add mteb benchmark results
Browse files
README.md
CHANGED
@@ -4,10 +4,1710 @@ tags:
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- finetuner
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- feature-extraction
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- sentence-similarity
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datasets:
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- jinaai/negation-dataset
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language: en
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license: apache-2.0
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|
11 |
---
|
12 |
|
13 |
<br><br>
|
|
|
4 |
- finetuner
|
5 |
- feature-extraction
|
6 |
- sentence-similarity
|
7 |
+
- mteb
|
8 |
datasets:
|
9 |
- jinaai/negation-dataset
|
10 |
language: en
|
11 |
license: apache-2.0
|
12 |
+
model-index:
|
13 |
+
- name: jina-embedding-s-en-v1
|
14 |
+
results:
|
15 |
+
- task:
|
16 |
+
type: Classification
|
17 |
+
dataset:
|
18 |
+
type: mteb/amazon_counterfactual
|
19 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
20 |
+
config: en
|
21 |
+
split: test
|
22 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
23 |
+
metrics:
|
24 |
+
- type: accuracy
|
25 |
+
value: 64.58208955223881
|
26 |
+
- type: ap
|
27 |
+
value: 27.24359671025387
|
28 |
+
- type: f1
|
29 |
+
value: 58.201387941715495
|
30 |
+
- task:
|
31 |
+
type: Classification
|
32 |
+
dataset:
|
33 |
+
type: mteb/amazon_polarity
|
34 |
+
name: MTEB AmazonPolarityClassification
|
35 |
+
config: default
|
36 |
+
split: test
|
37 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
38 |
+
metrics:
|
39 |
+
- type: accuracy
|
40 |
+
value: 61.926550000000006
|
41 |
+
- type: ap
|
42 |
+
value: 58.40954250092862
|
43 |
+
- type: f1
|
44 |
+
value: 59.921771639047904
|
45 |
+
- task:
|
46 |
+
type: Classification
|
47 |
+
dataset:
|
48 |
+
type: mteb/amazon_reviews_multi
|
49 |
+
name: MTEB AmazonReviewsClassification (en)
|
50 |
+
config: en
|
51 |
+
split: test
|
52 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
53 |
+
metrics:
|
54 |
+
- type: accuracy
|
55 |
+
value: 28.499999999999996
|
56 |
+
- type: f1
|
57 |
+
value: 27.160929516206465
|
58 |
+
- task:
|
59 |
+
type: Retrieval
|
60 |
+
dataset:
|
61 |
+
type: arguana
|
62 |
+
name: MTEB ArguAna
|
63 |
+
config: default
|
64 |
+
split: test
|
65 |
+
revision: None
|
66 |
+
metrics:
|
67 |
+
- type: map_at_1
|
68 |
+
value: 22.262
|
69 |
+
- type: map_at_10
|
70 |
+
value: 36.677
|
71 |
+
- type: map_at_100
|
72 |
+
value: 37.839
|
73 |
+
- type: map_at_1000
|
74 |
+
value: 37.857
|
75 |
+
- type: map_at_3
|
76 |
+
value: 31.685999999999996
|
77 |
+
- type: map_at_5
|
78 |
+
value: 34.544999999999995
|
79 |
+
- type: mrr_at_1
|
80 |
+
value: 22.404
|
81 |
+
- type: mrr_at_10
|
82 |
+
value: 36.713
|
83 |
+
- type: mrr_at_100
|
84 |
+
value: 37.881
|
85 |
+
- type: mrr_at_1000
|
86 |
+
value: 37.899
|
87 |
+
- type: mrr_at_3
|
88 |
+
value: 31.709
|
89 |
+
- type: mrr_at_5
|
90 |
+
value: 34.629
|
91 |
+
- type: ndcg_at_1
|
92 |
+
value: 22.262
|
93 |
+
- type: ndcg_at_10
|
94 |
+
value: 45.18
|
95 |
+
- type: ndcg_at_100
|
96 |
+
value: 50.4
|
97 |
+
- type: ndcg_at_1000
|
98 |
+
value: 50.841
|
99 |
+
- type: ndcg_at_3
|
100 |
+
value: 34.882000000000005
|
101 |
+
- type: ndcg_at_5
|
102 |
+
value: 40.036
|
103 |
+
- type: precision_at_1
|
104 |
+
value: 22.262
|
105 |
+
- type: precision_at_10
|
106 |
+
value: 7.255000000000001
|
107 |
+
- type: precision_at_100
|
108 |
+
value: 0.959
|
109 |
+
- type: precision_at_1000
|
110 |
+
value: 0.099
|
111 |
+
- type: precision_at_3
|
112 |
+
value: 14.723
|
113 |
+
- type: precision_at_5
|
114 |
+
value: 11.337
|
115 |
+
- type: recall_at_1
|
116 |
+
value: 22.262
|
117 |
+
- type: recall_at_10
|
118 |
+
value: 72.54599999999999
|
119 |
+
- type: recall_at_100
|
120 |
+
value: 95.946
|
121 |
+
- type: recall_at_1000
|
122 |
+
value: 99.36
|
123 |
+
- type: recall_at_3
|
124 |
+
value: 44.168
|
125 |
+
- type: recall_at_5
|
126 |
+
value: 56.686
|
127 |
+
- task:
|
128 |
+
type: Clustering
|
129 |
+
dataset:
|
130 |
+
type: mteb/arxiv-clustering-p2p
|
131 |
+
name: MTEB ArxivClusteringP2P
|
132 |
+
config: default
|
133 |
+
split: test
|
134 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
135 |
+
metrics:
|
136 |
+
- type: v_measure
|
137 |
+
value: 34.97570470844357
|
138 |
+
- task:
|
139 |
+
type: Clustering
|
140 |
+
dataset:
|
141 |
+
type: mteb/arxiv-clustering-s2s
|
142 |
+
name: MTEB ArxivClusteringS2S
|
143 |
+
config: default
|
144 |
+
split: test
|
145 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
146 |
+
metrics:
|
147 |
+
- type: v_measure
|
148 |
+
value: 24.372872291698265
|
149 |
+
- task:
|
150 |
+
type: Reranking
|
151 |
+
dataset:
|
152 |
+
type: mteb/askubuntudupquestions-reranking
|
153 |
+
name: MTEB AskUbuntuDupQuestions
|
154 |
+
config: default
|
155 |
+
split: test
|
156 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
157 |
+
metrics:
|
158 |
+
- type: map
|
159 |
+
value: 60.58753030525579
|
160 |
+
- type: mrr
|
161 |
+
value: 75.03484588664644
|
162 |
+
- task:
|
163 |
+
type: STS
|
164 |
+
dataset:
|
165 |
+
type: mteb/biosses-sts
|
166 |
+
name: MTEB BIOSSES
|
167 |
+
config: default
|
168 |
+
split: test
|
169 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
170 |
+
metrics:
|
171 |
+
- type: cos_sim_pearson
|
172 |
+
value: 85.21378425036666
|
173 |
+
- type: cos_sim_spearman
|
174 |
+
value: 80.45665253651644
|
175 |
+
- type: euclidean_pearson
|
176 |
+
value: 46.71436482437946
|
177 |
+
- type: euclidean_spearman
|
178 |
+
value: 45.13476336596072
|
179 |
+
- type: manhattan_pearson
|
180 |
+
value: 47.06449770246884
|
181 |
+
- type: manhattan_spearman
|
182 |
+
value: 45.498627078529
|
183 |
+
- task:
|
184 |
+
type: Classification
|
185 |
+
dataset:
|
186 |
+
type: mteb/banking77
|
187 |
+
name: MTEB Banking77Classification
|
188 |
+
config: default
|
189 |
+
split: test
|
190 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
191 |
+
metrics:
|
192 |
+
- type: accuracy
|
193 |
+
value: 74.48701298701299
|
194 |
+
- type: f1
|
195 |
+
value: 73.30813366682357
|
196 |
+
- task:
|
197 |
+
type: Clustering
|
198 |
+
dataset:
|
199 |
+
type: mteb/biorxiv-clustering-p2p
|
200 |
+
name: MTEB BiorxivClusteringP2P
|
201 |
+
config: default
|
202 |
+
split: test
|
203 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
204 |
+
metrics:
|
205 |
+
- type: v_measure
|
206 |
+
value: 29.66289767477026
|
207 |
+
- task:
|
208 |
+
type: Clustering
|
209 |
+
dataset:
|
210 |
+
type: mteb/biorxiv-clustering-s2s
|
211 |
+
name: MTEB BiorxivClusteringS2S
|
212 |
+
config: default
|
213 |
+
split: test
|
214 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
215 |
+
metrics:
|
216 |
+
- type: v_measure
|
217 |
+
value: 22.324367934720776
|
218 |
+
- task:
|
219 |
+
type: Retrieval
|
220 |
+
dataset:
|
221 |
+
type: climate-fever
|
222 |
+
name: MTEB ClimateFEVER
|
223 |
+
config: default
|
224 |
+
split: test
|
225 |
+
revision: None
|
226 |
+
