Muennighoff
commited on
Commit
•
2f6b75f
1
Parent(s):
bd44305
Add MTEB metadata
Browse files
README.md
CHANGED
@@ -4,6 +4,7 @@ tags:
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4 |
- sentence-transformers
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- feature-extraction
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- sentence-similarity
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language: en
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8 |
license: apache-2.0
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9 |
datasets:
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@@ -28,7 +29,2209 @@ datasets:
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- embedding-data/SPECTER
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- embedding-data/PAQ_pairs
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- embedding-data/WikiAnswers
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|
32 |
---
|
33 |
|
34 |
|
|
|
4 |
- sentence-transformers
|
5 |
- feature-extraction
|
6 |
- sentence-similarity
|
7 |
+
- mteb
|
8 |
language: en
|
9 |
license: apache-2.0
|
10 |
datasets:
|
|
|
29 |
- embedding-data/SPECTER
|
30 |
- embedding-data/PAQ_pairs
|
31 |
- embedding-data/WikiAnswers
|
32 |
+
model-index:
|
33 |
+
- name: all-mpnet-base-v2
|
34 |
+
results:
|
35 |
+
- task:
|
36 |
+
type: Classification
|
37 |
+
dataset:
|
38 |
+
type: mteb/amazon_counterfactual
|
39 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
40 |
+
config: en
|
41 |
+
split: test
|
42 |
+
metrics:
|
43 |
+
- type: accuracy
|
44 |
+
value: 65.26865671641791
|
45 |
+
- type: ap
|
46 |
+
value: 28.47453420428918
|
47 |
+
- type: f1
|
48 |
+
value: 59.3470101009448
|
49 |
+
- task:
|
50 |
+
type: Classification
|
51 |
+
dataset:
|
52 |
+
type: mteb/amazon_polarity
|
53 |
+
name: MTEB AmazonPolarityClassification
|
54 |
+
config: default
|
55 |
+
split: test
|
56 |
+
metrics:
|
57 |
+
- type: accuracy
|
58 |
+
value: 67.13145
|
59 |
+
- type: ap
|
60 |
+
value: 61.842060778903786
|
61 |
+
- type: f1
|
62 |
+
value: 66.79987305640383
|
63 |
+
- task:
|
64 |
+
type: Classification
|
65 |
+
dataset:
|
66 |
+
type: mteb/amazon_reviews_multi
|
67 |
+
name: MTEB AmazonReviewsClassification (en)
|
68 |
+
config: en
|
69 |
+
split: test
|
70 |
+
metrics:
|
71 |
+
- type: accuracy
|
72 |
+
value: 31.920000000000005
|
73 |
+
- type: f1
|
74 |
+
value: 31.2465193896153
|
75 |
+
- task:
|
76 |
+
type: Retrieval
|
77 |
+
dataset:
|
78 |
+
type: arguana
|
79 |
+
name: MTEB ArguAna
|
80 |
+
config: default
|
81 |
+
split: test
|
82 |
+
metrics:
|
83 |
+
- type: map_at_1
|
84 |
+
value: 23.186
|
85 |
+
- type: map_at_10
|
86 |
+
value: 37.692
|
87 |
+
- type: map_at_100
|
88 |
+
value: 38.986
|
89 |
+
- type: map_at_1000
|
90 |
+
value: 38.991
|
91 |
+
- type: map_at_3
|
92 |
+
value: 32.622
|
93 |
+
- type: map_at_5
|
94 |
+
value: 35.004999999999995
|
95 |
+
- type: ndcg_at_1
|
96 |
+
value: 23.186
|
97 |
+
- type: ndcg_at_10
|
98 |
+
value: 46.521
|
99 |
+
- type: ndcg_at_100
|
100 |
+
value: 51.954
|
101 |
+
- type: ndcg_at_1000
|
102 |
+
value: 52.087
|
103 |
+
- type: ndcg_at_3
|
104 |
+
value: 35.849
|
105 |
+
- type: ndcg_at_5
|
106 |
+
value: 40.12
|
107 |
+
- type: precision_at_1
|
108 |
+
value: 23.186
|
109 |
+
- type: precision_at_10
|
110 |
+
value: 7.510999999999999
|
111 |
+
- type: precision_at_100
|
112 |
+
value: 0.9860000000000001
|
113 |
+
- type: precision_at_1000
|
114 |
+
value: 0.1
|
115 |
+
- type: precision_at_3
|
116 |
+
value: 15.078
|
117 |
+
- type: precision_at_5
|
118 |
+
value: 11.110000000000001
|
119 |
+
- type: recall_at_1
|
120 |
+
value: 23.186
|
121 |
+
- type: recall_at_10
|
122 |
+
value: 75.107
|
123 |
+
- type: recall_at_100
|
124 |
+
value: 98.649
|
125 |
+
- type: recall_at_1000
|
126 |
+
value: 99.644
|
127 |
+
- type: recall_at_3
|
128 |
+
value: 45.235
|
129 |
+
- type: recall_at_5
|
130 |
+
value: 55.547999999999995
|
131 |
+
- task:
|
132 |
+
type: Clustering
|
133 |
+
dataset:
|
134 |
+
type: mteb/arxiv-clustering-p2p
|
135 |
+
name: MTEB ArxivClusteringP2P
|
136 |
+
config: default
|
137 |
+
split: test
|
138 |
+
metrics:
|
139 |
+
- type: v_measure
|
140 |
+
value: 48.37886340922374
|
141 |
+
- task:
|
142 |
+
type: Clustering
|
143 |
+
dataset:
|
144 |
+
type: mteb/arxiv-clustering-s2s
|
145 |
+
name: MTEB ArxivClusteringS2S
|
146 |
+
config: default
|
147 |
+
split: test
|
148 |
+
metrics:
|
149 |
+
- type: v_measure
|
150 |
+
value: 39.72488615315985
|
151 |
+
- task:
|
152 |
+
type: Reranking
|
153 |
+
dataset:
|
154 |
+
type: mteb/askubuntudupquestions-reranking
|
155 |
+
name: MTEB AskUbuntuDupQuestions
|
156 |
+
config: default
|
157 |
+
split: test
|
158 |
+
metrics:
|
159 |
+
- type: map
|
160 |
+
value: 65.85199009344481
|
161 |
+
- type: mrr
|
162 |
+
value: 78.47700391329201
|
163 |
+
- task:
|
164 |
+
type: STS
|
165 |
+
dataset:
|
166 |
+
type: mteb/biosses-sts
|
167 |
+
name: MTEB BIOSSES
|
168 |
+
config: default
|
169 |
+
split: test
|
170 |
+
metrics:
|
171 |
+
- type: cos_sim_pearson
|
172 |
+
value: 84.47737119217858
|
173 |
+
- type: cos_sim_spearman
|
174 |
+
value: 80.43195317854409
|
175 |
+
- type: euclidean_pearson
|
176 |
+
value: 82.20496332547978
|
177 |
+
- type: euclidean_spearman
|
178 |
+
value: 80.43195317854409
|
179 |
+
- type: manhattan_pearson
|
180 |
+
value: 81.4836610720397
|
181 |
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- type: manhattan_spearman
|
182 |
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value: 79.65904400101908
|
183 |
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- task:
|
184 |
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type: Classification
|
185 |
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dataset:
|
186 |
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type: mteb/banking77
|
187 |
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name: MTEB Banking77Classification
|
188 |
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config: default
|
189 |
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split: test
|
190 |
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metrics:
|
191 |
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- type: accuracy
|
192 |
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value: 81.8603896103896
|
193 |
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- type: f1
|
194 |
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value: 81.28027245637479
|
195 |
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- task:
|
196 |
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type: Clustering
|
197 |
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dataset:
|
198 |
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type: mteb/biorxiv-clustering-p2p
|
199 |
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name: MTEB BiorxivClusteringP2P
|
200 |
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config: default
|
201 |
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split: test
|
202 |
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metrics:
|
203 |
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- type: v_measure
|
204 |
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value: 39.616605133625185
|
205 |
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- task:
|
206 |
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type: Clustering
|
207 |
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dataset:
|
208 |
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type: mteb/biorxiv-clustering-s2s
|
209 |
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name: MTEB BiorxivClusteringS2S
|
210 |
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config: default
|
211 |
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split: test
|
212 |
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metrics:
|
213 |
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- type: v_measure
|
214 |
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value: 35.02442407186902
|
215 |
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- task:
|
216 |
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type: Retrieval
|
217 |
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dataset:
|
218 |
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type: BeIR/cqadupstack
|
219 |
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name: MTEB CQADupstackAndroidRetrieval
|
220 |
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config: default
|
221 |
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split: test
|
222 |
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metrics:
|
223 |
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- type: map_at_1
|
224 |
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value: 36.036
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225 |
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|
226 |
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value: 49.302
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227 |
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|
228 |
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value: 50.956
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229 |
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230 |
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value: 51.080000000000005
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231 |
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232 |
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|
233 |
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234 |
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value: 47.353
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235 |
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|
236 |
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237 |
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|
238 |
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value: 56.485
|
239 |
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|
240 |
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value: 61.413
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241 |
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242 |
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243 |
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244 |
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245 |
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246 |
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247 |
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248 |
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value: 45.207
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249 |
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|
250 |
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value: 11.144
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251 |
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|
252 |
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value: 1.735
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253 |
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254 |
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value: 0.22100000000000003
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255 |
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|
256 |
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value: 24.94
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257 |
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- type: precision_at_5
|
258 |
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value: 17.997
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259 |
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- type: recall_at_1
|
260 |
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value: 36.036
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261 |
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|
262 |
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value: 69.191
|
263 |
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|
264 |
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value: 89.423
|
265 |
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- type: recall_at_1000
|
266 |
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value: 98.425
|
267 |
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- type: recall_at_3
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268 |
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value: 53.849999999999994
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269 |
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- type: recall_at_5
|
270 |
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value: 60.107
|
271 |
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- task:
|
272 |
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type: Retrieval
|
273 |
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dataset:
|
274 |
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type: BeIR/cqadupstack
|
275 |
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name: MTEB CQADupstackEnglishRetrieval
|
276 |
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config: default
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277 |
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split: test
|
278 |
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metrics:
|
279 |
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|
280 |
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value: 32.92
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281 |
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|
282 |
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value: 45.739999999999995
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283 |
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284 |
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285 |
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286 |
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value: 47.443000000000005
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287 |
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288 |
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289 |
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290 |
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291 |
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292 |
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value: 42.229
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293 |
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|
294 |
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value: 52.288999999999994
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295 |
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296 |
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297 |
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298 |
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value: 58.788
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299 |
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|
300 |
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value: 47.531
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301 |
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302 |
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value: 49.861
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303 |
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304 |
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value: 42.229
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305 |
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|
306 |
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value: 10.299
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307 |
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308 |
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value: 1.68
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309 |
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- type: precision_at_1000
|
310 |
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value: 0.213
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311 |
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|
312 |
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value: 23.673
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313 |
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- type: precision_at_5
|
314 |
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value: 17.006
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315 |
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- type: recall_at_1
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316 |
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value: 32.92
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317 |
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- type: recall_at_10
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318 |
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value: 63.865
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319 |
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- type: recall_at_100
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320 |
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value: 84.06700000000001
|
321 |
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- type: recall_at_1000
|
322 |
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value: 94.536
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323 |
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- type: recall_at_3
|
324 |
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value: 49.643
|
325 |
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- type: recall_at_5
|
326 |
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value: 56.119
|
327 |
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- task:
|
328 |
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type: Retrieval
|
329 |
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dataset:
|
330 |
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type: BeIR/cqadupstack
|
331 |
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name: MTEB CQADupstackGamingRetrieval
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332 |
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config: default
|
333 |
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split: test
|
334 |
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metrics:
|
335 |
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- type: map_at_1
|
336 |
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value: 40.695
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337 |
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|
338 |
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value: 53.787
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339 |
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|
340 |
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value: 54.778000000000006
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341 |
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- type: map_at_1000
|
342 |
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value: 54.827000000000005
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343 |
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- type: map_at_3
|
344 |
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value: 50.151999999999994
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345 |
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|
346 |
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value: 52.207
|
347 |
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- type: ndcg_at_1
|
348 |
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value: 46.52
|
349 |
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- type: ndcg_at_10
|
350 |
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value: 60.026
|
351 |
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- type: ndcg_at_100
|
352 |
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value: 63.81099999999999
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353 |
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- type: ndcg_at_1000
|
354 |
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value: 64.741
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355 |
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|
356 |
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value: 53.83
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357 |
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|
358 |
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value: 56.928999999999995
