Commit
•
c9971ce
1
Parent(s):
d1d3576
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +2539 -0
- config.json +53 -0
- model.neuron +3 -0
- special_tokens_map.json +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +57 -0
- vocab.txt +0 -0
.gitattributes
CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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+
model.neuron filter=lfs diff=lfs merge=lfs -text
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README.md
ADDED
@@ -0,0 +1,2539 @@
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|
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
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- type: ap
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value: 90.21276917991995
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45 |
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value: 93.37741030006174
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46 |
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|
47 |
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type: Classification
|
48 |
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dataset:
|
49 |
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name: MTEB AmazonReviewsClassification (en)
|
50 |
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type: mteb/amazon_reviews_multi
|
51 |
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config: en
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52 |
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split: test
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53 |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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54 |
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|
55 |
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- type: accuracy
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56 |
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value: 48.846000000000004
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57 |
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58 |
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59 |
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|
60 |
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type: Retrieval
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61 |
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dataset:
|
62 |
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name: MTEB ArguAna
|
63 |
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type: arguana
|
64 |
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config: default
|
65 |
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split: test
|
66 |
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revision: None
|
67 |
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metrics:
|
68 |
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|
69 |
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value: 40.754000000000005
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70 |
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|
71 |
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72 |
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value: 55.708
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value: 40.754000000000005
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value: 8.841000000000001
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value: 0.991
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value: 0.1
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value: 22.238
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114 |
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value: 15.149000000000001
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value: 40.754000000000005
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value: 88.407
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value: 99.14699999999999
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value: 99.644
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value: 66.714
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126 |
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- type: recall_at_5
|
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value: 75.747
|
128 |
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- task:
|
129 |
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type: Clustering
|
130 |
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dataset:
|
131 |
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name: MTEB ArxivClusteringP2P
|
132 |
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type: mteb/arxiv-clustering-p2p
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133 |
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config: default
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134 |
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split: test
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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136 |
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metrics:
|
137 |
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- type: v_measure
|
138 |
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value: 48.74884539679369
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139 |
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- task:
|
140 |
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type: Clustering
|
141 |
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dataset:
|
142 |
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name: MTEB ArxivClusteringS2S
|
143 |
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type: mteb/arxiv-clustering-s2s
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config: default
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145 |
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split: test
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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147 |
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metrics:
|
148 |
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- type: v_measure
|
149 |
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value: 42.8075893810716
|
150 |
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- task:
|
151 |
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type: Reranking
|
152 |
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dataset:
|
153 |
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name: MTEB AskUbuntuDupQuestions
|
154 |
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type: mteb/askubuntudupquestions-reranking
|
155 |
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config: default
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split: test
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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metrics:
|
159 |
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- type: map
|
160 |
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value: 62.128470519187736
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- type: mrr
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162 |
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value: 74.28065778481289
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163 |
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|
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type: STS
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dataset:
|
166 |
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name: MTEB BIOSSES
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config: default
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split: test
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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|
172 |
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173 |
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value: 89.24629081484655
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174 |
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- type: cos_sim_spearman
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value: 86.93752309911496
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- type: euclidean_pearson
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value: 87.58589628573816
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- type: euclidean_spearman
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- type: manhattan_pearson
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value: 87.5594959805773
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- type: manhattan_spearman
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184 |
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|
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type: Classification
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186 |
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dataset:
|
187 |
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name: MTEB Banking77Classification
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type: mteb/banking77
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189 |
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config: default
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190 |
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split: test
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191 |
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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metrics:
|
193 |
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- type: accuracy
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194 |
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value: 86.9512987012987
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195 |
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- type: f1
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196 |
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value: 86.92515357973708
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197 |
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- task:
|
198 |
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type: Clustering
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199 |
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dataset:
|
200 |
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name: MTEB BiorxivClusteringP2P
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201 |
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type: mteb/biorxiv-clustering-p2p
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202 |
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config: default
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203 |
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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205 |
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metrics:
|
206 |
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- type: v_measure
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207 |
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value: 39.10263762928872
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208 |
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- task:
|
209 |
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type: Clustering
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210 |
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dataset:
|
211 |
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name: MTEB BiorxivClusteringS2S
|
212 |
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type: mteb/biorxiv-clustering-s2s
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213 |
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config: default
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214 |
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split: test
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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metrics:
|
217 |
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218 |
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value: 36.69711517426737
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219 |
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- task:
|
220 |
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221 |
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dataset:
|
222 |
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name: MTEB CQADupstackAndroidRetrieval
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223 |
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type: BeIR/cqadupstack
|
224 |
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config: default
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225 |
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split: test
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226 |
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revision: None
|
227 |
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metrics:
|
228 |
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229 |
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value: 32.327
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230 |
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231 |
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value: 45.525
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value: 42.36
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value: 50.29
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value: 50.773
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value: 47.703
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value: 39.199
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value: 9.914000000000001
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value: 1.5310000000000001
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value: 0.198
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value: 21.984
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value: 15.737000000000002
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value: 63.743
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value: 84.538
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882 |
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883 |
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884 |
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885 |
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886 |
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- 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 |
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revision: None
|
1305 |
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metrics:
|
1306 |
+
- type: map_at_1
|
1307 |
+
value: 40.358
|
1308 |
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- type: map_at_10
|
1309 |
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value: 64.497
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1310 |
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1311 |
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value: 65.362
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1312 |
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|
1313 |
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value: 65.41900000000001
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1314 |
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1315 |
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value: 61.06700000000001
|
1316 |
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|
1317 |
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value: 63.317
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1318 |
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|
1319 |
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value: 80.716
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1320 |
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|
1321 |
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value: 86.10799999999999
|
1322 |
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- type: mrr_at_100
|
1323 |
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value: 86.265
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1324 |
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|
1325 |
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value: 86.27
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1326 |
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|
1327 |
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value: 85.271
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1328 |
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|
1329 |
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value: 85.82499999999999
|
1330 |
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- type: ndcg_at_1
|
1331 |
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value: 80.716
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1332 |
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- type: ndcg_at_10
|
1333 |
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value: 72.597
|
1334 |
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- type: ndcg_at_100
|
1335 |
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value: 75.549
|
1336 |
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- type: ndcg_at_1000
|
1337 |
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value: 76.61
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1338 |
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- type: ndcg_at_3
|
1339 |
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value: 67.874
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1340 |
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|
1341 |
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value: 70.655
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1342 |
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- type: precision_at_1
|
1343 |
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value: 80.716
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1344 |
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- type: precision_at_10
|
1345 |
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value: 15.148
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1346 |
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- type: precision_at_100
|
1347 |
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value: 1.745
|
1348 |
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- type: precision_at_1000
|
1349 |
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value: 0.188
|
1350 |
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- type: precision_at_3
|
1351 |
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value: 43.597
|
1352 |
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- type: precision_at_5
|
1353 |
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value: 28.351
|
1354 |
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- type: recall_at_1
|
1355 |
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value: 40.358
|
1356 |
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- type: recall_at_10
|
1357 |
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value: 75.739
|
1358 |
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- type: recall_at_100
|
1359 |
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value: 87.259
|
1360 |
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- type: recall_at_1000
|
1361 |
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value: 94.234
|
1362 |
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- type: recall_at_3
|
1363 |
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value: 65.39500000000001
|
1364 |
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- type: recall_at_5
|
1365 |
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value: 70.878
|
1366 |
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- task:
|
1367 |
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type: Classification
|
1368 |
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dataset:
|
1369 |
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name: MTEB ImdbClassification
|
1370 |