metrics:
|
227 |
+
- type: map_at_1
|
228 |
+
value: 6.524000000000001
|
229 |
+
- type: map_at_10
|
230 |
+
value: 11.187
|
231 |
+
- type: map_at_100
|
232 |
+
value: 12.389999999999999
|
233 |
+
- type: map_at_1000
|
234 |
+
value: 12.559000000000001
|
235 |
+
- type: map_at_3
|
236 |
+
value: 9.386
|
237 |
+
- type: map_at_5
|
238 |
+
value: 10.295
|
239 |
+
- type: mrr_at_1
|
240 |
+
value: 13.941
|
241 |
+
- type: mrr_at_10
|
242 |
+
value: 22.742
|
243 |
+
- type: mrr_at_100
|
244 |
+
value: 23.896
|
245 |
+
- type: mrr_at_1000
|
246 |
+
value: 23.965
|
247 |
+
- type: mrr_at_3
|
248 |
+
value: 19.881
|
249 |
+
- type: mrr_at_5
|
250 |
+
value: 21.555
|
251 |
+
- type: ndcg_at_1
|
252 |
+
value: 13.941
|
253 |
+
- type: ndcg_at_10
|
254 |
+
value: 16.619999999999997
|
255 |
+
- type: ndcg_at_100
|
256 |
+
value: 22.415
|
257 |
+
- type: ndcg_at_1000
|
258 |
+
value: 26.05
|
259 |
+
- type: ndcg_at_3
|
260 |
+
value: 13.148000000000001
|
261 |
+
- type: ndcg_at_5
|
262 |
+
value: 14.433000000000002
|
263 |
+
- type: precision_at_1
|
264 |
+
value: 13.941
|
265 |
+
- type: precision_at_10
|
266 |
+
value: 5.153
|
267 |
+
- type: precision_at_100
|
268 |
+
value: 1.124
|
269 |
+
- type: precision_at_1000
|
270 |
+
value: 0.178
|
271 |
+
- type: precision_at_3
|
272 |
+
value: 9.685
|
273 |
+
- type: precision_at_5
|
274 |
+
value: 7.582999999999999
|
275 |
+
- type: recall_at_1
|
276 |
+
value: 6.524000000000001
|
277 |
+
- type: recall_at_10
|
278 |
+
value: 21.041999999999998
|
279 |
+
- type: recall_at_100
|
280 |
+
value: 41.515
|
281 |
+
- type: recall_at_1000
|
282 |
+
value: 62.507999999999996
|
283 |
+
- type: recall_at_3
|
284 |
+
value: 12.549
|
285 |
+
- type: recall_at_5
|
286 |
+
value: 15.939999999999998
|
287 |
+
- task:
|
288 |
+
type: Retrieval
|
289 |
+
dataset:
|
290 |
+
type: dbpedia-entity
|
291 |
+
name: MTEB DBPedia
|
292 |
+
config: default
|
293 |
+
split: test
|
294 |
+
revision: None
|
295 |
+
metrics:
|
296 |
+
- type: map_at_1
|
297 |
+
value: 6.483
|
298 |
+
- type: map_at_10
|
299 |
+
value: 11.955
|
300 |
+
- type: map_at_100
|
301 |
+
value: 15.470999999999998
|
302 |
+
- type: map_at_1000
|
303 |
+
value: 16.308
|
304 |
+
- type: map_at_3
|
305 |
+
value: 9.292
|
306 |
+
- type: map_at_5
|
307 |
+
value: 10.459
|
308 |
+
- type: mrr_at_1
|
309 |
+
value: 50.74999999999999
|
310 |
+
- type: mrr_at_10
|
311 |
+
value: 58.743
|
312 |
+
- type: mrr_at_100
|
313 |
+
value: 59.41499999999999
|
314 |
+
- type: mrr_at_1000
|
315 |
+
value: 59.431999999999995
|
316 |
+
- type: mrr_at_3
|
317 |
+
value: 56.708000000000006
|
318 |
+
- type: mrr_at_5
|
319 |
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value: 57.80800000000001
|
320 |
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- type: ndcg_at_1
|
321 |
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value: 39.0
|
322 |
+
- type: ndcg_at_10
|
323 |
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value: 26.721
|
324 |
+
- type: ndcg_at_100
|
325 |
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value: 29.366999999999997
|
326 |
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- type: ndcg_at_1000
|
327 |
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value: 35.618
|
328 |
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- type: ndcg_at_3
|
329 |
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value: 31.244
|
330 |
+
- type: ndcg_at_5
|
331 |
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value: 28.614
|
332 |
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- type: precision_at_1
|
333 |
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value: 50.74999999999999
|
334 |
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- type: precision_at_10
|
335 |
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value: 20.45
|
336 |
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- type: precision_at_100
|
337 |
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value: 6.0600000000000005
|
338 |
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- type: precision_at_1000
|
339 |
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value: 1.346
|
340 |
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- type: precision_at_3
|
341 |
+
value: 33.917
|
342 |
+
- type: precision_at_5
|
343 |
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value: 26.950000000000003
|
344 |
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- type: recall_at_1
|
345 |
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value: 6.483
|
346 |
+
- type: recall_at_10
|
347 |
+
value: 16.215
|
348 |
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- type: recall_at_100
|
349 |
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value: 33.382
|
350 |
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- type: recall_at_1000
|
351 |
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value: 54.445
|
352 |
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- type: recall_at_3
|
353 |
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value: 10.6
|
354 |
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- type: recall_at_5
|
355 |
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value: 12.889999999999999
|
356 |
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- task:
|
357 |
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type: Classification
|
358 |
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dataset:
|
359 |
+
type: mteb/emotion
|
360 |
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name: MTEB EmotionClassification
|
361 |
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config: default
|
362 |
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split: test
|
363 |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
364 |
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metrics:
|
365 |
+
- type: accuracy
|
366 |
+
value: 34.39
|
367 |
+
- type: f1
|
368 |
+
value: 31.334865751249474
|
369 |
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- task:
|
370 |
+
type: Retrieval
|
371 |
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dataset:
|
372 |
+
type: fever
|
373 |
+
name: MTEB FEVER
|
374 |
+
config: default
|
375 |
+
split: test
|
376 |
+
revision: None
|
377 |
+
metrics:
|
378 |
+
- type: map_at_1
|
379 |
+
value: 44.698
|
380 |
+
- type: map_at_10
|
381 |
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value: 55.30500000000001
|
382 |
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- type: map_at_100
|
383 |
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value: 55.838
|
384 |
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- type: map_at_1000
|
385 |
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value: 55.87
|
386 |
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- type: map_at_3
|
387 |
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value: 52.884
|
388 |
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- type: map_at_5
|
389 |
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value: 54.352000000000004
