ value: 86.27
1326
+ - type: mrr_at_3
1327
+ value: 85.271
1328
+ - type: mrr_at_5
1329
+ value: 85.82499999999999
1330
+ - type: ndcg_at_1
1331
+ value: 80.716
1332
+ - type: ndcg_at_10
1333
+ value: 72.597
1334
+ - type: ndcg_at_100
1335
+ value: 75.549
1336
+ - type: ndcg_at_1000
1337
+ value: 76.61
1338
+ - type: ndcg_at_3
1339
+ value: 67.874
1340
+ - type: ndcg_at_5
1341
+ value: 70.655
1342
+ - type: precision_at_1
1343
+ value: 80.716
1344
+ - type: precision_at_10
1345
+ value: 15.148
1346
+ - type: precision_at_100
1347
+ value: 1.745
1348
+ - type: precision_at_1000
1349
+ value: 0.188
1350
+ - type: precision_at_3
1351
+ value: 43.597
1352
+ - type: precision_at_5
1353
+ value: 28.351
1354
+ - type: recall_at_1
1355
+ value: 40.358
1356
+ - type: recall_at_10
1357
+ value: 75.739
1358
+ - type: recall_at_100
1359
+ value: 87.259
1360
+ - type: recall_at_1000
1361
+ value: 94.234
1362
+ - type: recall_at_3
1363
+ value: 65.39500000000001
1364
+ - type: recall_at_5
1365
+ value: 70.878
1366
+ - task:
1367
+ type: Classification
1368
+ dataset:
1369
+ name: MTEB ImdbClassification
1370
+ type: mteb/imdb
1371
+ config: default
1372
+ split: test
1373
+ revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
1374
+ metrics:
1375
+ - type: accuracy
1376
+ value: 90.80799999999998
1377
+ - type: ap
1378
+ value: 86.81350378180757
1379
+ - type: f1
1380
+ value: 90.79901248314215
1381
+ - task:
1382
+ type: Retrieval
1383
+ dataset:
1384
+ name: MTEB MSMARCO
1385
+ type: msmarco
1386
+ config: default
1387
+ split: dev
1388
+ revision: None
1389
+ metrics:
1390
+ - type: map_at_1
1391
+ value: 22.096
1392
+ - type: map_at_10
1393
+ value: 34.384
1394
+ - type: map_at_100
1395
+ value: 35.541
1396
+ - type: map_at_1000
1397
+ value: 35.589999999999996
1398
+ - type: map_at_3
1399
+ value: 30.496000000000002
1400
+ - type: map_at_5
1401
+ value: 32.718
1402
+ - type: mrr_at_1
1403
+ value: 22.750999999999998
1404
+ - type: mrr_at_10
1405
+ value: 35.024
1406
+ - type: mrr_at_100
1407
+ value: 36.125
1408
+ - type: mrr_at_1000
1409
+ value: 36.168
1410
+ - type: mrr_at_3
1411
+ value: 31.225
1412
+ - type: mrr_at_5
1413
+ value: 33.416000000000004
1414
+ - type: ndcg_at_1
1415
+ value: 22.750999999999998
1416
+ - type: ndcg_at_10
1417
+ value: 41.351
1418
+ - type: ndcg_at_100
1419
+ value: 46.92
1420
+ - type: ndcg_at_1000
1421
+ value: 48.111
1422
+ - type: ndcg_at_3
1423
+ value: 33.439
1424
+ - type: ndcg_at_5
1425
+ value: 37.407000000000004
1426
+ - type: precision_at_1
1427
+ value: 22.750999999999998
1428
+ - type: precision_at_10
1429
+ value: 6.564
1430
+ - type: precision_at_100
1431
+ value: 0.935
1432
+ - type: precision_at_1000
1433
+ value: 0.104
1434
+ - type: precision_at_3
1435
+ value: 14.288
1436
+ - type: precision_at_5
1437
+ value: 10.581999999999999
1438
+ - type: recall_at_1
1439
+ value: 22.096
1440
+ - type: recall_at_10
1441
+ value: 62.771
1442
+ - type: recall_at_100
1443
+ value: 88.529
1444
+ - type: recall_at_1000
1445
+ value: 97.55
1446
+ - type: recall_at_3
1447
+ value: 41.245
1448
+ - type: recall_at_5
1449
+ value: 50.788
1450
+ - task:
1451
+ type: Classification
1452
+ dataset:
1453
+ name: MTEB MTOPDomainClassification (en)
1454
+ type: mteb/mtop_domain
1455
+ config: en
1456
+ split: test
1457
+ revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
1458
+ metrics:
1459
+ - type: accuracy
1460
+ value: 94.16780665754673
1461
+ - type: f1
1462
+ value: 93.96331194859894
1463
+ - task:
1464
+ type: Classification
1465
+ dataset:
1466
+ name: MTEB MTOPIntentClassification (en)
1467
+ type: mteb/mtop_intent
1468
+ config: en
1469
+ split: test
1470
+ revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1471
+ metrics:
1472
+ - type: accuracy
1473
+ value: 76.90606475148198
1474
+ - type: f1
1475
+ value: 58.58344986604187
1476
+ - task:
1477
+ type: Classification
1478
+ dataset:
1479
+ name: MTEB MassiveIntentClassification (en)
1480
+ type: mteb/amazon_massive_intent
1481
+ config: en
1482
+ split: test
1483
+ revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
1484
+ metrics:
1485
+ - type: accuracy
1486
+ value: 76.14660390047075
1487
+ - type: f1
1488
+ value: 74.31533923533614
1489
+ - task:
1490
+ type: Classification
1491
+ dataset:
1492
+ name: MTEB MassiveScenarioClassification (en)
1493
+ type: mteb/amazon_massive_scenario
1494
+ config: en
1495
+ split: test
1496
+ revision: 7d571f92784cd94a019292a1f45445077d0ef634
1497
+ metrics:
1498
+ - type: accuracy
1499
+ value: 80.16139878950908
1500
+ - type: f1
1501
+ value: 80.18532656824924