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type: mteb/imdb
|
1371 |
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config: default
|
1372 |
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split: test
|
1373 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1374 |
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metrics:
|
1375 |
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- type: accuracy
|
1376 |
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value: 90.80799999999998
|
1377 |
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- type: ap
|
1378 |
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value: 86.81350378180757
|
1379 |
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- type: f1
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1380 |
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value: 90.79901248314215
|
1381 |
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- task:
|
1382 |
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type: Retrieval
|
1383 |
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dataset:
|
1384 |
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name: MTEB MSMARCO
|
1385 |
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type: msmarco
|
1386 |
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config: default
|
1387 |
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split: dev
|
1388 |
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revision: None
|
1389 |
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metrics:
|
1390 |
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- type: map_at_1
|
1391 |
+
value: 22.096
|
1392 |
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- type: map_at_10
|
1393 |
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value: 34.384
|
1394 |
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- type: map_at_100
|
1395 |
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value: 35.541
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1396 |
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- type: map_at_1000
|
1397 |
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value: 35.589999999999996
|
1398 |
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|
1399 |
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value: 30.496000000000002
|
1400 |
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- type: map_at_5
|
1401 |
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value: 32.718
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1402 |
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- type: mrr_at_1
|
1403 |
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value: 22.750999999999998
|
1404 |
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- type: mrr_at_10
|
1405 |
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value: 35.024
|
1406 |
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- type: mrr_at_100
|
1407 |
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value: 36.125
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1408 |
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- type: mrr_at_1000
|
1409 |
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value: 36.168
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1410 |
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- type: mrr_at_3
|
1411 |
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value: 31.225
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1412 |
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- type: mrr_at_5
|
1413 |
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value: 33.416000000000004
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1414 |
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- type: ndcg_at_1
|
1415 |
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value: 22.750999999999998
|
1416 |
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- type: ndcg_at_10
|
1417 |
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value: 41.351
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1418 |
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- type: ndcg_at_100
|
1419 |
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value: 46.92
|
1420 |
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- type: ndcg_at_1000
|
1421 |
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value: 48.111
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1422 |
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- type: ndcg_at_3
|
1423 |
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value: 33.439
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1424 |
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- type: ndcg_at_5
|
1425 |
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value: 37.407000000000004
|
1426 |
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- type: precision_at_1
|
1427 |
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value: 22.750999999999998
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1428 |
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- type: precision_at_10
|
1429 |
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value: 6.564
|
1430 |
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- type: precision_at_100
|
1431 |
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value: 0.935
|
1432 |
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- type: precision_at_1000
|
1433 |
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value: 0.104
|
1434 |
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- type: precision_at_3
|
1435 |
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value: 14.288
|
1436 |
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- type: precision_at_5
|
1437 |
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value: 10.581999999999999
|
1438 |
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- type: recall_at_1
|
1439 |
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value: 22.096
|
1440 |
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- type: recall_at_10
|
1441 |
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value: 62.771
|
1442 |
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- type: recall_at_100
|
1443 |
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value: 88.529
|
1444 |
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- type: recall_at_1000
|
1445 |
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value: 97.55
|
1446 |
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- type: recall_at_3
|
1447 |
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value: 41.245
|
1448 |
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- type: recall_at_5
|
1449 |
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value: 50.788
|
1450 |
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- task:
|
1451 |
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type: Classification
|
1452 |
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dataset:
|
1453 |
+
name: MTEB MTOPDomainClassification (en)
|
1454 |
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type: mteb/mtop_domain
|
1455 |
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config: en
|
1456 |
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split: test
|
1457 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
1458 |
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metrics:
|
1459 |
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- type: accuracy
|
1460 |
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value: 94.16780665754673
|
1461 |
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- type: f1
|
1462 |
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value: 93.96331194859894
|
1463 |
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- task:
|
1464 |
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type: Classification
|
1465 |
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dataset:
|
1466 |
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name: MTEB MTOPIntentClassification (en)
|
1467 |
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type: mteb/mtop_intent
|
1468 |
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config: en
|
1469 |
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split: test
|
1470 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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1471 |
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metrics:
|
1472 |
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- type: accuracy
|
1473 |
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value: 76.90606475148198
|
1474 |
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- type: f1
|
1475 |
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value: 58.58344986604187
|
1476 |
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- task:
|
1477 |
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type: Classification
|
1478 |
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dataset:
|
1479 |
+
name: MTEB MassiveIntentClassification (en)
|
1480 |
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type: mteb/amazon_massive_intent
|
1481 |
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config: en
|
1482 |
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split: test
|
1483 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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1484 |
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metrics:
|
1485 |
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- type: accuracy
|
1486 |
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value: 76.14660390047075
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1487 |
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- type: f1
|
1488 |
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value: 74.31533923533614
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1489 |
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- task:
|
1490 |
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type: Classification
|
1491 |