|
390 |
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- type: mrr_at_1
|
391 |
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value: 48.32
|
392 |
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- type: mrr_at_10
|
393 |
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value: 59.39
|
394 |
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- type: mrr_at_100
|
395 |
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value: 59.89
|
396 |
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- type: mrr_at_1000
|
397 |
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value: 59.913000000000004
|
398 |
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- type: mrr_at_3
|
399 |
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value: 56.977999999999994
|
400 |
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- type: mrr_at_5
|
401 |
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value: 58.44200000000001
|
402 |
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- type: ndcg_at_1
|
403 |
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value: 48.32
|
404 |
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- type: ndcg_at_10
|
405 |
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value: 61.23800000000001
|
406 |
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- type: ndcg_at_100
|
407 |
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value: 63.79
|
408 |
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- type: ndcg_at_1000
|
409 |
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value: 64.575
|
410 |
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- type: ndcg_at_3
|
411 |
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value: 56.489999999999995
|
412 |
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- type: ndcg_at_5
|
413 |
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value: 59.016999999999996
|
414 |
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- type: precision_at_1
|
415 |
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value: 48.32
|
416 |
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- type: precision_at_10
|
417 |
+
value: 8.288
|
418 |
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- type: precision_at_100
|
419 |
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value: 0.964
|
420 |
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- type: precision_at_1000
|
421 |
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value: 0.104
|
422 |
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- type: precision_at_3
|
423 |
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value: 22.867
|
424 |
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- type: precision_at_5
|
425 |
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value: 15.098
|
426 |
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- type: recall_at_1
|
427 |
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value: 44.698
|
428 |
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- type: recall_at_10
|
429 |
+
value: 75.752
|
430 |
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- type: recall_at_100
|
431 |
+
value: 87.402
|
432 |
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- type: recall_at_1000
|
433 |
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value: 93.316
|
434 |
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- type: recall_at_3
|
435 |
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value: 62.82600000000001
|
436 |
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- type: recall_at_5
|
437 |
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value: 69.01899999999999
|
438 |
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- task:
|
439 |
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type: Retrieval
|
440 |
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dataset:
|
441 |
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type: fiqa
|
442 |
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name: MTEB FiQA2018
|
443 |
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config: default
|
444 |
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split: test
|
445 |
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revision: None
|
446 |
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metrics:
|
447 |
+
- type: map_at_1
|
448 |
+
value: 12.119
|
449 |
+
- type: map_at_10
|
450 |
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value: 20.299
|
451 |
+
- type: map_at_100
|
452 |
+
value: 21.863
|
453 |
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- type: map_at_1000
|
454 |
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value: 22.064
|
455 |
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- type: map_at_3
|
456 |
+
value: 17.485999999999997
|
457 |
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- type: map_at_5
|
458 |
+
value: 19.148
|
459 |
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- type: mrr_at_1
|
460 |
+
value: 24.383
|
461 |
+
- type: mrr_at_10
|
462 |
+
value: 33.074
|
463 |
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- type: mrr_at_100
|
464 |
+
value: 34.03
|
465 |
+
- type: mrr_at_1000
|
466 |
+
value: 34.102
|
467 |
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- type: mrr_at_3
|
468 |
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value: 30.736
|
469 |
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- type: mrr_at_5
|
470 |
+
value: 32.202
|
471 |
+
- type: ndcg_at_1
|
472 |
+
value: 24.383
|
473 |
+
- type: ndcg_at_10
|
474 |
+
value: 26.645999999999997
|
475 |
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- type: ndcg_at_100
|
476 |
+
value: 33.348
|
477 |
+
- type: ndcg_at_1000
|
478 |
+
value: 37.294
|
479 |
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- type: ndcg_at_3
|
480 |
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value: 23.677
|
481 |
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- type: ndcg_at_5
|
482 |
+
value: 24.935
|
483 |
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- type: precision_at_1
|
484 |
+
value: 24.383
|
485 |
+
- type: precision_at_10
|
486 |
+
value: 7.654
|
487 |
+
- type: precision_at_100
|
488 |
+
value: 1.461
|
489 |
+
- type: precision_at_1000
|
490 |
+
value: 0.214
|
491 |
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- type: precision_at_3
|
492 |
+
value: 16.101
|
493 |
+
- type: precision_at_5
|
494 |
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value: 12.222
|
495 |
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- type: recall_at_1
|
496 |
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value: 12.119
|
497 |
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- type: recall_at_10
|
498 |
+
value: 32.531
|
499 |
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- type: recall_at_100
|
500 |
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value: 58.028999999999996
|
501 |
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- type: recall_at_1000
|
502 |
+