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359 |
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- type: precision_at_1
|
360 |
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value: 46.52
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361 |
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|
362 |
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value: 9.754999999999999
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363 |
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- type: precision_at_100
|
364 |
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value: 1.2670000000000001
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365 |
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|
366 |
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value: 0.13799999999999998
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367 |
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|
368 |
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value: 24.096
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369 |
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- type: precision_at_5
|
370 |
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value: 16.689999999999998
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371 |
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- type: recall_at_1
|
372 |
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value: 40.695
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373 |
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- type: recall_at_10
|
374 |
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value: 75.181
|
375 |
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- type: recall_at_100
|
376 |
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value: 91.479
|
377 |
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- type: recall_at_1000
|
378 |
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value: 98.06899999999999
|
379 |
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- type: recall_at_3
|
380 |
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value: 58.707
|
381 |
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- type: recall_at_5
|
382 |
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value: 66.295
|
383 |
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- task:
|
384 |
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type: Retrieval
|
385 |
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dataset:
|
386 |
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type: BeIR/cqadupstack
|
387 |
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name: MTEB CQADupstackGisRetrieval
|
388 |
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config: default
|
389 |
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split: test
|
390 |
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metrics:
|
391 |
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- type: map_at_1
|
392 |
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value: 29.024
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393 |
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|
394 |
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value: 38.438
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395 |
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396 |
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value: 39.576
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397 |
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- type: map_at_1000
|
398 |
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value: 39.645
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399 |
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|
400 |
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value: 34.827999999999996
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401 |
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|
402 |
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value: 36.947
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403 |
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|
404 |
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value: 31.299
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405 |
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|
406 |
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value: 44.268
|
407 |
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|
408 |
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value: 49.507
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409 |
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|
410 |
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value: 51.205999999999996
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411 |
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|
412 |
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value: 37.248999999999995
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413 |
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|
414 |
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value: 40.861999999999995
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415 |
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|
416 |
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value: 31.299
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417 |
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|
418 |
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value: 6.949
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419 |
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|
420 |
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value: 1.012
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421 |
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|
422 |
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value: 0.11900000000000001
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423 |
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- type: precision_at_3
|
424 |
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value: 15.518
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425 |
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- type: precision_at_5
|
426 |
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value: 11.366999999999999
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427 |
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- type: recall_at_1
|
428 |
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value: 29.024
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429 |
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- type: recall_at_10
|
430 |
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value: 60.404
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431 |
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- type: recall_at_100
|
432 |
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value: 83.729
|
433 |
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- type: recall_at_1000
|
434 |
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value: 96.439
|
435 |
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- type: recall_at_3
|
436 |
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value: 41.65
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437 |
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- type: recall_at_5
|
438 |
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value: 50.263999999999996
|
439 |
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- task:
|
440 |
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type: Retrieval
|
441 |
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dataset:
|
442 |
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type: BeIR/cqadupstack
|
443 |
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name: MTEB CQADupstackMathematicaRetrieval
|
444 |
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config: default
|
445 |
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split: test
|
446 |
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metrics:
|
447 |
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|
448 |
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value: 17.774
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449 |
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|
450 |
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451 |
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452 |
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value: 29.603
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453 |
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454 |
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value: 29.709999999999997
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455 |
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|
456 |
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value: 25.036
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457 |
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|
458 |
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value: 26.657999999999998
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459 |
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|
460 |
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value: 22.139
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461 |
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|
462 |
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value: 34.205999999999996
|
463 |
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|
464 |
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value: 40.844
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465 |
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|
466 |
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value: 43.144
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467 |
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|
468 |
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value: 28.732999999999997
|
469 |
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|
470 |
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value: 31.252000000000002
|
471 |
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|
472 |
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value: 22.139
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473 |
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|
474 |
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value: 6.567
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475 |
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|
476 |
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value: 1.147
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477 |
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|
478 |
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value: 0.146
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479 |
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|
480 |
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value: 14.386
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481 |
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|
482 |
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value: 10.423
|
483 |
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- type: recall_at_1
|
484 |
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value: 17.774
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485 |
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- type: recall_at_10
|
486 |
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value: 48.32
|
487 |
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- type: recall_at_100
|
488 |
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value: 76.373
|
489 |
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- type: recall_at_1000
|
490 |
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value: 92.559
|
491 |
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- type: recall_at_3
|
492 |
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value: 33.478
|
493 |
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- type: recall_at_5
|
494 |
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value: 39.872
|
495 |
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- task:
|
496 |
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type: Retrieval
|
497 |
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dataset:
|
498 |
+
type: BeIR/cqadupstack
|
499 |
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name: MTEB CQADupstackPhysicsRetrieval
|
500 |
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config: default
|
501 |
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split: test
|
502 |
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metrics:
|
503 |
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- type: map_at_1
|
504 |
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value: 31.885
|
505 |
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|
506 |
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value: 44.289
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507 |
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|
508 |
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value: 45.757999999999996
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509 |
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|
510 |
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value: 45.86
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511 |
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|
512 |
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value: 40.459
|
513 |
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- type: map_at_5
|
514 |
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value: 42.662
|
515 |
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|
516 |
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value: 39.75
|
517 |
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- type: ndcg_at_10
|
518 |
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value: 50.975
|
519 |
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|
520 |
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value: 56.528999999999996
|
521 |
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|
522 |
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value: 58.06099999999999
|
523 |
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|
524 |
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value: 45.327
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525 |
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|
526 |
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value: 48.041
|
527 |
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- type: precision_at_1
|
528 |
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value: 39.75
|
529 |
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|
530 |
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value: 9.557
|
531 |
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|
532 |
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value: 1.469
|
533 |
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|
534 |
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value: 0.17700000000000002
|
535 |
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|
536 |
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value: 22.073
|
537 |
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- type: precision_at_5
|
538 |
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value: 15.765
|
539 |
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- type: recall_at_1
|
540 |
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value: 31.885
|
541 |
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- type: recall_at_10
|
542 |
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value: 64.649
|
543 |
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- type: recall_at_100
|
544 |
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value: 87.702
|
545 |
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- type: recall_at_1000
|
546 |
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value: 97.327
|
547 |
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- type: recall_at_3
|
548 |
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value: 48.61
|
549 |
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- type: recall_at_5
|
550 |
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value: 55.882
|
551 |
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- task:
|
552 |
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type: Retrieval
|
553 |
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dataset:
|
554 |
+
type: BeIR/cqadupstack
|
555 |
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name: MTEB CQADupstackProgrammersRetrieval
|
556 |
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config: default
|
557 |
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split: test
|
558 |
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metrics:
|
559 |
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|
560 |
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value: 26.454
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561 |
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|
562 |
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563 |
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|
564 |
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value: 39.225
|
565 |
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|
566 |
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value: 39.332
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567 |
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|
568 |
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value: 34.115
|
569 |
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|
570 |
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value: 35.942
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571 |
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|
572 |
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value: 32.42
|
573 |
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|
574 |
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value: 44.165
|
575 |
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- type: ndcg_at_100
|
576 |
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value: 50.202000000000005
|
577 |
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- type: ndcg_at_1000
|
578 |
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value: 52.188
|
579 |
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- type: ndcg_at_3
|
580 |
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value: 38.381
|
581 |
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- type: ndcg_at_5
|
582 |
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value: 40.849000000000004
|
583 |
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- type: precision_at_1
|
584 |
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value: 32.42
|
585 |
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|
586 |
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value: 8.482000000000001
|
587 |
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- type: precision_at_100
|
588 |
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value: 1.332
|
589 |
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- type: precision_at_1000
|
590 |
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value: 0.169
|
591 |
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|
592 |
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value: 18.683
|
593 |
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- type: precision_at_5
|
594 |
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value: 13.539000000000001
|
595 |
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- type: recall_at_1
|
596 |
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value: 26.454
|
597 |
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- type: recall_at_10
|
598 |
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value: 57.937000000000005
|
599 |
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- type: recall_at_100
|
600 |
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value: 83.76
|
601 |
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- type: recall_at_1000
|
602 |
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value: 96.82600000000001
|
603 |
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- type: recall_at_3
|
604 |
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value: 41.842