1502
+ - task:
1503
+ type: Clustering
1504
+ dataset:
1505
+ name: MTEB MedrxivClusteringP2P
1506
+ type: mteb/medrxiv-clustering-p2p
1507
+ config: default
1508
+ split: test
1509
+ revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
1510
+ metrics:
1511
+ - type: v_measure
1512
+ value: 32.949880906135085
1513
+ - task:
1514
+ type: Clustering
1515
+ dataset:
1516
+ name: MTEB MedrxivClusteringS2S
1517
+ type: mteb/medrxiv-clustering-s2s
1518
+ config: default
1519
+ split: test
1520
+ revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
1521
+ metrics:
1522
+ - type: v_measure
1523
+ value: 31.56300351524862
1524
+ - task:
1525
+ type: Reranking
1526
+ dataset:
1527
+ name: MTEB MindSmallReranking
1528
+ type: mteb/mind_small
1529
+ config: default
1530
+ split: test
1531
+ revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
1532
+ metrics:
1533
+ - type: map
1534
+ value: 31.196521894371315
1535
+ - type: mrr
1536
+ value: 32.22644231694389
1537
+ - task:
1538
+ type: Retrieval
1539
+ dataset:
1540
+ name: MTEB NFCorpus
1541
+ type: nfcorpus
1542
+ config: default
1543
+ split: test
1544
+ revision: None
1545
+ metrics:
1546
+ - type: map_at_1
1547
+ value: 6.783
1548
+ - type: map_at_10
1549
+ value: 14.549000000000001
1550
+ - type: map_at_100
1551
+ value: 18.433
1552
+ - type: map_at_1000
1553
+ value: 19.949
1554
+ - type: map_at_3
1555
+ value: 10.936
1556
+ - type: map_at_5
1557
+ value: 12.514
1558
+ - type: mrr_at_1
1559
+ value: 47.368
1560
+ - type: mrr_at_10
1561
+ value: 56.42
1562
+ - type: mrr_at_100
1563
+ value: 56.908
1564
+ - type: mrr_at_1000
1565
+ value: 56.95
1566
+ - type: mrr_at_3
1567
+ value: 54.283
1568
+ - type: mrr_at_5
1569
+ value: 55.568
1570
+ - type: ndcg_at_1
1571
+ value: 45.666000000000004
1572
+ - type: ndcg_at_10
1573
+ value: 37.389
1574
+ - type: ndcg_at_100
1575
+ value: 34.253
1576
+ - type: ndcg_at_1000
1577
+ value: 43.059999999999995
1578
+ - type: ndcg_at_3
1579
+ value: 42.725
1580
+ - type: ndcg_at_5
1581
+ value: 40.193
1582
+ - type: precision_at_1
1583
+ value: 47.368
1584
+ - type: precision_at_10
1585
+ value: 27.988000000000003
1586
+ - type: precision_at_100
1587
+ value: 8.672
1588
+ - type: precision_at_1000
1589
+ value: 2.164
1590
+ - type: precision_at_3
1591
+ value: 40.248
1592
+ - type: precision_at_5
1593
+ value: 34.737
1594
+ - type: recall_at_1
1595
+ value: 6.783
1596
+ - type: recall_at_10
1597
+ value: 17.838
1598
+ - type: recall_at_100
1599
+ value: 33.672000000000004
1600
+ - type: recall_at_1000
1601
+ value: 66.166
1602
+ - type: recall_at_3
1603
+ value: 11.849
1604
+ - type: recall_at_5
1605
+ value: 14.205000000000002
1606
+ - task:
1607
+ type: Retrieval
1608
+ dataset:
1609
+ name: MTEB NQ
1610
+ type: nq
1611
+ config: default
1612
+ split: test
1613
+ revision: None
1614
+ metrics:
1615
+ - type: map_at_1
1616
+ value: 31.698999999999998
1617
+ - type: map_at_10
1618
+ value: 46.556
1619
+ - type: map_at_100
1620
+ value: 47.652
1621
+ - type: map_at_1000
1622
+ value: 47.68
1623
+ - type: map_at_3
1624
+ value: 42.492000000000004
1625
+ - type: map_at_5
1626
+ value: 44.763999999999996
1627
+ - type: mrr_at_1
1628
+ value: 35.747
1629
+ - type: mrr_at_10
1630
+ value: 49.242999999999995
1631
+ - type: mrr_at_100
1632
+ value: 50.052
1633
+ - type: mrr_at_1000
1634
+ value: 50.068
1635
+ - type: mrr_at_3
1636
+ value: 45.867000000000004
1637
+ - type: mrr_at_5
1638
+ value: 47.778999999999996
1639
+ - type: ndcg_at_1
1640
+ value: 35.717999999999996
1641
+ - type: ndcg_at_10
1642
+ value: 54.14600000000001
1643
+ - type: ndcg_at_100
1644
+ value: 58.672999999999995
1645
+ - type: ndcg_at_1000
1646
+ value: 59.279
1647
+ - type: ndcg_at_3
1648
+ value: 46.407
1649
+ - type: ndcg_at_5
1650
+ value: 50.181
1651
+ - type: precision_at_1
1652
+ value: 35.717999999999996
1653
+ - type: precision_at_10
1654
+ value: 8.844000000000001
1655
+ - type: precision_at_100
1656
+ value: 1.139
1657
+ - type: precision_at_1000
1658
+ value: 0.12
1659
+ - type: precision_at_3
1660
+ value: 20.993000000000002
1661
+ - type: precision_at_5
1662
+ value: 14.791000000000002
1663
+ - type: recall_at_1
1664
+ value: 31.698999999999998
1665
+ - type: recall_at_10
1666
+ value: 74.693
1667
+ - type: recall_at_100
1668
+ value: 94.15299999999999
1669
+ - type: recall_at_1000
1670
+ value: 98.585
1671
+ - type: recall_at_3
1672
+ value: 54.388999999999996
1673
+ - type: recall_at_5
1674
+ value: 63.08200000000001
1675
+ - task:
1676
+ type: Retrieval
1677
+ dataset:
1678
+ name: MTEB QuoraRetrieval
1679