value: 82.513
|
503 |
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- type: recall_at_3
|
504 |
+
value: 21.787
|
505 |
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- type: recall_at_5
|
506 |
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value: 27.229999999999997
|
507 |
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- task:
|
508 |
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type: Retrieval
|
509 |
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dataset:
|
510 |
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type: hotpotqa
|
511 |
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name: MTEB HotpotQA
|
512 |
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config: default
|
513 |
+
split: test
|
514 |
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revision: None
|
515 |
+
metrics:
|
516 |
+
- type: map_at_1
|
517 |
+
value: 26.057000000000002
|
518 |
+
- type: map_at_10
|
519 |
+
value: 34.892
|
520 |
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- type: map_at_100
|
521 |
+
value: 35.687000000000005
|
522 |
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- type: map_at_1000
|
523 |
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value: 35.763
|
524 |
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- type: map_at_3
|
525 |
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value: 32.879000000000005
|
526 |
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- type: map_at_5
|
527 |
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value: 34.105000000000004
|
528 |
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- type: mrr_at_1
|
529 |
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value: 52.113
|
530 |
+
- type: mrr_at_10
|
531 |
+
value: 58.940000000000005
|
532 |
+
- type: mrr_at_100
|
533 |
+
value: 59.438
|
534 |
+
- type: mrr_at_1000
|
535 |
+
value: 59.473
|
536 |
+
- type: mrr_at_3
|
537 |
+
value: 57.299
|
538 |
+
- type: mrr_at_5
|
539 |
+
value: 58.353
|
540 |
+
- type: ndcg_at_1
|
541 |
+
value: 52.113
|
542 |
+
- type: ndcg_at_10
|
543 |
+
value: 43.105
|
544 |
+
- type: ndcg_at_100
|
545 |
+
value: 46.44
|
546 |
+
- type: ndcg_at_1000
|
547 |
+
value: 48.241
|
548 |
+
- type: ndcg_at_3
|
549 |
+
value: 39.566
|
550 |
+
- type: ndcg_at_5
|
551 |
+
value: 41.508
|
552 |
+
- type: precision_at_1
|
553 |
+
value: 52.113
|
554 |
+
- type: precision_at_10
|
555 |
+
value: 8.892999999999999
|
556 |
+
- type: precision_at_100
|
557 |
+
value: 1.1520000000000001
|
558 |
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- type: precision_at_1000
|
559 |
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value: 0.13899999999999998
|
560 |
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- type: precision_at_3
|
561 |
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value: 24.398
|
562 |
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- type: precision_at_5
|
563 |
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value: 16.181
|
564 |
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- type: recall_at_1
|
565 |
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value: 26.057000000000002
|
566 |
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- type: recall_at_10
|
567 |
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value: 44.463
|
568 |
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- type: recall_at_100
|
569 |
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value: 57.616
|
570 |
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- type: recall_at_1000
|
571 |
+
value: 69.65599999999999
|
572 |
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- type: recall_at_3
|
573 |
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value: 36.597
|
574 |
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- type: recall_at_5
|
575 |
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value: 40.452
|
576 |
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- task:
|
577 |
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type: Classification
|
578 |
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dataset:
|
579 |
+
type: mteb/imdb
|
580 |
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name: MTEB ImdbClassification
|
581 |
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config: default
|
582 |
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split: test
|
583 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
584 |
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metrics:
|
585 |
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- type: accuracy
|
586 |
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value: 58.268399999999986
|
587 |
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- type: ap
|
588 |
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value: 55.03852332714837
|
589 |
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- type: f1
|
590 |
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value: 57.23656436062262
|
591 |
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- task:
|
592 |
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type: Retrieval
|
593 |
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dataset:
|
594 |
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type: msmarco
|
595 |
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name: MTEB MSMARCO
|
596 |
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config: default
|
597 |
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split: dev
|
598 |
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revision: None
|
599 |
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metrics:
|
600 |
+
- type: map_at_1
|
601 |
+
value: 14.273
|
602 |
+
- type: map_at_10
|
603 |
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value: 23.953
|
604 |
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- type: map_at_100
|
605 |
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value: 25.207
|
606 |
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- type: map_at_1000
|
607 |
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value: 25.285999999999998
|
608 |
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- type: map_at_3
|
609 |
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value: 20.727
|
610 |
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- type: map_at_5
|
611 |
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value: 22.492
|
612 |
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- type: mrr_at_1
|
613 |
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value: 14.685
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614 |
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- type: mrr_at_10
|
615 |
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value: 24.423000000000002
|
616 |
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- type: mrr_at_100
|
617 |
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value: 25.64
|
618 |
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- type: mrr_at_1000