|
605 |
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- type: recall_at_5
|
606 |
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value: 48.285
|
607 |
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- task:
|
608 |
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type: Retrieval
|
609 |
+
dataset:
|
610 |
+
type: BeIR/cqadupstack
|
611 |
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name: MTEB CQADupstackRetrieval
|
612 |
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config: default
|
613 |
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split: test
|
614 |
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metrics:
|
615 |
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- type: map_at_1
|
616 |
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623 |
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624 |
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625 |
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629 |
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631 |
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632 |
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633 |
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634 |
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635 |
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637 |
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647 |
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648 |
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649 |
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650 |
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651 |
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653 |
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|
654 |
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655 |
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656 |
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657 |
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658 |
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659 |
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|
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- type: recall_at_5
|
662 |
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value: 49.553333333333335
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|
664 |
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type: Retrieval
|
665 |
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dataset:
|
666 |
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type: BeIR/cqadupstack
|
667 |
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name: MTEB CQADupstackStatsRetrieval
|
668 |
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config: default
|
669 |
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split: test
|
670 |
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metrics:
|
671 |
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|
672 |
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value: 25.244
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673 |
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|
674 |
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675 |
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677 |
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679 |
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680 |
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681 |
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682 |
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683 |
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684 |
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685 |
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|
686 |
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value: 38.149
|
687 |
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|
688 |
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value: 43.856
|
689 |
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690 |
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value: 46.026
|
691 |
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692 |
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value: 33.318
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693 |
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|
694 |
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695 |
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697 |
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|
698 |
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699 |
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|
700 |
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701 |
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|
702 |
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703 |
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|
704 |
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value: 14.673
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705 |
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|
706 |
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value: 10.245
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707 |
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|
708 |
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value: 25.244
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709 |
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|
710 |
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711 |
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712 |
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value: 75.928
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713 |
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- type: recall_at_1000
|
714 |
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value: 91.79899999999999
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715 |
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- type: recall_at_3
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716 |
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value: 36.325
|
717 |
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- type: recall_at_5
|
718 |
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value: 41.752
|
719 |
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- task:
|
720 |
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type: Retrieval
|
721 |
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dataset:
|
722 |
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type: BeIR/cqadupstack
|
723 |
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name: MTEB CQADupstackTexRetrieval
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724 |
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config: default
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725 |
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split: test
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726 |
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metrics:
|
727 |
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728 |
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value: 18.857
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729 |
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- type: map_at_10
|
730 |
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731 |
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732 |
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value: 29.186
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733 |
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734 |
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value: 29.323
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735 |
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|
736 |
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value: 24.779
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737 |
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|
738 |
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value: 26.459
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739 |
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740 |
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value: 23.227999999999998
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741 |
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|
742 |
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value: 33.353
|
743 |
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744 |
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value: 39.598
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745 |
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- type: ndcg_at_1000
|
746 |
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value: 42.268
|
747 |
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|
748 |
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value: 28.054000000000002
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749 |
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750 |
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value: 30.566
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751 |
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752 |
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753 |
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754 |
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value: 6.397
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755 |
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756 |
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value: 1.129
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757 |
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- type: precision_at_1000
|
758 |
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value: 0.155
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759 |
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|
760 |
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value: 13.616
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761 |
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- type: precision_at_5
|
762 |
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value: 10.116999999999999
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763 |
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- type: recall_at_1
|
764 |
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value: 18.857
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765 |
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- type: recall_at_10
|
766 |
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value: 45.797
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767 |
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- type: recall_at_100
|
768 |
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value: 73.615
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769 |
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- type: recall_at_1000
|
770 |
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value: 91.959
|
771 |
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- type: recall_at_3
|
772 |
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value: 31.129
|
773 |
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- type: recall_at_5
|
774 |
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value: 37.565
|
775 |
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- task:
|
776 |
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type: Retrieval
|
777 |
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dataset:
|
778 |
+
type: BeIR/cqadupstack
|
779 |
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name: MTEB CQADupstackUnixRetrieval
|
780 |
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config: default
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781 |
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split: test
|
782 |
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metrics:
|
783 |
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- type: map_at_1
|
784 |
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value: 27.486
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785 |
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|
786 |
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value: 39.164
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787 |
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788 |
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value: 40.543
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789 |
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- type: map_at_1000
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790 |
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value: 40.636
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791 |
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- type: map_at_3
|
792 |
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value: 35.52
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793 |
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- type: map_at_5
|
794 |
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value: 37.355
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795 |
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|
796 |
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797 |
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|
798 |
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value: 45.414
|
799 |
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- type: ndcg_at_100
|
800 |
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value: 51.254
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801 |
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- type: ndcg_at_1000
|
802 |
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value: 53.044000000000004
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803 |
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804 |
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value: 39.324999999999996
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805 |
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806 |
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value: 41.835
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807 |
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|
808 |
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value: 32.275999999999996
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809 |
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- type: precision_at_10
|
810 |
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value: 8.144
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811 |
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812 |
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value: 1.237
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813 |
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|
814 |
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value: 0.15
|
815 |
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|
816 |
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value: 18.501
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817 |
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|
818 |
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value: 13.134
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819 |
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|
820 |
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value: 27.486
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821 |
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|
822 |
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value: 60.449
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823 |
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|
824 |
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value: 85.176
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825 |
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- type: recall_at_1000
|
826 |
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value: 97.087
|
827 |
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- type: recall_at_3
|
828 |
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value: 43.59
|
829 |
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- type: recall_at_5
|
830 |
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value: 50.08899999999999
|
831 |
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- task:
|
832 |
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type: Retrieval
|
833 |
+
dataset:
|
834 |
+
type: BeIR/cqadupstack
|
835 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
836 |
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config: default
|
837 |
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split: test
|
838 |
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metrics:
|
839 |
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|
840 |
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value: 26.207
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841 |
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|
842 |
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843 |
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844 |
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value: 39.043
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845 |
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|
846 |
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value: 39.273
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847 |
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|
848 |
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value: 33.487
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849 |
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|
850 |
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851 |
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852 |
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value: 31.423000000000002
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853 |
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854 |
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855 |
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|
856 |
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value: 50.49
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857 |
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858 |
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value: 52.283
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859 |
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860 |
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value: 37.602000000000004
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861 |
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862 |
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863 |
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|
864 |
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value: 31.423000000000002
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865 |
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|
866 |
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867 |
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|
868 |
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value: 1.7590000000000001
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869 |
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870 |
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871 |
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872 |
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value: 17.523
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873 |
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|
874 |
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value: 13.161999999999999
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875 |
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876 |
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value: 26.207
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877 |
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|
878 |
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value: 59.17099999999999
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879 |
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880 |
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value: 86.166
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881 |
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|
882 |
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value: 96.54700000000001
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883 |
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|
884 |