+ type: quora
1680
+ config: default
1681
+ split: test
1682
+ revision: None
1683
+ metrics:
1684
+ - type: map_at_1
1685
+ value: 71.283
1686
+ - type: map_at_10
1687
+ value: 85.24000000000001
1688
+ - type: map_at_100
1689
+ value: 85.882
1690
+ - type: map_at_1000
1691
+ value: 85.897
1692
+ - type: map_at_3
1693
+ value: 82.326
1694
+ - type: map_at_5
1695
+ value: 84.177
1696
+ - type: mrr_at_1
1697
+ value: 82.21000000000001
1698
+ - type: mrr_at_10
1699
+ value: 88.228
1700
+ - type: mrr_at_100
1701
+ value: 88.32
1702
+ - type: mrr_at_1000
1703
+ value: 88.32
1704
+ - type: mrr_at_3
1705
+ value: 87.323
1706
+ - type: mrr_at_5
1707
+ value: 87.94800000000001
1708
+ - type: ndcg_at_1
1709
+ value: 82.17999999999999
1710
+ - type: ndcg_at_10
1711
+ value: 88.9
1712
+ - type: ndcg_at_100
1713
+ value: 90.079
1714
+ - type: ndcg_at_1000
1715
+ value: 90.158
1716
+ - type: ndcg_at_3
1717
+ value: 86.18299999999999
1718
+ - type: ndcg_at_5
1719
+ value: 87.71799999999999
1720
+ - type: precision_at_1
1721
+ value: 82.17999999999999
1722
+ - type: precision_at_10
1723
+ value: 13.464
1724
+ - type: precision_at_100
1725
+ value: 1.533
1726
+ - type: precision_at_1000
1727
+ value: 0.157
1728
+ - type: precision_at_3
1729
+ value: 37.693
1730
+ - type: precision_at_5
1731
+ value: 24.792
1732
+ - type: recall_at_1
1733
+ value: 71.283
1734
+ - type: recall_at_10
1735
+ value: 95.742
1736
+ - type: recall_at_100
1737
+ value: 99.67200000000001
1738
+ - type: recall_at_1000
1739
+ value: 99.981
1740
+ - type: recall_at_3
1741
+ value: 87.888
1742
+ - type: recall_at_5
1743
+ value: 92.24
1744
+ - task:
1745
+ type: Clustering
1746
+ dataset:
1747
+ name: MTEB RedditClustering
1748
+ type: mteb/reddit-clustering
1749
+ config: default
1750
+ split: test
1751
+ revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
1752
+ metrics:
1753
+ - type: v_measure
1754
+ value: 56.24267063669042
1755
+ - task:
1756
+ type: Clustering
1757
+ dataset:
1758
+ name: MTEB RedditClusteringP2P
1759
+ type: mteb/reddit-clustering-p2p
1760
+ config: default
1761
+ split: test
1762
+ revision: 282350215ef01743dc01b456c7f5241fa8937f16
1763
+ metrics:
1764
+ - type: v_measure
1765
+ value: 62.88056988932578
1766
+ - task:
1767
+ type: Retrieval
1768
+ dataset:
1769
+ name: MTEB SCIDOCS
1770
+ type: scidocs
1771
+ config: default
1772
+ split: test
1773
+ revision: None
1774
+ metrics:
1775
+ - type: map_at_1
1776
+ value: 4.903
1777
+ - type: map_at_10
1778
+ value: 13.202
1779
+ - type: map_at_100
1780
+ value: 15.5
1781
+ - type: map_at_1000
1782
+ value: 15.870999999999999
1783
+ - type: map_at_3
1784
+ value: 9.407
1785
+ - type: map_at_5
1786
+ value: 11.238
1787
+ - type: mrr_at_1
1788
+ value: 24.2
1789
+ - type: mrr_at_10
1790
+ value: 35.867
1791
+ - type: mrr_at_100
1792
+ value: 37.001
1793
+ - type: mrr_at_1000
1794
+ value: 37.043
1795
+ - type: mrr_at_3
1796
+ value: 32.5
1797
+ - type: mrr_at_5
1798
+ value: 34.35
1799
+ - type: ndcg_at_1
1800
+ value: 24.2
1801
+ - type: ndcg_at_10
1802
+ value: 21.731
1803
+ - type: ndcg_at_100
1804
+ value: 30.7
1805
+ - type: ndcg_at_1000
1806
+ value: 36.618
1807
+ - type: ndcg_at_3
1808
+ value: 20.72
1809
+ - type: ndcg_at_5
1810
+ value: 17.954
1811
+ - type: precision_at_1
1812
+ value: 24.2
1813
+ - type: precision_at_10
1814
+ value: 11.33
1815
+ - type: precision_at_100
1816
+ value: 2.4410000000000003
1817
+ - type: precision_at_1000
1818
+ value: 0.386
1819
+ - type: precision_at_3
1820
+ value: 19.667
1821
+ - type: precision_at_5
1822
+ value: 15.86
1823
+ - type: recall_at_1
1824
+ value: 4.903
1825
+ - type: recall_at_10
1826
+ value: 22.962
1827
+ - type: recall_at_100
1828
+ value: 49.563
1829
+ - type: recall_at_1000
1830
+ value: 78.238
1831
+ - type: recall_at_3
1832
+ value: 11.953
1833
+ - type: recall_at_5
1834
+ value: 16.067999999999998
1835
+ - task:
1836
+ type: STS
1837
+ dataset:
1838
+ name: MTEB SICK-R
1839
+ type: mteb/sickr-sts
1840
+ config: default
1841
+ split: test
1842
+ revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
1843
+ metrics:
1844
+ - type: cos_sim_pearson
1845
+ value: 84.12694254604078
1846
+ - type: cos_sim_spearman
1847
+ value: 80.30141815181918
1848
+ - type: euclidean_pearson
1849
+ value: 81.34015449877128
1850
+ - type: euclidean_spearman
1851
+ value: 80.13984197010849
1852
+ - type: manhattan_pearson
1853
+ value: 81.31767068124086
1854
+ - type: manhattan_spearman
1855
+ value: 80.11720513114103
1856
+ - task:
1857
+ type: STS
1858
+ dataset:
1859
+ name: MTEB STS12
1860
+ type: mteb/sts12-sts