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dataset:
|
1492 |
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name: MTEB MassiveScenarioClassification (en)
|
1493 |
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type: mteb/amazon_massive_scenario
|
1494 |
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config: en
|
1495 |
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split: test
|
1496 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
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1497 |
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metrics:
|
1498 |
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- type: accuracy
|
1499 |
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value: 80.16139878950908
|
1500 |
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- type: f1
|
1501 |
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value: 80.18532656824924
|
1502 |
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- task:
|
1503 |
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type: Clustering
|
1504 |
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dataset:
|
1505 |
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name: MTEB MedrxivClusteringP2P
|
1506 |
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type: mteb/medrxiv-clustering-p2p
|
1507 |
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config: default
|
1508 |
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split: test
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1509 |
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revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
1510 |
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metrics:
|
1511 |
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- type: v_measure
|
1512 |
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value: 32.949880906135085
|
1513 |
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- task:
|
1514 |
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type: Clustering
|
1515 |
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dataset:
|
1516 |
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name: MTEB MedrxivClusteringS2S
|
1517 |
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type: mteb/medrxiv-clustering-s2s
|
1518 |
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config: default
|
1519 |
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split: test
|
1520 |
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revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
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1521 |
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metrics:
|
1522 |
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- type: v_measure
|
1523 |
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value: 31.56300351524862
|
1524 |
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- task:
|
1525 |
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type: Reranking
|
1526 |
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dataset:
|
1527 |
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name: MTEB MindSmallReranking
|
1528 |
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type: mteb/mind_small
|
1529 |
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config: default
|
1530 |
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split: test
|
1531 |
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revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
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1532 |
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metrics:
|
1533 |
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- type: map
|
1534 |
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value: 31.196521894371315
|
1535 |
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- type: mrr
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1536 |
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value: 32.22644231694389
|
1537 |
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- task:
|
1538 |
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type: Retrieval
|
1539 |
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dataset:
|
1540 |
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name: MTEB NFCorpus
|
1541 |
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type: nfcorpus
|
1542 |
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config: default
|
1543 |
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split: test
|
1544 |
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revision: None
|
1545 |
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metrics:
|
1546 |
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- type: map_at_1
|
1547 |
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value: 6.783
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1548 |
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- type: map_at_10
|
1549 |
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value: 14.549000000000001
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1550 |
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- type: map_at_100
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1551 |
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value: 18.433
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1552 |
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- type: map_at_1000
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1553 |
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value: 19.949
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1554 |
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- type: map_at_3
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1555 |
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value: 10.936
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1556 |
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1557 |
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value: 12.514
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1558 |
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1559 |
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value: 47.368
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1560 |
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1561 |
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value: 56.42
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1562 |
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1563 |
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value: 56.908
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1564 |
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1565 |
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value: 56.95
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1566 |
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1567 |
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value: 54.283
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1568 |
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1569 |
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value: 55.568
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1570 |
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1571 |
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value: 45.666000000000004
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1572 |
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1573 |
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value: 37.389
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1574 |
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1575 |
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value: 34.253
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1576 |
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1577 |
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value: 43.059999999999995
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1578 |
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- type: ndcg_at_3
|
1579 |
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value: 42.725
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1580 |
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- type: ndcg_at_5
|
1581 |
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value: 40.193
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1582 |
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- type: precision_at_1
|
1583 |
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value: 47.368
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1584 |
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- type: precision_at_10
|
1585 |
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value: 27.988000000000003
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1586 |
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- type: precision_at_100
|
1587 |
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value: 8.672
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1588 |
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- type: precision_at_1000
|
1589 |
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value: 2.164
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1590 |
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- type: precision_at_3
|
1591 |
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value: 40.248
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1592 |
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- type: precision_at_5
|
1593 |
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value: 34.737
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1594 |
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- type: recall_at_1
|
1595 |
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value: 6.783
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1596 |
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- type: recall_at_10
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1597 |
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value: 17.838
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1598 |