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value: 41.18
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885 |
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|
886 |
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value: 48.083999999999996
|
887 |
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|
888 |
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type: Retrieval
|
889 |
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dataset:
|
890 |
+
type: BeIR/cqadupstack
|
891 |
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name: MTEB CQADupstackWordpressRetrieval
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892 |
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config: default
|
893 |
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split: test
|
894 |
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metrics:
|
895 |
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|
896 |
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value: 20.342
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897 |
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898 |
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899 |
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900 |
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901 |
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902 |
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903 |
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904 |
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905 |
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906 |
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907 |
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908 |
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value: 22.551
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909 |
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910 |
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value: 35.945
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911 |
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|
912 |
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value: 41.012
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913 |
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|
914 |
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value: 43.641999999999996
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915 |
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|
916 |
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value: 29.45
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917 |
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|
918 |
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919 |
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920 |
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921 |
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|
922 |
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value: 6.1
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923 |
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|
924 |
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value: 0.943
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925 |
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|
926 |
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value: 0.129
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927 |
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|
928 |
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value: 13.184999999999999
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929 |
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|
930 |
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value: 9.353
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931 |
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|
932 |
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value: 20.342
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933 |
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|
934 |
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value: 52.349000000000004
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935 |
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|
936 |
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value: 75.728
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937 |
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|
938 |
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value: 95.253
|
939 |
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|
940 |
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value: 34.427
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941 |
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|
942 |
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value: 40.326
|
943 |
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|
944 |
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type: Retrieval
|
945 |
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dataset:
|
946 |
+
type: climate-fever
|
947 |
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name: MTEB ClimateFEVER
|
948 |
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|
949 |
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|
950 |
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metrics:
|
951 |
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|
952 |
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value: 7.71
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953 |
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|
954 |
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955 |
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|
956 |
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957 |
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|
958 |
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959 |
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|
960 |
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961 |
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|
962 |
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963 |
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|
964 |
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value: 18.046
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965 |
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|
966 |
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value: 21.971
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967 |
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|
968 |
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value: 29.468
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969 |
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|
970 |
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value: 33.428999999999995
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971 |
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|
972 |
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973 |
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|
974 |
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975 |
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|
976 |
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value: 18.046
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977 |
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|
978 |
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value: 7.192
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979 |
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|
980 |
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value: 1.51
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981 |
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|
982 |
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value: 0.22499999999999998
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983 |
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|
984 |
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value: 13.312
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985 |
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|
986 |
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value: 10.775
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987 |
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|
988 |
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value: 7.71
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989 |
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|
990 |
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value: 27.908
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991 |
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|
992 |
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value: 54.452
|
993 |
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|
994 |
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value: 76.764
|
995 |
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|
996 |
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value: 16.64
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997 |
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- type: recall_at_5
|
998 |
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value: 21.631
|
999 |
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- task:
|
1000 |
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type: Retrieval
|
1001 |
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dataset:
|
1002 |
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type: dbpedia-entity
|
1003 |
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name: MTEB DBPedia
|
1004 |
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config: default
|
1005 |
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split: test
|
1006 |
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metrics:
|
1007 |
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|
1008 |
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value: 6.8180000000000005
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1009 |
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|
1010 |
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value: 14.591000000000001
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1011 |
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|
1012 |
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|
1013 |
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|
1014 |
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value: 21.178
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1015 |
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|
1016 |
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value: 10.345
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1017 |
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|
1018 |
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value: 12.367
|
1019 |
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|
1020 |
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value: 39.25
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1021 |
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|
1022 |
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value: 32.088
|
1023 |
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|
1024 |
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value: 36.019
|
1025 |
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|
1026 |
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value: 43.649
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1027 |
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|
1028 |
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value: 35.132999999999996
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1029 |
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- type: ndcg_at_5
|
1030 |
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value: 33.777
|
1031 |
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|
1032 |
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value: 49.5
|
1033 |
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- type: precision_at_10
|
1034 |
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value: 25.624999999999996
|
1035 |
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- type: precision_at_100
|
1036 |
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value: 8.043
|
1037 |
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- type: precision_at_1000
|
1038 |
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value: 1.7409999999999999
|
1039 |
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1040 |
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value: 38.417
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1041 |
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- type: precision_at_5
|
1042 |
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value: 33.2
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1043 |
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- type: recall_at_1
|
1044 |
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value: 6.8180000000000005
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1045 |
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- type: recall_at_10
|
1046 |
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value: 20.399
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1047 |
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- type: recall_at_100
|
1048 |
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value: 42.8
|
1049 |
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- type: recall_at_1000
|
1050 |
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value: 68.081
|
1051 |
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- type: recall_at_3
|
1052 |
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value: 11.928999999999998
|
1053 |
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- type: recall_at_5
|
1054 |
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value: 15.348999999999998
|
1055 |
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- task:
|
1056 |
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type: Classification
|
1057 |
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dataset:
|
1058 |
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type: mteb/emotion
|
1059 |
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name: MTEB EmotionClassification
|
1060 |
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config: default
|
1061 |
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split: test
|
1062 |
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metrics:
|
1063 |
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- type: accuracy
|
1064 |
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value: 39.725
|
1065 |
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- type: f1
|
1066 |
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value: 35.19385687310605
|
1067 |
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- task:
|
1068 |
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type: Retrieval
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1069 |
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dataset:
|
1070 |
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type: fever
|
1071 |
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name: MTEB FEVER
|
1072 |
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config: default
|
1073 |
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split: test
|
1074 |
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metrics:
|
1075 |
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- type: map_at_1
|
1076 |
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value: 31.901000000000003
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1077 |
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- type: map_at_10
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1078 |
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value: 44.156
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1079 |
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- type: map_at_100
|
1080 |
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value: 44.901
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1081 |
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- type: map_at_1000
|
1082 |
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value: 44.939
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1083 |
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|
1084 |
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value: 41.008
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1085 |
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|
1086 |
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value: 42.969
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1087 |
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- type: ndcg_at_1
|
1088 |
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value: 34.263
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1089 |
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|
1090 |
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value: 50.863
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1091 |
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- type: ndcg_at_100
|
1092 |
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value: 54.336
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1093 |
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- type: ndcg_at_1000
|
1094 |
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value: 55.297
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1095 |
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|
1096 |
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value: 44.644
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1097 |
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|
1098 |
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value: 48.075
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1099 |
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- type: precision_at_1
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1100 |
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value: 34.263
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1101 |
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- type: precision_at_10
|
1102 |
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value: 7.542999999999999
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1103 |
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- type: precision_at_100
|
1104 |
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value: 0.9400000000000001
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1105 |
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- type: precision_at_1000
|
1106 |
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value: 0.104
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1107 |
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- type: precision_at_3
|
1108 |
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value: 18.912000000000003
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1109 |
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- type: precision_at_5
|
1110 |
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value: 13.177
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1111 |
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- type: recall_at_1
|
1112 |
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value: 31.901000000000003
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1113 |
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- type: recall_at_10
|
1114 |
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value: 68.872
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1115 |
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- type: recall_at_100
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1116 |
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value: 84.468
|
1117 |
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- type: recall_at_1000
|
1118 |
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value: 91.694
|
1119 |
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- type: recall_at_3
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1120 |
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value: 52.272
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1121 |
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- type: recall_at_5
|
1122 |
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value: 60.504999999999995
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1123 |
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- task:
|
1124 |
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type: Retrieval
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1125 |
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dataset:
|
1126 |
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type: fiqa
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1127 |
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name: MTEB FiQA2018
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1128 |
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config: default
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1129 |
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split: test
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1130 |
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metrics:
|
1131 |
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- type: map_at_1
|
1132 |
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value: 24.4
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1133 |
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|
1134 |
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value: 41.117
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1135 |
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1136 |
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value: 43.167
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1137 |
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1138 |
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value: 43.323
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1139 |
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1140 |
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value: 35.744
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1141 |
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- type: map_at_5
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1142 |
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value: 38.708
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1143 |
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- type: ndcg_at_1
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1144 |
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value: 49.074
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1145 |
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- type: ndcg_at_10
|
1146 |
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value: 49.963
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1147 |
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- type: ndcg_at_100
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1148 |
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value: 56.564
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1149 |
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- type: ndcg_at_1000
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1150 |
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value: 58.931999999999995
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1151 |
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- type: ndcg_at_3
|
1152 |
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value: 45.489000000000004
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1153 |
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- type: ndcg_at_5
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1154 |
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value: 47.133
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1155 |
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- type: precision_at_1
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1156 |
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value: 49.074
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1157 |
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|
1158 |
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value: 13.889000000000001
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1159 |
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- type: precision_at_100
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1160 |
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value: 2.091
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1161 |
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- type: precision_at_1000
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1162 |
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value: 0.251
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1163 |
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- type: precision_at_3
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1164 |
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value: 30.658
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1165 |
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- type: precision_at_5
|
1166 |
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value: 22.593
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1167 |
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- type: recall_at_1
|
1168 |
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value: 24.4
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1169 |
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- type: recall_at_10
|
1170 |
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value: 58.111999999999995
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1171 |
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- type: recall_at_100
|
1172 |
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value: 81.96900000000001
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1173 |
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- type: recall_at_1000
|
1174 |
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value: 96.187
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1175 |
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- type: recall_at_3
|
1176 |
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value: 41.661
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1177 |
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- type: recall_at_5
|
1178 |
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value: 49.24
|
1179 |
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- task:
|
1180 |
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type: Retrieval
|
1181 |
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dataset:
|
1182 |
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type: hotpotqa
|
1183 |
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name: MTEB HotpotQA
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1184 |
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config: default
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1185 |
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split: test
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1186 |
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metrics:
|
1187 |
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- type: map_at_1
|
1188 |
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value: 22.262
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1189 |
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- type: map_at_10
|
1190 |
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value: 31.266
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1191 |
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- type: map_at_100
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1192 |
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value: 32.202
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1193 |
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- type: map_at_1000
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1194 |
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value: 32.300000000000004
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1195 |
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- type: map_at_3
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1196 |
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value: 28.874
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1197 |
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- type: map_at_5
|
1198 |
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value: 30.246000000000002
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1199 |
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- type: ndcg_at_1
|
1200 |
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value: 44.524
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1201 |
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- type: ndcg_at_10
|
1202 |
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value: 39.294000000000004
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1203 |
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- type: ndcg_at_100
|
1204 |
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value: 43.296
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1205 |
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- type: ndcg_at_1000
|
1206 |
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value: 45.561
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1207 |
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- type: ndcg_at_3
|
1208 |
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value: 35.013
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1209 |
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- type: ndcg_at_5
|
1210 |
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value: 37.177
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1211 |
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- type: precision_at_1
|
1212 |
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value: 44.524
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1213 |
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- type: precision_at_10
|
1214 |
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value: 8.52
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1215 |
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- type: precision_at_100
|
1216 |
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value: 1.169
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1217 |
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- type: precision_at_1000
|
1218 |
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value: 0.147
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1219 |
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- type: precision_at_3
|
1220 |
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value: 22.003
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1221 |
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- type: precision_at_5
|
1222 |
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value: 14.914
|
1223 |
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- type: recall_at_1
|
1224 |
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value: 22.262
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1225 |
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- type: recall_at_10
|
1226 |
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value: 42.6
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1227 |
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- type: recall_at_100
|
1228 |
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value: 58.46
|
1229 |
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- type: recall_at_1000
|
1230 |
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value: 73.565
|
1231 |
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- type: recall_at_3
|
1232 |
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value: 33.005
|
1233 |
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- type: recall_at_5
|
1234 |
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value: 37.286
|
1235 |
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- task:
|
1236 |
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type: Classification
|
1237 |
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dataset:
|
1238 |
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type: mteb/imdb
|
1239 |
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name: MTEB ImdbClassification
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1240 |
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config: default
|
1241 |
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split: test
|
1242 |
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metrics:
|
1243 |
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- type: accuracy
|
1244 |
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value: 70.7156
|
1245 |
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- type: ap
|
1246 |
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value: 64.89470531959896
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1247 |
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- type: f1
|
1248 |
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value: 70.53051887683772
|
1249 |
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- task:
|
1250 |
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type: Retrieval
|
1251 |
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dataset:
|
1252 |
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type: msmarco
|
1253 |
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name: MTEB MSMARCO
|
1254 |
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config: default
|
1255 |
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split: dev
|
1256 |
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metrics:
|
1257 |
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- type: map_at_1
|
1258 |
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value: 21.174
|
1259 |
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- type: map_at_10
|
1260 |
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value: 33.0
|
1261 |
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- type: map_at_100
|
1262 |
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value: 34.178
|
1263 |
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- type: map_at_1000
|
1264 |
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value: 34.227000000000004
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1265 |
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- type: map_at_3
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1266 |
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value: 29.275000000000002
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1267 |
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- type: map_at_5
|
1268 |
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value: 31.341
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1269 |
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- type: ndcg_at_1
|
1270 |
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value: 21.776999999999997
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1271 |
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- type: ndcg_at_10
|
1272 |
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value: 39.745999999999995
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1273 |
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- type: ndcg_at_100
|
1274 |
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value: 45.488
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1275 |
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- type: ndcg_at_1000
|
1276 |
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value: 46.733999999999995
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1277 |
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- type: ndcg_at_3
|
1278 |
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value: 32.086
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1279 |
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- type: ndcg_at_5
|
1280 |
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value: 35.792
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1281 |
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- type: precision_at_1
|
1282 |
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value: 21.776999999999997
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1283 |
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- type: precision_at_10
|
1284 |
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value: 6.324000000000001
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1285 |
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- type: precision_at_100
|
1286 |
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value: 0.922
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1287 |
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1288 |
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value: 0.10300000000000001
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1289 |
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- type: precision_at_3
|
1290 |
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value: 13.696
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1291 |
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- type: precision_at_5
|
1292 |
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value: 10.100000000000001
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1293 |
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- type: recall_at_1
|
1294 |
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value: 21.174
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1295 |
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- type: recall_at_10
|
1296 |
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value: 60.488
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1297 |
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- type: recall_at_100
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1298 |
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value: 87.234
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1299 |
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- type: recall_at_1000
|
1300 |
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value: 96.806
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1301 |
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- type: recall_at_3
|
1302 |
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value: 39.582
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1303 |
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- type: recall_at_5
|
1304 |
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value: 48.474000000000004
|
1305 |
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- task:
|
1306 |
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type: Classification
|
1307 |
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dataset:
|
1308 |
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type: mteb/mtop_domain
|
1309 |
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name: MTEB MTOPDomainClassification (en)
|
1310 |
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config: en
|
1311 |
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split: test
|
1312 |
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metrics:
|
1313 |
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- type: accuracy
|
1314 |
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value: 92.07934336525308
|
1315 |
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- type: f1
|
1316 |
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value: 91.93440027035814
|
1317 |
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- task:
|
1318 |
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type: Classification
|
1319 |
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dataset:
|
1320 |
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type: mteb/mtop_intent
|
1321 |
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name: MTEB MTOPIntentClassification (en)
|
1322 |
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config: en
|
1323 |
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split: test
|
1324 |
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metrics:
|
1325 |
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- type: accuracy
|
1326 |
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value: 70.20975832193344
|
1327 |
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- type: f1
|
1328 |
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value: 48.571776628850074
|
1329 |
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- task:
|
1330 |
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type: Classification