|
619 |
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value: 25.713
|
620 |
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- type: mrr_at_3
|
621 |
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value: 21.213
|
622 |
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- type: mrr_at_5
|
623 |
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value: 22.979
|
624 |
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- type: ndcg_at_1
|
625 |
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value: 14.685
|
626 |
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- type: ndcg_at_10
|
627 |
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value: 29.698
|
628 |
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- type: ndcg_at_100
|
629 |
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value: 36.010999999999996
|
630 |
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- type: ndcg_at_1000
|
631 |
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value: 38.102999999999994
|
632 |
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- type: ndcg_at_3
|
633 |
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value: 23.0
|
634 |
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- type: ndcg_at_5
|
635 |
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value: 26.186
|
636 |
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- type: precision_at_1
|
637 |
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value: 14.685
|
638 |
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- type: precision_at_10
|
639 |
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value: 4.954
|
640 |
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- type: precision_at_100
|
641 |
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value: 0.815
|
642 |
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- type: precision_at_1000
|
643 |
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value: 0.099
|
644 |
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- type: precision_at_3
|
645 |
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value: 10.038
|
646 |
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- type: precision_at_5
|
647 |
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value: 7.636
|
648 |
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- type: recall_at_1
|
649 |
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value: 14.273
|
650 |
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- type: recall_at_10
|
651 |
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value: 47.559000000000005
|
652 |
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- type: recall_at_100
|
653 |
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value: 77.375
|
654 |
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- type: recall_at_1000
|
655 |
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value: 93.616
|
656 |
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- type: recall_at_3
|
657 |
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value: 29.110999999999997
|
658 |
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- type: recall_at_5
|
659 |
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value: 36.825
|
660 |
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- task:
|
661 |
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type: Classification
|
662 |
+
dataset:
|
663 |
+
type: mteb/mtop_domain
|
664 |
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name: MTEB MTOPDomainClassification (en)
|
665 |
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config: en
|
666 |
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split: test
|
667 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
668 |
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metrics:
|
669 |
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- type: accuracy
|
670 |
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value: 89.85636114911081
|
671 |
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- type: f1
|
672 |
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value: 89.65403786390279
|
673 |
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- task:
|
674 |
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type: Classification
|
675 |
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dataset:
|
676 |
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type: mteb/mtop_intent
|
677 |
+
name: MTEB MTOPIntentClassification (en)
|
678 |
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config: en
|
679 |
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split: test
|
680 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
681 |
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metrics:
|
682 |
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- type: accuracy
|
683 |
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value: 59.03784769721842
|
684 |
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- type: f1
|
685 |
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value: 42.57604111096128
|
686 |
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- task:
|
687 |
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type: Classification
|
688 |
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dataset:
|
689 |
+
type: mteb/amazon_massive_intent
|
690 |
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name: MTEB MassiveIntentClassification (en)
|
691 |
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config: en
|
692 |
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split: test
|
693 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
694 |
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metrics:
|
695 |
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- type: accuracy
|
696 |
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value: 65.00336247478144
|
697 |
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- type: f1
|
698 |
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value: 63.12578076844032
|
699 |
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- task:
|
700 |
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type: Classification
|
701 |
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dataset:
|
702 |
+
type: mteb/amazon_massive_scenario
|
703 |
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name: MTEB MassiveScenarioClassification (en)
|
704 |
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config: en
|
705 |
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split: test
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706 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
707 |
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metrics:
|
708 |
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- type: accuracy
|
709 |
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value: 72.14862138533962
|
710 |
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- type: f1
|
711 |
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value: 71.91174720216141