1861
+ config: default
1862
+ split: test
1863
+ revision: a0d554a64d88156834ff5ae9920b964011b16384
1864
+ metrics:
1865
+ - type: cos_sim_pearson
1866
+ value: 86.13112984010417
1867
+ - type: cos_sim_spearman
1868
+ value: 78.03063573402875
1869
+ - type: euclidean_pearson
1870
+ value: 83.51928418844804
1871
+ - type: euclidean_spearman
1872
+ value: 78.4045235411144
1873
+ - type: manhattan_pearson
1874
+ value: 83.49981637388689
1875
+ - type: manhattan_spearman
1876
+ value: 78.4042575139372
1877
+ - task:
1878
+ type: STS
1879
+ dataset:
1880
+ name: MTEB STS13
1881
+ type: mteb/sts13-sts
1882
+ config: default
1883
+ split: test
1884
+ revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
1885
+ metrics:
1886
+ - type: cos_sim_pearson
1887
+ value: 82.50327987379504
1888
+ - type: cos_sim_spearman
1889
+ value: 84.18556767756205
1890
+ - type: euclidean_pearson
1891
+ value: 82.69684424327679
1892
+ - type: euclidean_spearman
1893
+ value: 83.5368106038335
1894
+ - type: manhattan_pearson
1895
+ value: 82.57967581007374
1896
+ - type: manhattan_spearman
1897
+ value: 83.43009053133697
1898
+ - task:
1899
+ type: STS
1900
+ dataset:
1901
+ name: MTEB STS14
1902
+ type: mteb/sts14-sts
1903
+ config: default
1904
+ split: test
1905
+ revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
1906
+ metrics:
1907
+ - type: cos_sim_pearson
1908
+ value: 82.50756863007814
1909
+ - type: cos_sim_spearman
1910
+ value: 82.27204331279108
1911
+ - type: euclidean_pearson
1912
+ value: 81.39535251429741
1913
+ - type: euclidean_spearman
1914
+ value: 81.84386626336239
1915
+ - type: manhattan_pearson
1916
+ value: 81.34281737280695
1917
+ - type: manhattan_spearman
1918
+ value: 81.81149375673166
1919
+ - task:
1920
+ type: STS
1921
+ dataset:
1922
+ name: MTEB STS15
1923
+ type: mteb/sts15-sts
1924
+ config: default
1925
+ split: test
1926
+ revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
1927
+ metrics:
1928
+ - type: cos_sim_pearson
1929
+ value: 86.8727714856726
1930
+ - type: cos_sim_spearman
1931
+ value: 87.95738287792312
1932
+ - type: euclidean_pearson
1933
+ value: 86.62920602795887
1934
+ - type: euclidean_spearman
1935
+ value: 87.05207355381243
1936
+ - type: manhattan_pearson
1937
+ value: 86.53587918472225
1938
+ - type: manhattan_spearman
1939
+ value: 86.95382961029586
1940
+ - task:
1941
+ type: STS
1942
+ dataset:
1943
+ name: MTEB STS16
1944
+ type: mteb/sts16-sts
1945
+ config: default
1946
+ split: test
1947
+ revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
1948
+ metrics:
1949
+ - type: cos_sim_pearson
1950
+ value: 83.52240359769479
1951
+ - type: cos_sim_spearman
1952
+ value: 85.47685776238286
1953
+ - type: euclidean_pearson
1954
+ value: 84.25815333483058
1955
+ - type: euclidean_spearman
1956
+ value: 85.27415639683198
1957
+ - type: manhattan_pearson
1958
+ value: 84.29127757025637
1959
+ - type: manhattan_spearman
1960
+ value: 85.30226224917351
1961
+ - task:
1962
+ type: STS
1963
+ dataset:
1964
+ name: MTEB STS17 (en-en)
1965
+ type: mteb/sts17-crosslingual-sts
1966
+ config: en-en
1967
+ split: test
1968
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
1969
+ metrics:
1970
+ - type: cos_sim_pearson
1971
+ value: 86.42501708915708
1972
+ - type: cos_sim_spearman
1973
+ value: 86.42276182795041
1974
+ - type: euclidean_pearson
1975
+ value: 86.5408207354761
1976
+ - type: euclidean_spearman
1977
+ value: 85.46096321750838
1978
+ - type: manhattan_pearson
1979
+ value: 86.54177303026881
1980
+ - type: manhattan_spearman
1981
+ value: 85.50313151916117
1982
+ - task:
1983
+ type: STS
1984
+ dataset:
1985
+ name: MTEB STS22 (en)
1986
+ type: mteb/sts22-crosslingual-sts
1987
+ config: en
1988
+ split: test
1989
+ revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
1990
+ metrics:
1991
+ - type: cos_sim_pearson
1992
+ value: 64.86521089250766
1993
+ - type: cos_sim_spearman
1994
+ value: 65.94868540323003
1995
+ - type: euclidean_pearson
1996
+ value: 67.16569626533084
1997
+ - type: euclidean_spearman
1998
+ value: 66.37667004134917
1999
+ - type: manhattan_pearson
2000
+ value: 67.1482365102333
2001
+ - type: manhattan_spearman
2002
+ value: 66.53240122580029
2003
+ - task:
2004
+ type: STS
2005
+ dataset:
2006
+ name: MTEB STSBenchmark
2007
+ type: mteb/stsbenchmark-sts
2008
+ config: default
2009
+ split: test
2010
+ revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
2011
+ metrics:
2012
+ - type: cos_sim_pearson
2013
+ value: 84.64746265365318
2014
+ - type: cos_sim_spearman
2015
+ value: 86.41888825906786
2016