|
1331 |
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dataset:
|
1332 |
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type: mteb/amazon_massive_intent
|
1333 |
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name: MTEB MassiveIntentClassification (en)
|
1334 |
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config: en
|
1335 |
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split: test
|
1336 |
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metrics:
|
1337 |
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- type: accuracy
|
1338 |
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value: 69.56624075319435
|
1339 |
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- type: f1
|
1340 |
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value: 67.64419185784621
|
1341 |
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- task:
|
1342 |
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type: Classification
|
1343 |
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dataset:
|
1344 |
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type: mteb/amazon_massive_scenario
|
1345 |
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name: MTEB MassiveScenarioClassification (en)
|
1346 |
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config: en
|
1347 |
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split: test
|
1348 |
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metrics:
|
1349 |
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- type: accuracy
|
1350 |
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value: 76.01210490921318
|
1351 |
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- type: f1
|
1352 |
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value: 75.1934366365826
|
1353 |
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- task:
|
1354 |
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type: Clustering
|
1355 |
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dataset:
|
1356 |
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type: mteb/medrxiv-clustering-p2p
|
1357 |
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name: MTEB MedrxivClusteringP2P
|
1358 |
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config: default
|
1359 |
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split: test
|
1360 |
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metrics:
|
1361 |
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- type: v_measure
|
1362 |
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value: 35.58002813186373
|
1363 |
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- task:
|
1364 |
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type: Clustering
|
1365 |
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dataset:
|
1366 |
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type: mteb/medrxiv-clustering-s2s
|
1367 |
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name: MTEB MedrxivClusteringS2S
|
1368 |
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config: default
|
1369 |
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split: test
|
1370 |
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metrics:
|
1371 |
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- type: v_measure
|
1372 |
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value: 32.872725562410444
|
1373 |
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- task:
|
1374 |
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type: Reranking
|
1375 |
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dataset:
|
1376 |
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type: mteb/mind_small
|
1377 |
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name: MTEB MindSmallReranking
|
1378 |
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config: default
|
1379 |
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split: test
|
1380 |
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metrics:
|
1381 |
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- type: map
|
1382 |
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value: 30.965343604861328
|
1383 |
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- type: mrr
|
1384 |
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value: 31.933710165863594
|
1385 |
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- task:
|
1386 |
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type: Retrieval
|
1387 |
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dataset:
|
1388 |
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type: nfcorpus
|
1389 |
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name: MTEB NFCorpus
|
1390 |
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config: default
|
1391 |
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split: test
|
1392 |
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metrics:
|
1393 |
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|
1394 |
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value: 4.938
|
1395 |
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1396 |
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value: 12.034
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1397 |
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1398 |
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value: 15.675
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1399 |
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1400 |
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value: 17.18
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1401 |
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1402 |
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value: 8.471
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1403 |
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1404 |
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value: 10.128
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1405 |
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1406 |
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value: 40.402
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1407 |
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1408 |
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value: 33.289
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1409 |
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- type: ndcg_at_100
|
1410 |
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value: 31.496000000000002
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1411 |
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1412 |
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1413 |
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1414 |
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value: 37.841
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1415 |
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1416 |
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value: 36.215
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1417 |
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1418 |
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value: 41.796
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1419 |
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1420 |
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value: 25.294
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1421 |
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1422 |
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value: 8.381
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1423 |
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1424 |
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1425 |
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1426 |
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value: 36.429
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1427 |
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1428 |
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value: 32.446000000000005
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1429 |
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1430 |
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value: 4.938
|
1431 |
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- type: recall_at_10
|
1432 |
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value: 16.637
|
1433 |
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- type: recall_at_100
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1434 |
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value: 33.853
|
1435 |
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- type: recall_at_1000
|
1436 |
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value: 66.07
|
1437 |
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- type: recall_at_3
|
1438 |
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value: 9.818
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1439 |
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- type: recall_at_5
|
1440 |
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value: 12.544
|
1441 |
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- task:
|
1442 |
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type: Retrieval
|
1443 |
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dataset:
|
1444 |
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type: nq
|
1445 |
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name: MTEB NQ
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1446 |
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config: default
|
1447 |
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split: test
|
1448 |
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metrics:
|
1449 |
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|
1450 |
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value: 27.124
|
1451 |
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- type: map_at_10
|
1452 |
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value: 42.418
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1453 |
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1454 |
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value: 43.633
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1455 |
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- type: map_at_1000
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1456 |
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value: 43.66
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1457 |
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|
1458 |
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value: 37.766
|
1459 |
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1460 |
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value: 40.482
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1461 |
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- type: ndcg_at_1
|
1462 |
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value: 30.794
|
1463 |
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- type: ndcg_at_10
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1464 |
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value: 50.449999999999996
|
1465 |
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- type: ndcg_at_100
|
1466 |
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value: 55.437999999999995
|
1467 |
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- type: ndcg_at_1000
|
1468 |
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value: 56.084
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1469 |
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- type: ndcg_at_3
|
1470 |
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value: 41.678
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1471 |
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- type: ndcg_at_5
|
1472 |
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value: 46.257
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1473 |
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- type: precision_at_1
|
1474 |
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value: 30.794
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1475 |
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- type: precision_at_10
|
1476 |
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value: 8.656
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1477 |
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- type: precision_at_100
|
1478 |
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value: 1.141
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1479 |
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- type: precision_at_1000
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1480 |
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value: 0.12
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1481 |
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- type: precision_at_3
|
1482 |
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value: 19.37
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1483 |
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- type: precision_at_5
|
1484 |
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value: 14.218
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1485 |
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- type: recall_at_1
|
1486 |
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value: 27.124
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1487 |
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- type: recall_at_10
|
1488 |
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value: 72.545
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1489 |
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- type: recall_at_100
|
1490 |
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value: 93.938
|
1491 |
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- type: recall_at_1000
|
1492 |
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value: 98.788
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1493 |
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- type: recall_at_3
|
1494 |
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value: 49.802
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1495 |
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- type: recall_at_5
|
1496 |
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value: 60.426
|
1497 |
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- task:
|
1498 |
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type: Retrieval
|
1499 |
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dataset:
|
1500 |
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type: quora
|
1501 |
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name: MTEB QuoraRetrieval
|
1502 |
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config: default
|
1503 |
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split: test
|
1504 |
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metrics:
|
1505 |
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- type: map_at_1
|
1506 |
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value: 69.33500000000001
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1507 |
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1508 |
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value: 83.554
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1509 |
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1510 |
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value: 84.237
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1511 |
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- type: map_at_1000
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1512 |
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value: 84.251
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1513 |
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- type: map_at_3
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1514 |
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value: 80.456
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1515 |
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- type: map_at_5
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1516 |
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value: 82.395
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1517 |
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- type: ndcg_at_1
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1518 |
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value: 80.06
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1519 |
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- type: ndcg_at_10
|
1520 |
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value: 87.46199999999999
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1521 |
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- type: ndcg_at_100
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1522 |
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value: 88.774
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1523 |
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- type: ndcg_at_1000
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1524 |
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value: 88.864
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1525 |
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- type: ndcg_at_3
|
1526 |
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value: 84.437
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1527 |
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1528 |
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value: 86.129
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1529 |
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- type: precision_at_1
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1530 |
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value: 80.06
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1531 |
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- type: precision_at_10
|
1532 |
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value: 13.418
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1533 |
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- type: precision_at_100
|
1534 |
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value: 1.536
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1535 |
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- type: precision_at_1000
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1536 |
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value: 0.157
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1537 |
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- type: precision_at_3
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1538 |
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value: 37.103
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1539 |
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- type: precision_at_5
|
1540 |
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value: 24.522
|
1541 |
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- type: recall_at_1
|
1542 |
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value: 69.33500000000001
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1543 |
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- type: recall_at_10
|
1544 |
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value: 95.03200000000001
|
1545 |
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- type: recall_at_100
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1546 |
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value: 99.559
|
1547 |
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- type: recall_at_1000
|
1548 |
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value: 99.98700000000001
|
1549 |
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- type: recall_at_3
|
1550 |
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value: 86.404
|
1551 |
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- type: recall_at_5
|
1552 |
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value: 91.12400000000001
|
1553 |
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- task:
|
1554 |
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type: Clustering
|
1555 |
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dataset:
|
1556 |
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type: mteb/reddit-clustering