|
712 |
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- task:
|
713 |
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type: Clustering
|
714 |
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dataset:
|
715 |
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type: mteb/medrxiv-clustering-p2p
|
716 |
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name: MTEB MedrxivClusteringP2P
|
717 |
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config: default
|
718 |
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split: test
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719 |
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revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
720 |
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metrics:
|
721 |
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- type: v_measure
|
722 |
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value: 28.259326082067094
|
723 |
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- task:
|
724 |
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type: Clustering
|
725 |
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dataset:
|
726 |
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type: mteb/medrxiv-clustering-s2s
|
727 |
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name: MTEB MedrxivClusteringS2S
|
728 |
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config: default
|
729 |
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split: test
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730 |
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revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
731 |
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metrics:
|
732 |
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- type: v_measure
|
733 |
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value: 23.874256261395775
|
734 |
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- task:
|
735 |
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type: Reranking
|
736 |
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dataset:
|
737 |
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type: mteb/mind_small
|
738 |
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name: MTEB MindSmallReranking
|
739 |
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config: default
|
740 |
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split: test
|
741 |
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revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
742 |
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metrics:
|
743 |
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- type: map
|
744 |
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value: 29.251614283788385
|
745 |
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- type: mrr
|
746 |
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value: 29.9695581475798
|
747 |
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- task:
|
748 |
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type: Retrieval
|
749 |
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dataset:
|
750 |
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type: nfcorpus
|
751 |
+
name: MTEB NFCorpus
|
752 |
+
config: default
|
753 |
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split: test
|
754 |
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revision: None
|
755 |
+
metrics:
|
756 |
+
- type: map_at_1
|
757 |
+
value: 3.9309999999999996
|
758 |
+
- type: map_at_10
|
759 |
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value: 8.472
|
760 |
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- type: map_at_100
|
761 |
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value: 10.461
|
762 |
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- type: map_at_1000
|
763 |
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value: 11.588
|
764 |
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- type: map_at_3
|
765 |
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value: 6.343999999999999
|
766 |
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- type: map_at_5
|
767 |
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value: 7.379
|
768 |
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- type: mrr_at_1
|
769 |
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value: 35.913000000000004
|
770 |
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- type: mrr_at_10
|
771 |
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value: 43.91
|
772 |
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- type: mrr_at_100
|
773 |
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value: 44.519999999999996
|
774 |
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- type: mrr_at_1000
|
775 |
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value: 44.59
|
776 |
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- type: mrr_at_3
|
777 |
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value: 41.589
|
778 |
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- type: mrr_at_5
|
779 |
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value: 42.626
|
780 |
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- type: ndcg_at_1
|
781 |
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value: 34.52
|
782 |
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- type: ndcg_at_10
|
783 |
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value: 25.128
|
784 |
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- type: ndcg_at_100
|
785 |
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value: 22.917
|
786 |
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- type: ndcg_at_1000
|
787 |
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value: 31.64
|
788 |
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- type: ndcg_at_3
|
789 |
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value: 29.866999999999997
|
790 |
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- type: ndcg_at_5
|
791 |
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value: 27.494000000000003
|
792 |
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- type: precision_at_1
|
793 |
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value: 35.913000000000004
|
794 |
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- type: precision_at_10
|
795 |
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value: 18.607000000000003
|
796 |
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- type: precision_at_100
|
797 |
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value: 6.006
|
798 |
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- type: precision_at_1000
|
799 |
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value: 1.814
|
800 |
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- type: precision_at_3
|
801 |
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value: 28.277
|
802 |