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- type: recall_at_100
|
1599 |
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value: 33.672000000000004
|
1600 |
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- type: recall_at_1000
|
1601 |
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value: 66.166
|
1602 |
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- type: recall_at_3
|
1603 |
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value: 11.849
|
1604 |
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- type: recall_at_5
|
1605 |
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value: 14.205000000000002
|
1606 |
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- task:
|
1607 |
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type: Retrieval
|
1608 |
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dataset:
|
1609 |
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name: MTEB NQ
|
1610 |
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type: nq
|
1611 |
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config: default
|
1612 |
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split: test
|
1613 |
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revision: None
|
1614 |
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metrics:
|
1615 |
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- type: map_at_1
|
1616 |
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value: 31.698999999999998
|
1617 |
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- type: map_at_10
|
1618 |
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value: 46.556
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1619 |
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- type: map_at_100
|
1620 |
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value: 47.652
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1621 |
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1622 |
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value: 47.68
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1623 |
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1624 |
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value: 42.492000000000004
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1625 |
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|
1626 |
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value: 44.763999999999996
|
1627 |
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1628 |
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value: 35.747
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1629 |
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|
1630 |
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value: 49.242999999999995
|
1631 |
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- type: mrr_at_100
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1632 |
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value: 50.052
|
1633 |
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- type: mrr_at_1000
|
1634 |
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value: 50.068
|
1635 |
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- type: mrr_at_3
|
1636 |
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value: 45.867000000000004
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1637 |
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- type: mrr_at_5
|
1638 |
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value: 47.778999999999996
|
1639 |
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- type: ndcg_at_1
|
1640 |
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value: 35.717999999999996
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1641 |
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- type: ndcg_at_10
|
1642 |
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value: 54.14600000000001
|
1643 |
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- type: ndcg_at_100
|
1644 |
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value: 58.672999999999995
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1645 |
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- type: ndcg_at_1000
|
1646 |
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value: 59.279
|
1647 |
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- type: ndcg_at_3
|
1648 |
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value: 46.407
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1649 |
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|
1650 |
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value: 50.181
|
1651 |
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|
1652 |
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value: 35.717999999999996
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1653 |
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- type: precision_at_10
|
1654 |
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value: 8.844000000000001
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1655 |
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- type: precision_at_100
|
1656 |
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value: 1.139
|
1657 |
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- type: precision_at_1000
|
1658 |
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value: 0.12
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1659 |
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- type: precision_at_3
|
1660 |
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value: 20.993000000000002
|
1661 |
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- type: precision_at_5
|
1662 |
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value: 14.791000000000002
|
1663 |
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- type: recall_at_1
|
1664 |
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value: 31.698999999999998
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1665 |
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- type: recall_at_10
|
1666 |
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value: 74.693
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1667 |
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- type: recall_at_100
|
1668 |
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value: 94.15299999999999
|
1669 |
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- type: recall_at_1000
|
1670 |
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value: 98.585
|
1671 |
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- type: recall_at_3
|
1672 |
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value: 54.388999999999996
|
1673 |
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- type: recall_at_5
|
1674 |
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value: 63.08200000000001
|
1675 |
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- task:
|
1676 |
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type: Retrieval
|
1677 |
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dataset:
|
1678 |
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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 |
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- type: map_at_10
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1687 |
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value: 85.24000000000001
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1688 |
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1689 |
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value: 85.882
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1690 |
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1691 |
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value: 85.897
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1692 |
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1693 |
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value: 82.326
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1694 |
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1695 |
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value: 84.177
|
1696 |
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- type: mrr_at_1
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1697 |
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value: 82.21000000000001
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1698 |
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- type: mrr_at_10
|
1699 |
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value: 88.228
|
1700 |
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- type: mrr_at_100
|
1701 |
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value: 88.32
|
1702 |
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- type: mrr_at_1000
|
1703 |
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value: 88.32
|
1704 |
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- type: mrr_at_3
|
1705 |
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value: 87.323
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1706 |
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- type: mrr_at_5
|
1707 |
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value: 87.94800000000001
|
1708 |
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- type: ndcg_at_1
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1709 |
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value: 82.17999999999999
|
1710 |
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- type: ndcg_at_10
|
1711 |
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value: 88.9
|
1712 |
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- type: ndcg_at_100
|
1713 |
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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 @@
|
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|
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 @@
|
|
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|
|
|
|
|
|
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 @@
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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
|
|