|
1557 |
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name: MTEB RedditClustering
|
1558 |
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config: default
|
1559 |
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split: test
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1560 |
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metrics:
|
1561 |
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- type: v_measure
|
1562 |
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value: 54.824256698437324
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1563 |
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- task:
|
1564 |
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type: Clustering
|
1565 |
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dataset:
|
1566 |
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type: mteb/reddit-clustering-p2p
|
1567 |
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name: MTEB RedditClusteringP2P
|
1568 |
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config: default
|
1569 |
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split: test
|
1570 |
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metrics:
|
1571 |
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- type: v_measure
|
1572 |
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value: 56.768972678049366
|
1573 |
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- task:
|
1574 |
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type: Retrieval
|
1575 |
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dataset:
|
1576 |
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type: scidocs
|
1577 |
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name: MTEB SCIDOCS
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1578 |
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config: default
|
1579 |
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split: test
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1580 |
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metrics:
|
1581 |
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- type: map_at_1
|
1582 |
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value: 5.192
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1583 |
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1584 |
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value: 14.426
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1585 |
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- type: map_at_100
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1586 |
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value: 17.18
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1587 |
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- type: map_at_1000
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1588 |
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value: 17.580000000000002
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1589 |
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- type: map_at_3
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1590 |
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value: 9.94
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1591 |
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- type: map_at_5
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1592 |
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value: 12.077
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1593 |
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- type: ndcg_at_1
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1594 |
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value: 25.5
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1595 |
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- type: ndcg_at_10
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1596 |
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value: 23.765
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1597 |
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- type: ndcg_at_100
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1598 |
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value: 33.664
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1599 |
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- type: ndcg_at_1000
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1600 |
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value: 39.481
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1601 |
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- type: ndcg_at_3
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1602 |
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value: 21.813
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1603 |
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- type: ndcg_at_5
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1604 |
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value: 19.285
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1605 |
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- type: precision_at_1
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1606 |
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value: 25.5
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1607 |
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- type: precision_at_10
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1608 |
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value: 12.690000000000001
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1609 |
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- type: precision_at_100
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1610 |
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value: 2.71
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1611 |
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- type: precision_at_1000
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1612 |
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value: 0.409
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1613 |
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- type: precision_at_3
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1614 |
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value: 20.732999999999997
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1615 |
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- type: precision_at_5
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1616 |
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value: 17.24
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1617 |
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- type: recall_at_1
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1618 |
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value: 5.192
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1619 |
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- type: recall_at_10
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1620 |
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value: 25.712000000000003
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1621 |
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- type: recall_at_100
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1622 |
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value: 54.99699999999999
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1623 |
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- type: recall_at_1000
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1624 |
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value: 82.97200000000001
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1625 |
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- type: recall_at_3
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1626 |
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value: 12.631999999999998
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1627 |
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- type: recall_at_5
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1628 |
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value: 17.497
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1629 |
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- task:
|
1630 |
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type: STS
|
1631 |
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dataset:
|
1632 |
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type: mteb/sickr-sts
|
1633 |
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name: MTEB SICK-R
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1634 |
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config: default
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1635 |
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split: test
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1636 |
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metrics:
|
1637 |
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- type: cos_sim_pearson
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1638 |
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value: 84.00280838354293
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1639 |
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- type: cos_sim_spearman
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1640 |
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value: 80.5854192844009
|
1641 |
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- type: euclidean_pearson
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1642 |
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value: 80.55974827073891
|
1643 |
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- type: euclidean_spearman
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1644 |
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value: 80.58541460172292
|
1645 |
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- type: manhattan_pearson
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1646 |
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value: 80.27294578437488
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1647 |
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- type: manhattan_spearman
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1648 |
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value: 80.33176193921884
|
1649 |
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- task:
|
1650 |
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type: STS
|
1651 |
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dataset:
|
1652 |
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type: mteb/sts12-sts
|
1653 |
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name: MTEB STS12
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1654 |
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config: default
|
1655 |
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split: test
|
1656 |
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metrics:
|
1657 |
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- type: cos_sim_pearson
|
1658 |
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value: 83.2801353818369
|
1659 |
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- type: cos_sim_spearman
|
1660 |
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value: 72.63427853822449
|
1661 |
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- type: euclidean_pearson
|
1662 |
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value: 79.01343235899544
|
1663 |
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- type: euclidean_spearman
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1664 |
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value: 72.63178302036903
|
1665 |
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- type: manhattan_pearson
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1666 |
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value: 78.65899981586094
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1667 |
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- type: manhattan_spearman
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1668 |
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1669 |
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- task:
|
1670 |
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1671 |
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dataset:
|
1672 |
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type: mteb/sts13-sts
|
1673 |
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name: MTEB STS13
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1674 |
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config: default
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1675 |
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split: test
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1676 |
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metrics:
|
1677 |
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- type: cos_sim_pearson
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1678 |
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value: 83.20700572036095
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1679 |
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- type: cos_sim_spearman
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1680 |
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value: 83.48499016384896
|
1681 |
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- type: euclidean_pearson
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1682 |
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value: 82.82555353364394
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1683 |
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- type: euclidean_spearman
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1684 |
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value: 83.48499008964005
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1685 |
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- type: manhattan_pearson
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value: 82.46034885462956
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1687 |
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- type: manhattan_spearman
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1689 |
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|
1690 |
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type: STS
|
1691 |
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dataset:
|
1692 |
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type: mteb/sts14-sts
|
1693 |
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name: MTEB STS14
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1694 |
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config: default
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1695 |
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split: test
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1696 |
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metrics:
|
1697 |
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- type: cos_sim_pearson
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1698 |
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value: 82.27113025749529
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1699 |
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- type: cos_sim_spearman
|
1700 |
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value: 78.0001371342168
|
1701 |
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- type: euclidean_pearson
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1702 |
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value: 80.62651938409732
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1703 |
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- type: euclidean_spearman
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1704 |
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value: 78.0001341029446
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1705 |
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- type: manhattan_pearson
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1706 |
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value: 80.25786381999085
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1707 |
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- type: manhattan_spearman
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1708 |
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value: 77.68750207429126
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1709 |
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- task:
|
1710 |
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type: STS
|
1711 |
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dataset:
|
1712 |
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type: mteb/sts15-sts
|
1713 |
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name: MTEB STS15
|
1714 |
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config: default
|
1715 |
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split: test
|
1716 |
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metrics:
|
1717 |
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- type: cos_sim_pearson
|
1718 |
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value: 84.98824030948605
|
1719 |
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1720 |
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|
1721 |
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- type: euclidean_pearson
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1722 |
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value: 84.88733530073506
|
1723 |
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- type: euclidean_spearman
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1724 |
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value: 85.66275062257034
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1725 |
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- type: manhattan_pearson
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1726 |
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value: 84.70100813924223
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1727 |
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1728 |
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1729 |
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- task:
|
1730 |
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|
1731 |
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dataset:
|
1732 |
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type: mteb/sts16-sts
|
1733 |
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name: MTEB STS16
|
1734 |
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config: default
|
1735 |
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split: test
|
1736 |
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metrics:
|
1737 |
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|
1738 |
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value: 78.82478639193744
|
1739 |
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1740 |
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|
1741 |
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- type: euclidean_pearson
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1742 |
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value: 79.84794502236802
|
1743 |
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- type: euclidean_spearman
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1744 |
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|
1745 |
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- type: manhattan_pearson
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1746 |
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1747 |
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1748 |
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|
1749 |
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|
1750 |
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|
1751 |
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dataset:
|
1752 |
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type: mteb/sts17-crosslingual-sts
|
1753 |
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name: MTEB STS17 (en-en)
|
1754 |
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config: en-en
|
1755 |