+ - type: euclidean_pearson
2017
+ value: 85.27453642725811
2018
+ - type: euclidean_spearman
2019
+ value: 85.94095796602544
2020
+ - type: manhattan_pearson
2021
+ value: 85.28643660505334
2022
+ - type: manhattan_spearman
2023
+ value: 85.95028003260744
2024
+ - task:
2025
+ type: Reranking
2026
+ dataset:
2027
+ name: MTEB SciDocsRR
2028
+ type: mteb/scidocs-reranking
2029
+ config: default
2030
+ split: test
2031
+ revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
2032
+ metrics:
2033
+ - type: map
2034
+ value: 87.48903153618527
2035
+ - type: mrr
2036
+ value: 96.41081503826601
2037
+ - task:
2038
+ type: Retrieval
2039
+ dataset:
2040
+ name: MTEB SciFact
2041
+ type: scifact
2042
+ config: default
2043
+ split: test
2044
+ revision: None
2045
+ metrics:
2046
+ - type: map_at_1
2047
+ value: 58.594
2048
+ - type: map_at_10
2049
+ value: 69.296
2050
+ - type: map_at_100
2051
+ value: 69.782
2052
+ - type: map_at_1000
2053
+ value: 69.795
2054
+ - type: map_at_3
2055
+ value: 66.23
2056
+ - type: map_at_5
2057
+ value: 68.293
2058
+ - type: mrr_at_1
2059
+ value: 61.667
2060
+ - type: mrr_at_10
2061
+ value: 70.339
2062
+ - type: mrr_at_100
2063
+ value: 70.708
2064
+ - type: mrr_at_1000
2065
+ value: 70.722
2066
+ - type: mrr_at_3
2067
+ value: 68.0
2068
+ - type: mrr_at_5
2069
+ value: 69.56700000000001
2070
+ - type: ndcg_at_1
2071
+ value: 61.667
2072
+ - type: ndcg_at_10
2073
+ value: 74.039
2074
+ - type: ndcg_at_100
2075
+ value: 76.103
2076
+ - type: ndcg_at_1000
2077
+ value: 76.47800000000001
2078
+ - type: ndcg_at_3
2079
+ value: 68.967
2080
+ - type: ndcg_at_5
2081
+ value: 71.96900000000001
2082
+ - type: precision_at_1
2083
+ value: 61.667
2084
+ - type: precision_at_10
2085
+ value: 9.866999999999999
2086
+ - type: precision_at_100
2087
+ value: 1.097
2088
+ - type: precision_at_1000
2089
+ value: 0.11299999999999999
2090
+ - type: precision_at_3
2091
+ value: 27.111
2092
+ - type: precision_at_5
2093
+ value: 18.2
2094
+ - type: recall_at_1
2095
+ value: 58.594
2096
+ - type: recall_at_10
2097
+ value: 87.422
2098
+ - type: recall_at_100
2099
+ value: 96.667
2100
+ - type: recall_at_1000
2101
+ value: 99.667
2102
+ - type: recall_at_3
2103
+ value: 74.217
2104
+ - type: recall_at_5
2105
+ value: 81.539
2106
+ - task:
2107
+ type: PairClassification
2108
+ dataset:
2109
+ name: MTEB SprintDuplicateQuestions
2110
+ type: mteb/sprintduplicatequestions-pairclassification
2111
+ config: default
2112
+ split: test
2113
+ revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
2114
+ metrics:
2115
+ - type: cos_sim_accuracy
2116
+ value: 99.85049504950496
2117
+ - type: cos_sim_ap
2118
+ value: 96.33111544137081
2119
+ - type: cos_sim_f1
2120
+ value: 92.35443037974684
2121
+ - type: cos_sim_precision
2122
+ value: 93.53846153846153
2123
+ - type: cos_sim_recall
2124
+ value: 91.2
2125
+ - type: dot_accuracy
2126
+ value: 99.82376237623762
2127
+ - type: dot_ap
2128
+ value: 95.38082527310888
2129
+ - type: dot_f1
2130
+ value: 90.90909090909092
2131
+ - type: dot_precision
2132
+ value: 92.90187891440502
2133
+ - type: dot_recall
2134
+ value: 89.0
2135
+ - type: euclidean_accuracy
2136
+ value: 99.84851485148515
2137
+ - type: euclidean_ap
2138
+ value: 96.32316003996347
2139
+ - type: euclidean_f1
2140
+ value: 92.2071392659628
2141
+ - type: euclidean_precision
2142
+ value: 92.71991911021233
2143
+ - type: euclidean_recall
2144
+ value: 91.7
2145
+ - type: manhattan_accuracy
2146
+ value: 99.84851485148515
2147
+ - type: manhattan_ap
2148
+ value: 96.3655668249217
2149
+ - type: manhattan_f1
2150
+ value: 92.18356026222895
2151
+ - type: manhattan_precision
2152
+ value: 92.98067141403867
2153
+ - type: manhattan_recall
2154
+ value: 91.4
2155
+ - type: max_accuracy
2156
+ value: 99.85049504950496
2157
+ - type: max_ap
2158
+ value: 96.3655668249217
2159
+ - type: max_f1
2160
+ value: 92.35443037974684
2161
+ - task:
2162
+ type: Clustering
2163
+ dataset:
2164
+ name: MTEB StackExchangeClustering
2165
+ type: mteb/stackexchange-clustering
2166
+ config: default
2167
+ split: test
2168
+ revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
2169
+ metrics:
2170
+ - type: v_measure
2171
+ value: 65.94861371629051
2172
+ - task:
2173
+ type: Clustering
2174
+ dataset:
2175
+ name: MTEB StackExchangeClusteringP2P
2176
+ type: mteb/stackexchange-clustering-p2p
2177
+ config: default
2178
+ split: test
2179
+ revision: 815ca46b2622cec33ccafc3735d572c266efdb44
2180
+ metrics:
2181
+ - type: v_measure
2182
+ value: 35.009430451385
2183
+ - task:
2184
+ type: Reranking
2185