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- type: precision_at_5
|
803 |
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value: 23.777
|
804 |
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- type: recall_at_1
|
805 |
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value: 3.9309999999999996
|
806 |
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- type: recall_at_10
|
807 |
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value: 11.684
|
808 |
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- type: recall_at_100
|
809 |
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value: 24.212
|
810 |
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- type: recall_at_1000
|
811 |
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value: 55.36
|
812 |
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- type: recall_at_3
|
813 |
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value: 7.329
|
814 |
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- type: recall_at_5
|
815 |
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value: 9.059000000000001
|
816 |
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- task:
|
817 |
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type: Retrieval
|
818 |
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dataset:
|
819 |
+
type: nq
|
820 |
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name: MTEB NQ
|
821 |
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config: default
|
822 |
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split: test
|
823 |
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revision: None
|
824 |
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metrics:
|
825 |
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- type: map_at_1
|
826 |
+
value: 19.03
|
827 |
+
- type: map_at_10
|
828 |
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value: 30.990000000000002
|
829 |
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- type: map_at_100
|
830 |
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value: 32.211
|
831 |
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- type: map_at_1000
|
832 |
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value: 32.267
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833 |
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- type: map_at_3
|
834 |
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value: 26.833000000000002
|
835 |
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- type: map_at_5
|
836 |
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value: 29.128
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837 |
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- type: mrr_at_1
|
838 |
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value: 21.523999999999997
|
839 |
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- type: mrr_at_10
|
840 |
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value: 33.085
|
841 |
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- type: mrr_at_100
|
842 |
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value: 34.096
|
843 |
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- type: mrr_at_1000
|
844 |
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value: 34.139
|
845 |
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- type: mrr_at_3
|
846 |
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value: 29.354999999999997
|
847 |
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- type: mrr_at_5
|
848 |
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value: 31.441999999999997
|
849 |
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- type: ndcg_at_1
|
850 |
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value: 21.495
|
851 |
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- type: ndcg_at_10
|
852 |
+
value: 37.971
|
853 |
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- type: ndcg_at_100
|
854 |
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value: 43.492999999999995
|
855 |
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- type: ndcg_at_1000
|
856 |
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value: 44.925
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857 |
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- type: ndcg_at_3
|
858 |
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value: 29.808
|
859 |
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- type: ndcg_at_5
|
860 |
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value: 33.748
|
861 |
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- type: precision_at_1
|
862 |
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value: 21.495
|
863 |
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- type: precision_at_10
|
864 |
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value: 6.819
|
865 |
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- type: precision_at_100
|
866 |
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value: 0.991
|
867 |
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- type: precision_at_1000
|
868 |
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value: 0.11299999999999999
|
869 |
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- type: precision_at_3
|
870 |
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value: 13.886000000000001
|
871 |
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- type: precision_at_5
|
872 |
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value: 10.574
|
873 |
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- type: recall_at_1
|
874 |
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value: 19.03
|
875 |
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- type: recall_at_10
|
876 |
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value: 57.493
|
877 |
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- type: recall_at_100
|
878 |
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value: 82.03200000000001
|
879 |
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- type: recall_at_1000
|
880 |
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value: 92.879
|
881 |
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- type: recall_at_3
|
882 |
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value: 35.899
|
883 |
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- type: recall_at_5
|
884 |
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value: 45.092
|
885 |
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- task:
|
886 |
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type: Retrieval
|
887 |
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dataset:
|
888 |
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type: quora
|
889 |
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name: MTEB QuoraRetrieval
|
890 |
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config: default
|
891 |
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split: test
|
892 |
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revision: None