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split: test
|
1756 |
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metrics:
|
1757 |
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1758 |
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value: 90.90804154377126
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1759 |
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- type: cos_sim_spearman
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1760 |
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|
1761 |
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- type: euclidean_pearson
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1762 |
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|
1763 |
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- type: euclidean_spearman
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1764 |
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1765 |
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- type: manhattan_pearson
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1766 |
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1767 |
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1768 |
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1769 |
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- task:
|
1770 |
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type: STS
|
1771 |
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dataset:
|
1772 |
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type: mteb/sts22-crosslingual-sts
|
1773 |
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name: MTEB STS22 (en)
|
1774 |
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config: en
|
1775 |
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split: test
|
1776 |
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metrics:
|
1777 |
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- type: cos_sim_pearson
|
1778 |
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value: 66.78771571400975
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1779 |
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- type: cos_sim_spearman
|
1780 |
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|
1781 |
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- type: euclidean_pearson
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1782 |
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1783 |
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- type: euclidean_spearman
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1784 |
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1785 |
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- type: manhattan_pearson
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1786 |
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1787 |
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1788 |
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1789 |
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- task:
|
1790 |
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|
1791 |
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dataset:
|
1792 |
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type: mteb/stsbenchmark-sts
|
1793 |
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name: MTEB STSBenchmark
|
1794 |
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config: default
|
1795 |
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split: test
|
1796 |
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metrics:
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1797 |
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1798 |
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1799 |
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- type: cos_sim_spearman
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1800 |
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|
1801 |
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- type: euclidean_pearson
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1802 |
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value: 83.78671249317563
|
1803 |
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1804 |
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|
1805 |
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- type: manhattan_pearson
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1806 |
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1807 |
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1808 |
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1809 |
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- task:
|
1810 |
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type: Reranking
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1811 |
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dataset:
|
1812 |
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type: mteb/scidocs-reranking
|
1813 |
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name: MTEB SciDocsRR
|
1814 |
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config: default
|
1815 |
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split: test
|
1816 |
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metrics:
|
1817 |
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- type: map
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1818 |
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1819 |
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- type: mrr
|
1820 |
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|
1821 |
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- task:
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1822 |
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|
1823 |
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dataset:
|
1824 |
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type: scifact
|
1825 |
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name: MTEB SciFact
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1826 |
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config: default
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1827 |
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split: test
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1828 |
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metrics:
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1829 |
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1830 |
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value: 51.456
|
1831 |
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1832 |
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1833 |
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1834 |
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1835 |
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1836 |
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1837 |
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1838 |
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1839 |
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1840 |
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1841 |
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1842 |
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1843 |
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1844 |
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1845 |
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1846 |
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1847 |
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1848 |
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1849 |
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1850 |
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1851 |
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1852 |
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1853 |
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1854 |
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1855 |
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1856 |
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1857 |
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1858 |
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1859 |
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1860 |
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1861 |
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1862 |
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1863 |
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1864 |
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1865 |
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1866 |
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1867 |
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1868 |
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value: 79.011
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1869 |
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1870 |
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value: 94.167
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1871 |
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1872 |
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value: 99.667
|
1873 |
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- type: recall_at_3
|
1874 |
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value: 64.506
|
1875 |
+
- type: recall_at_5
|
1876 |
+
value: 71.211
|
1877 |
+
- task:
|
1878 |
+
type: PairClassification
|
1879 |
+
dataset:
|
1880 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
1881 |
+
name: MTEB SprintDuplicateQuestions
|
1882 |
+
config: default
|
1883 |
+
split: test
|
1884 |
+
metrics:
|
1885 |
+
- type: cos_sim_accuracy
|
1886 |
+
value: 99.65940594059406
|
1887 |
+
- type: cos_sim_ap
|
1888 |
+
value: 90.1455141683116
|
1889 |
+
- type: cos_sim_f1
|
1890 |
+
value: 82.26044226044226
|
1891 |
+
- type: cos_sim_precision
|
1892 |
+
value: 80.8695652173913
|
1893 |
+
- type: cos_sim_recall
|
1894 |
+
value: 83.7
|
1895 |
+
- type: dot_accuracy
|
1896 |
+
value: 99.65940594059406
|
1897 |
+
- type: dot_ap
|
1898 |
+
value: 90.1455141683116
|
1899 |
+
- type: dot_f1
|
1900 |
+
value: 82.26044226044226
|
1901 |
+
- type: dot_precision
|
1902 |
+
value: 80.8695652173913
|
1903 |
+
- type: dot_recall
|
1904 |
+
value: 83.7
|
1905 |
+
- type: euclidean_accuracy
|
1906 |
+
value: 99.65940594059406
|
1907 |
+
- type: euclidean_ap
|
1908 |
+
value: 90.14551416831162
|
1909 |
+
- type: euclidean_f1
|
1910 |
+
value: 82.26044226044226
|
1911 |
+
- type: euclidean_precision
|
1912 |
+
value: 80.8695652173913
|
1913 |
+
- type: euclidean_recall
|
1914 |
+
value: 83.7
|
1915 |
+
- type: manhattan_accuracy
|
1916 |
+
value: 99.64950495049504
|
1917 |
+
- type: manhattan_ap
|
1918 |
+
value: 89.5492617367771
|
1919 |
+
- type: manhattan_f1
|
1920 |
+
value: 81.58280410356619
|
1921 |
+
- type: manhattan_precision
|
1922 |
+
value: 79.75167144221585
|
1923 |
+
- type: manhattan_recall
|
1924 |
+
value: 83.5
|
1925 |
+
- type: max_accuracy
|
1926 |
+
value: 99.65940594059406
|
1927 |
+
- type: max_ap
|
1928 |
+
value: 90.14551416831162
|
1929 |
+
- type: max_f1
|
1930 |
+
value: 82.26044226044226
|
1931 |
+
- task:
|
1932 |
+
type: Clustering
|
1933 |
+
dataset:
|
1934 |
+
type: mteb/stackexchange-clustering
|
1935 |
+
name: MTEB StackExchangeClustering
|
1936 |
+
config: default
|
1937 |
+
split: test
|
1938 |
+
metrics:
|
1939 |
+
- type: v_measure
|
1940 |
+
value: 53.80048409076929
|
1941 |
+
- task:
|
1942 |
+
type: Clustering
|
1943 |
+
dataset:
|
1944 |
+
type: mteb/stackexchange-clustering-p2p
|
1945 |
+
name: MTEB StackExchangeClusteringP2P
|
1946 |
+
config: default
|
1947 |
+
split: test
|
1948 |
+
metrics:
|
1949 |
+
- type: v_measure
|
1950 |
+
value: 34.280269334397545
|
1951 |
+
- task:
|
1952 |
+
type: Reranking
|
1953 |
+
dataset:
|
1954 |
+
type: mteb/stackoverflowdupquestions-reranking
|
1955 |
+
name: MTEB StackOverflowDupQuestions
|
1956 |
+
config: default
|
1957 |
+
split: test
|
1958 |
+
metrics:
|
1959 |
+
- type: map
|
1960 |
+
value: 51.97907654945493
|
1961 |
+
- type: mrr
|
1962 |
+
value: 52.82873376623376
|
1963 |
+
- task:
|
1964 |
+
type: Summarization
|
1965 |
+
dataset:
|
1966 |
+
type: mteb/summeval
|
1967 |
+
name: MTEB SummEval
|
1968 |
+
config: default
|
1969 |
+
split: test
|
1970 |
+
metrics:
|
1971 |
+
- type: cos_sim_pearson
|
1972 |
+
value: 28.364293841556304
|
1973 |
+
- type: cos_sim_spearman
|
1974 |
+
value: 27.485869639926136
|
1975 |
+
- type: dot_pearson
|
1976 |
+
value: 28.364295910221145
|
1977 |
+
- type: dot_spearman
|
1978 |
+
value: 27.485869639926136
|
1979 |
+
- task:
|
1980 |
+
type: Retrieval
|
1981 |
+
dataset:
|
1982 |
+
type: trec-covid
|
1983 |
+
name: MTEB TRECCOVID
|
1984 |
+
config: default
|
1985 |
+
split: test
|
1986 |
+
metrics:
|
1987 |
+
- type: map_at_1
|
1988 |
+
value: 0.19499999999999998
|
1989 |
+
- type: map_at_10
|
1990 |
+
value: 1.218
|
1991 |
+
- type: map_at_100
|
1992 |
+
value: 7.061000000000001
|
1993 |
+
- type: map_at_1000
|
1994 |
+
value: 19.735
|
1995 |
+
- type: map_at_3
|
1996 |
+
value: 0.46499999999999997
|
1997 |
+
- type: map_at_5
|
1998 |
+
value: 0.672
|
1999 |
+
- type: ndcg_at_1
|
2000 |
+
value: 60.0
|
2001 |
+
- type: ndcg_at_10
|
2002 |
+
value: 51.32600000000001
|
2003 |
+
- type: ndcg_at_100
|
2004 |
+
value: 41.74
|
2005 |
+
- type: ndcg_at_1000
|
2006 |
+
value: 43.221
|
2007 |
+
- type: ndcg_at_3
|
2008 |
+
value: 54.989
|
2009 |
+
- type: ndcg_at_5
|
2010 |
+
value: 52.905
|
2011 |
+
- type: precision_at_1
|
2012 |
+
value: 66.0
|
2013 |
+
- type: precision_at_10
|
2014 |
+
value: 55.60000000000001
|
2015 |
+
- type: precision_at_100
|
2016 |
+
value: 43.34
|
2017 |
+
- type: precision_at_1000
|
2018 |
+
value: 19.994
|
2019 |
+
- type: precision_at_3
|
2020 |
+
value: 59.333000000000006
|
2021 |
+
- type: precision_at_5
|
2022 |
+
value: 57.199999999999996
|
2023 |
+
- type: recall_at_1
|
2024 |
+
value: 0.19499999999999998
|
2025 |
+
- type: recall_at_10
|
2026 |
+
value: 1.473
|
2027 |
+
- type: recall_at_100
|
2028 |
+
value: 10.596
|
2029 |
+
- type: recall_at_1000
|
2030 |
+
value: 42.466
|
2031 |
+
- type: recall_at_3
|
2032 |
+
value: 0.49899999999999994
|
2033 |
+
- type: recall_at_5
|
2034 |
+
value: 0.76
|
2035 |
+
- task:
|
2036 |
+
type: Retrieval
|
2037 |
+
dataset:
|
2038 |
+
type: webis-touche2020
|
2039 |
+
name: MTEB Touche2020
|
2040 |
+
config: default
|
2041 |
+
split: test
|
2042 |
+
metrics:
|
2043 |
+
- type: map_at_1
|
2044 |
+
value: 1.997
|
2045 |
+
- type: map_at_10
|
2046 |
+
value: 7.5569999999999995
|
2047 |
+
- type: map_at_100
|
2048 |
+
value: 12.238
|
2049 |
+
- type: map_at_1000
|
2050 |
+
value: 13.773
|
2051 |
+
- type: map_at_3
|
2052 |
+
value: 4.334
|
2053 |
+
- type: map_at_5
|
2054 |
+
value: 5.5
|
2055 |
+
- type: ndcg_at_1
|
2056 |
+
value: 22.448999999999998
|
2057 |
+
- type: ndcg_at_10
|
2058 |
+
value: 19.933999999999997
|
2059 |
+
- type: ndcg_at_100
|
2060 |
+
value: 30.525999999999996
|
2061 |
+
- type: ndcg_at_1000
|
2062 |
+
value: 43.147999999999996
|
2063 |
+
- type: ndcg_at_3
|
2064 |
+
value: 22.283
|
2065 |
+
- type: ndcg_at_5
|
2066 |
+
value: 21.224
|
2067 |
+
- type: precision_at_1
|
2068 |
+
value: 24.490000000000002
|
2069 |
+
- type: precision_at_10
|
2070 |
+
value: 17.551
|
2071 |
+
- type: precision_at_100
|
2072 |
+
value: 6.4079999999999995
|
2073 |
+
- type: precision_at_1000
|
2074 |
+
value: 1.463
|
2075 |
+
- type: precision_at_3
|
2076 |
+
value: 23.128999999999998
|
2077 |
+
- type: precision_at_5
|
2078 |
+
value: 20.816000000000003
|
2079 |
+
- type: recall_at_1
|
2080 |
+
value: 1.997
|
2081 |
+
- type: recall_at_10
|
2082 |
+
value: 13.001999999999999
|
2083 |
+
- type: recall_at_100
|
2084 |
+
value: 40.98
|
2085 |
+
- type: recall_at_1000
|
2086 |
+
value: 79.40899999999999
|
2087 |
+
- type: recall_at_3
|
2088 |
+
value: 5.380999999999999
|
2089 |
+
- type: recall_at_5
|
2090 |
+
value: 7.721
|
2091 |
+
- task:
|
2092 |
+
type: Classification
|
2093 |
+
dataset:
|
2094 |
+
type: mteb/toxic_conversations_50k
|
2095 |
+
name: MTEB ToxicConversationsClassification
|
2096 |
+
config: default
|
2097 |
+
split: test
|
2098 |
+
metrics:
|
2099 |
+
- type: accuracy
|
2100 |
+
value: 60.861200000000004
|
2101 |
+
- type: ap
|
2102 |
+
value: 11.39641747026629
|
2103 |
+
- type: f1
|
2104 |
+
value: 47.80230380517065
|
2105 |
+
- task:
|
2106 |
+
type: Classification
|
2107 |
+
dataset:
|
2108 |
+
type: mteb/tweet_sentiment_extraction
|
2109 |
+
name: MTEB TweetSentimentExtractionClassification
|
2110 |
+
config: default
|
2111 |
+
split: test
|
2112 |
+
metrics:
|
2113 |
+
- type: accuracy
|
2114 |
+
value: 55.464063384267114
|
2115 |
+
- type: f1
|
2116 |
+
value: 55.759039643764666
|
2117 |
+
- task:
|
2118 |
+
type: Clustering
|
2119 |
+
dataset:
|
2120 |
+
type: mteb/twentynewsgroups-clustering
|
2121 |
+
name: MTEB TwentyNewsgroupsClustering
|
2122 |
+
config: default
|
2123 |
+
split: test
|
2124 |
+
metrics:
|
2125 |
+
- type: v_measure
|
2126 |
+
value: 49.74455348083809
|
2127 |
+
- task:
|
2128 |
+
type: PairClassification
|
2129 |
+
dataset:
|
2130 |
+
type: mteb/twittersemeval2015-pairclassification
|
2131 |
+
name: MTEB TwitterSemEval2015
|
2132 |
+
config: default
|
2133 |
+
split: test
|
2134 |
+
metrics:
|
2135 |
+
- type: cos_sim_accuracy
|
2136 |
+
value: 86.07617571675507
|
2137 |
+
- type: cos_sim_ap
|
2138 |
+
value: 73.85398650568216
|
2139 |
+
- type: cos_sim_f1
|
2140 |
+
value: 68.50702798531087
|
2141 |
+
- type: cos_sim_precision
|
2142 |
+
value: 65.86316045775506
|
2143 |
+
- type: cos_sim_recall
|
2144 |
+
value: 71.37203166226914
|
2145 |
+
- type: dot_accuracy
|
2146 |
+
value: 86.07617571675507
|
2147 |
+
- type: dot_ap
|
2148 |
+
value: 73.85398346238429
|
2149 |
+
- type: dot_f1
|
2150 |
+
value: 68.50702798531087
|
2151 |
+
- type: dot_precision
|
2152 |
+
value: 65.86316045775506
|
2153 |
+
- type: dot_recall
|
2154 |
+
value: 71.37203166226914
|
2155 |
+
- type: euclidean_accuracy
|
2156 |
+
value: 86.07617571675507
|
2157 |
+
- type: euclidean_ap
|
2158 |
+
value: 73.85398625060357
|
2159 |
+
- type: euclidean_f1
|
2160 |
+
value: 68.50702798531087
|
2161 |
+
- type: euclidean_precision
|
2162 |
+
value: 65.86316045775506
|
2163 |
+
- type: euclidean_recall
|
2164 |
+
value: 71.37203166226914
|
2165 |
+
- type: manhattan_accuracy
|
2166 |
+
value: 85.98676759849795
|
2167 |
+
- type: manhattan_ap
|
2168 |
+
value: 73.86874126878737
|
2169 |
+
- type: manhattan_f1
|
2170 |
+
value: 68.55096559662361
|
2171 |
+
- type: manhattan_precision
|
2172 |
+
value: 66.51774633904195
|
2173 |
+
- type: manhattan_recall
|
2174 |
+
value: 70.71240105540898
|
2175 |
+
- type: max_accuracy
|
2176 |
+
value: 86.07617571675507
|
2177 |
+
- type: max_ap
|
2178 |
+
value: 73.86874126878737
|
2179 |
+
- type: max_f1
|
2180 |
+
value: 68.55096559662361
|
2181 |
+
- task:
|
2182 |
+
type: PairClassification
|
2183 |
+
dataset:
|
2184 |
+
type: mteb/twitterurlcorpus-pairclassification
|
2185 |
+
name: MTEB TwitterURLCorpus
|
2186 |
+
config: default
|
2187 |
+
split: test
|
2188 |
+
metrics:
|
2189 |
+
- type: cos_sim_accuracy
|
2190 |
+
value: 88.51631932316529
|
2191 |
+
- type: cos_sim_ap
|
2192 |
+
value: 85.10831084479727
|
2193 |
+
- type: cos_sim_f1
|
2194 |
+
value: 77.14563397129186
|
2195 |
+
- type: cos_sim_precision
|
2196 |
+
value: 74.9709386806161
|
2197 |
+
- type: cos_sim_recall
|
2198 |
+
value: 79.45026178010471
|
2199 |
+
- type: dot_accuracy
|
2200 |
+
value: 88.51631932316529
|
2201 |
+
- type: dot_ap
|
2202 |
+
value: 85.10831188797107
|
2203 |
+
- type: dot_f1
|
2204 |
+
value: 77.14563397129186
|
2205 |
+
- type: dot_precision
|
2206 |
+
value: 74.9709386806161
|
2207 |
+
- type: dot_recall
|
2208 |
+
value: 79.45026178010471
|
2209 |
+
- type: euclidean_accuracy
|
2210 |
+
value: 88.51631932316529
|
2211 |
+
- type: euclidean_ap
|
2212 |
+
value: 85.10829618408616
|
2213 |
+
- type: euclidean_f1
|
2214 |
+
value: 77.14563397129186
|
2215 |
+
- type: euclidean_precision
|
2216 |
+
value: 74.9709386806161
|
2217 |
+
- type: euclidean_recall
|
2218 |
+
value: 79.45026178010471
|
2219 |
+
- type: manhattan_accuracy
|
2220 |
+
value: 88.50467652423643
|
2221 |
+
- type: manhattan_ap
|
2222 |
+
value: 85.08329502055064
|
2223 |
+
- type: manhattan_f1
|
2224 |
+
value: 77.11157455683002
|
2225 |
+
- type: manhattan_precision
|
2226 |
+
value: 74.67541834968263
|
2227 |
+
- type: manhattan_recall
|
2228 |
+
value: 79.71204188481676
|
2229 |
+
- type: max_accuracy
|
2230 |
+
value: 88.51631932316529
|
2231 |
+
- type: max_ap
|
2232 |
+
value: 85.10831188797107
|
2233 |
+
- type: max_f1
|
2234 |
+
value: 77.14563397129186
|
2235 |
---
|
2236 |
|
2237 |
|