+ dataset:
2186
+ name: MTEB StackOverflowDupQuestions
2187
+ type: mteb/stackoverflowdupquestions-reranking
2188
+ config: default
2189
+ split: test
2190
+ revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
2191
+ metrics:
2192
+ - type: map
2193
+ value: 54.61164066427969
2194
+ - type: mrr
2195
+ value: 55.49710603938544
2196
+ - task:
2197
+ type: Summarization
2198
+ dataset:
2199
+ name: MTEB SummEval
2200
+ type: mteb/summeval
2201
+ config: default
2202
+ split: test
2203
+ revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
2204
+ metrics:
2205
+ - type: cos_sim_pearson
2206
+ value: 30.622620124907662
2207
+ - type: cos_sim_spearman
2208
+ value: 31.0678351356163
2209
+ - type: dot_pearson
2210
+ value: 30.863727693306814
2211
+ - type: dot_spearman
2212
+ value: 31.230306567021255
2213
+ - task:
2214
+ type: Retrieval
2215
+ dataset:
2216
+ name: MTEB TRECCOVID
2217
+ type: trec-covid
2218
+ config: default
2219
+ split: test
2220
+ revision: None
2221
+ metrics:
2222
+ - type: map_at_1
2223
+ value: 0.22
2224
+ - type: map_at_10
2225
+ value: 2.011
2226
+ - type: map_at_100
2227
+ value: 10.974
2228
+ - type: map_at_1000
2229
+ value: 25.819
2230
+ - type: map_at_3
2231
+ value: 0.6649999999999999
2232
+ - type: map_at_5
2233
+ value: 1.076
2234
+ - type: mrr_at_1
2235
+ value: 86.0
2236
+ - type: mrr_at_10
2237
+ value: 91.8
2238
+ - type: mrr_at_100
2239
+ value: 91.8
2240
+ - type: mrr_at_1000
2241
+ value: 91.8
2242
+ - type: mrr_at_3
2243
+ value: 91.0
2244
+ - type: mrr_at_5
2245
+ value: 91.8
2246
+ - type: ndcg_at_1
2247
+ value: 82.0
2248
+ - type: ndcg_at_10
2249
+ value: 78.07300000000001
2250
+ - type: ndcg_at_100
2251
+ value: 58.231
2252
+ - type: ndcg_at_1000
2253
+ value: 51.153000000000006
2254
+ - type: ndcg_at_3
2255
+ value: 81.123
2256
+ - type: ndcg_at_5
2257
+ value: 81.059
2258
+ - type: precision_at_1
2259
+ value: 86.0
2260
+ - type: precision_at_10
2261
+ value: 83.0
2262
+ - type: precision_at_100
2263
+ value: 59.38
2264
+ - type: precision_at_1000
2265
+ value: 22.55
2266
+ - type: precision_at_3
2267
+ value: 87.333
2268
+ - type: precision_at_5
2269
+ value: 86.8
2270
+ - type: recall_at_1
2271
+ value: 0.22
2272
+ - type: recall_at_10
2273
+ value: 2.2079999999999997
2274
+ - type: recall_at_100
2275
+ value: 14.069
2276
+ - type: recall_at_1000
2277
+ value: 47.678
2278
+ - type: recall_at_3
2279
+ value: 0.7040000000000001
2280
+ - type: recall_at_5
2281
+ value: 1.161
2282
+ - task:
2283
+ type: Retrieval
2284
+ dataset:
2285
+ name: MTEB Touche2020
2286
+ type: webis-touche2020
2287
+ config: default
2288
+ split: test
2289
+ revision: None
2290
+ metrics:
2291
+ - type: map_at_1
2292
+ value: 2.809
2293
+ - type: map_at_10
2294
+ value: 10.394
2295
+ - type: map_at_100
2296
+ value: 16.598
2297
+ - type: map_at_1000
2298
+ value: 18.142
2299
+ - type: map_at_3
2300
+ value: 5.572
2301
+ - type: map_at_5
2302
+ value: 7.1370000000000005
2303
+ - type: mrr_at_1
2304
+ value: 32.653
2305
+ - type: mrr_at_10
2306
+ value: 46.564
2307
+ - type: mrr_at_100
2308
+ value: 47.469
2309
+ - type: mrr_at_1000
2310
+ value: 47.469
2311
+ - type: mrr_at_3
2312
+ value: 42.177
2313
+ - type: mrr_at_5
2314
+ value: 44.524
2315
+ - type: ndcg_at_1
2316
+ value: 30.612000000000002
2317
+ - type: ndcg_at_10
2318
+ value: 25.701
2319
+ - type: ndcg_at_100
2320
+ value: 37.532
2321
+ - type: ndcg_at_1000
2322
+ value: 48.757
2323
+ - type: ndcg_at_3
2324
+ value: 28.199999999999996
2325
+ - type: ndcg_at_5
2326
+ value: 25.987
2327
+ - type: precision_at_1
2328
+ value: 32.653
2329
+ - type: precision_at_10
2330
+ value: 23.469
2331
+ - type: precision_at_100
2332
+ value: 7.9799999999999995
2333
+ - type: precision_at_1000
2334
+ value: 1.5350000000000001
2335
+ - type: precision_at_3
2336
+ value: 29.932
2337
+ - type: precision_at_5
2338
+ value: 26.122
2339
+ - type: recall_at_1
2340
+ value: 2.809
2341
+ - type: recall_at_10
2342
+ value: 16.887
2343
+ - type: recall_at_100
2344
+ value: 48.67
2345
+ - type: recall_at_1000
2346
+ value: 82.89699999999999
2347
+ - type: recall_at_3
2348
+ value: 6.521000000000001
2349
+ - type: recall_at_5
2350
+ value: 9.609
2351
+ - task:
2352
+ type: Classification
2353
+ dataset:
2354
+ name: MTEB ToxicConversationsClassification
2355
+ type: mteb/toxic_conversations_50k
2356
+ config: default
2357
+ split: test
2358
+ revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
2359
+ metrics:
2360
+ - type: accuracy
2361
+ value: 71.57860000000001
2362
+ - type: ap
2363
+ value: 13.82629211536393
2364
+ - type: f1
2365
+ value: 54.59860966183956
2366
+ - task:
2367
+ type: Classification
2368
+ dataset:
2369
+ name: MTEB TweetSentimentExtractionClassification
2370
+ type: mteb/tweet_sentiment_extraction
2371
+ config: default
2372
+ split: test
2373
+ revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
2374
+ metrics:
2375
+ - type: accuracy
2376
+ value: 59.38030560271647
2377
+ - type: f1
2378
+ value: 59.69685552567865
2379
+ - task:
2380
+ type: Clustering
2381
+ dataset:
2382
+ name: MTEB TwentyNewsgroupsClustering
2383
+ type: mteb/twentynewsgroups-clustering
2384
+ config: default
2385
+ split: test
2386
+ revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
2387
+ metrics:
2388
+ - type: v_measure
2389
+ value: 51.4736717043405
2390
+ - task:
2391
+ type: PairClassification
2392
+ dataset:
2393
+ name: MTEB TwitterSemEval2015
2394
+ type: mteb/twittersemeval2015-pairclassification
2395
+ config: default
2396
+ split: test
2397
+ revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
2398
+ metrics:
2399
+ - type: cos_sim_accuracy
2400
+ value: 86.92853311080646
2401
+ - type: cos_sim_ap
2402
+ value: 77.67872502591382
2403
+ - type: cos_sim_f1
2404
+ value: 70.33941236068895
2405
+ - type: cos_sim_precision
2406
+ value: 67.63273258645884
2407
+ - type: cos_sim_recall
2408
+ value: 73.27176781002639
2409
+ - type: dot_accuracy
2410
+ value: 85.79603027954938
2411
+ - type: dot_ap
2412
+ value: 73.73786190233379
2413
+ - type: dot_f1
2414
+ value: 67.3437901774235
2415
+ - type: dot_precision
2416
+ value: 65.67201604814443
2417
+ - type: dot_recall
2418
+ value: 69.10290237467018
2419
+ - type: euclidean_accuracy
2420
+ value: 86.94045419324074
2421
+ - type: euclidean_ap
2422
+ value: 77.6687791535167
2423
+ - type: euclidean_f1
2424
+ value: 70.47209214023542
2425
+ - type: euclidean_precision
2426
+ value: 67.7207492094381
2427
+ - type: euclidean_recall
2428
+ value: 73.45646437994723
2429
+ - type: manhattan_accuracy
2430
+ value: 86.87488823985218
2431
+ - type: manhattan_ap
2432
+ value: 77.63373392430728
2433
+ - type: manhattan_f1
2434
+ value: 70.40920716112532
2435
+ - type: manhattan_precision
2436
+ value: 68.31265508684864
2437
+ - type: manhattan_recall
2438
+ value: 72.63852242744063
2439
+ - type: max_accuracy
2440
+ value: 86.94045419324074
2441
+ - type: max_ap
2442
+ value: 77.67872502591382
2443
+ - type: max_f1
2444
+ value: 70.47209214023542
2445
+ - task:
2446
+ type: PairClassification
2447
+ dataset:
2448
+ name: MTEB TwitterURLCorpus
2449
+ type: mteb/twitterurlcorpus-pairclassification
2450
+ config: default
2451
+ split: test
2452
+ revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
2453
+ metrics:
2454
+ - type: cos_sim_accuracy
2455
+ value: 88.67155664221679
2456
+ - type: cos_sim_ap
2457
+ value: 85.64591703003417
2458
+ - type: cos_sim_f1
2459
+ value: 77.59531005352656
2460
+ - type: cos_sim_precision
2461
+ value: 73.60967184801382
2462
+ - type: cos_sim_recall
2463
+ value: 82.03726516784724
2464
+ - type: dot_accuracy
2465
+ value: 88.41541506578181
2466
+ - type: dot_ap
2467
+ value: 84.6482788957769
2468
+ - type: dot_f1
2469
+ value: 77.04748541466657
2470
+ - type: dot_precision
2471
+ value: 74.02440754931176
2472
+ - type: dot_recall
2473
+ value: 80.3279950723745
2474
+ - type: euclidean_accuracy
2475
+ value: 88.63080684596576
2476
+ - type: euclidean_ap
2477
+ value: 85.44570045321562
2478
+ - type: euclidean_f1
2479
+ value: 77.28769403336106
2480
+ - type: euclidean_precision
2481
+ value: 72.90600040958427
2482
+ - type: euclidean_recall
2483
+ value: 82.22975053895904
2484
+ - type: manhattan_accuracy
2485
+ value: 88.59393798269105
2486
+ - type: manhattan_ap
2487
+ value: 85.40271361038187
2488
+ - type: manhattan_f1
2489
+ value: 77.17606419344392
2490
+ - type: manhattan_precision
2491
+ value: 72.4447747078295
2492
+ - type: manhattan_recall
2493
+ value: 82.5685247921158
2494
+ - type: max_accuracy
2495
+ value: 88.67155664221679
2496
+ - type: max_ap
2497
+ value: 85.64591703003417
2498
+ - type: max_f1
2499
+ value: 77.59531005352656
2500
+ ---
2501
+ # Neuronx model for [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)
2502
+
2503
+ This repository contains are [**AWS Inferentia2**](https://aws.amazon.com/ec2/instance-types/inf2/) and [`neuronx`](https://awsdocs-neuron.readthedocs-hosted.com/en/latest/) compatible checkpoint for [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5). You can find detailed information about the base model on its [Model Card](https://huggingface.co/BAAI/bge-base-en-v1.5).
2504
+
2505
+ ## Usage on Amazon SageMaker
2506
+
2507
+ _coming soon_
2508
+
2509
+ ## Usage with optimum-neuron
2510
+
2511
+ ```python
2512
+
2513
+ from optimum.neuron import pipeline
2514
+
2515
+ # Load pipeline from Hugging Face repository
2516
+ pipe = pipeline("text-generation", "aws-neuron/bge-base-en-v1-5-seqlen-384-bs-1")
2517
+
2518
+ # We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
2519
+ messages = [
2520
+ {"role": "user", "content": "What is 2+2?"},
2521
+ ]
2522
+ prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
2523
+ # Run generation
2524
+ outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
2525
+ print(outputs[0]["generated_text"])
2526
+
2527
+ ```
2528
+
2529
+ **input_shapes**
2530
+
2531
+ ```json
2532
+ {
2533
+ "sequence_length": 384,
2534
+ "batch_size": 1
2535
+ }
2536
+ ```
2537
+
2538
+
2539
+
config.json ADDED
@@ -0,0 +1,53 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "BAAI/bge-base-en-v1.5",
3
+ "architectures": [
4
+ "BertModel"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "classifier_dropout": null,
8
+ "gradient_checkpointing": false,
9
+ "hidden_act": "gelu",
10
+ "hidden_dropout_prob": 0.1,
11
+ "hidden_size": 768,
12
+ "id2label": {
13
+ "0": "LABEL_0"
14
+ },
15
+ "initializer_range": 0.02,
16
+ "intermediate_size": 3072,
17
+ "label2id": {
18
+ "LABEL_0": 0
19
+ },
20
+ "layer_norm_eps": 1e-12,
21
+ "max_position_embeddings": 512,
22
+ "model_type": "bert",
23
+ "neuron": {
24
+ "auto_cast": null,
25
+ "auto_cast_type": null,
26
+ "compiler_type": "neuronx-cc",
27
+ "compiler_version": "2.11.0.34+c5231f848",
28
+ "disable_fallback": false,
29
+ "disable_fast_relayout": false,
30
+ "dynamic_batch_size": false,
31
+ "input_names": [
32
+ "input_ids",
33
+ "attention_mask",
34
+ "token_type_ids"
35
+ ],
36
+ "output_names": [
37
+ "last_hidden_state",
38
+ "pooler_output"
39
+ ],
40
+ "static_batch_size": 1,
41
+ "static_sequence_length": 384
42
+ },
43
+ "num_attention_heads": 12,
44
+ "num_hidden_layers": 12,
45
+ "pad_token_id": 0,
46
+ "position_embedding_type": "absolute",
47
+ "task": null,
48
+ "torch_dtype": "float32",
49
+ "transformers_version": "4.35.0",
50
+ "type_vocab_size": 2,
51
+ "use_cache": true,
52
+ "vocab_size": 30522
53
+ }
model.neuron ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9a8b0cd957cab25a3dc4e69a4f09588e482b2c5eb60a59cef18f718c5d71c72b
3
+ size 273801602
special_tokens_map.json ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "cls_token": {
3
+ "content": "[CLS]",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "mask_token": {
10
+ "content": "[MASK]",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": {
17
+ "content": "[PAD]",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "sep_token": {
24
+ "content": "[SEP]",
25
+ "lstrip": false,
26
+ "normalized": false,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ },
30
+ "unk_token": {
31
+ "content": "[UNK]",
32
+ "lstrip": false,
33
+ "normalized": false,
34
+ "rstrip": false,
35
+ "single_word": false
36
+ }
37
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,57 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "[PAD]",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "100": {
12
+ "content": "[UNK]",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "101": {
20
+ "content": "[CLS]",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "102": {
28
+ "content": "[SEP]",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "103": {
36
+ "content": "[MASK]",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ }
43
+ },
44
+ "clean_up_tokenization_spaces": true,
45
+ "cls_token": "[CLS]",
46
+ "do_basic_tokenize": true,
47
+ "do_lower_case": true,
48
+ "mask_token": "[MASK]",
49
+ "model_max_length": 512,
50
+ "never_split": null,
51
+ "pad_token": "[PAD]",
52
+ "sep_token": "[SEP]",
53
+ "strip_accents": null,
54
+ "tokenize_chinese_chars": true,
55
+ "tokenizer_class": "BertTokenizer",
56
+ "unk_token": "[UNK]"
57
+ }
vocab.txt ADDED
The diff for this file is too large to render. See raw diff