|
893 |
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metrics:
|
894 |
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- type: map_at_1
|
895 |
+
value: 67.97
|
896 |
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- type: map_at_10
|
897 |
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value: 81.478
|
898 |
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- type: map_at_100
|
899 |
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value: 82.147
|
900 |
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- type: map_at_1000
|
901 |
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value: 82.172
|
902 |
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- type: map_at_3
|
903 |
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value: 78.456
|
904 |
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- type: map_at_5
|
905 |
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value: 80.337
|
906 |
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- type: mrr_at_1
|
907 |
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value: 78.24
|
908 |
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- type: mrr_at_10
|
909 |
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value: 84.941
|
910 |
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- type: mrr_at_100
|
911 |
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value: 85.08099999999999
|
912 |
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- type: mrr_at_1000
|
913 |
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value: 85.083
|
914 |
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- type: mrr_at_3
|
915 |
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value: 83.743
|
916 |
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- type: mrr_at_5
|
917 |
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value: 84.553
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918 |
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- type: ndcg_at_1
|
919 |
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value: 78.24
|
920 |
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- type: ndcg_at_10
|
921 |
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value: 85.61999999999999
|
922 |
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- type: ndcg_at_100
|
923 |
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value: 87.113
|
924 |
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- type: ndcg_at_1000
|
925 |
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value: 87.318
|
926 |
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- type: ndcg_at_3
|
927 |
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value: 82.403
|
928 |
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- type: ndcg_at_5
|
929 |
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value: 84.15700000000001
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930 |
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- type: precision_at_1
|
931 |
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value: 78.24
|
932 |
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- type: precision_at_10
|
933 |
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value: 12.979
|
934 |
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- type: precision_at_100
|
935 |
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value: 1.503
|
936 |
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- type: precision_at_1000
|
937 |
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value: 0.156
|
938 |
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- type: precision_at_3
|
939 |
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value: 35.9
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940 |
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- type: precision_at_5
|
941 |
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value: 23.704
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942 |
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- type: recall_at_1
|
943 |
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value: 67.97
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944 |
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- type: recall_at_10
|
945 |
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value: 93.563
|
946 |
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- type: recall_at_100
|
947 |
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value: 98.834
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948 |
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- type: recall_at_1000
|
949 |
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value: 99.901
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950 |
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- type: recall_at_3
|
951 |
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value: 84.319
|
952 |
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- type: recall_at_5
|
953 |
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value: 89.227
|
954 |
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- task:
|
955 |
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type: Clustering
|
956 |
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dataset:
|
957 |
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type: mteb/reddit-clustering
|
958 |
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name: MTEB RedditClustering
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959 |
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config: default
|
960 |
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split: test
|
961 |
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revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
962 |
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metrics:
|
963 |
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- type: v_measure
|
964 |
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value: 35.853649010160694
|
965 |
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- task:
|
966 |
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type: Clustering
|
967 |
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dataset:
|
968 |
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type: mteb/reddit-clustering-p2p
|
969 |
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name: MTEB RedditClusteringP2P
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970 |
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config: default
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971 |
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split: test
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972 |
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revision: 282350215ef01743dc01b456c7f5241fa8937f16
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973 |
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metrics:
|
974 |
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- type: v_measure
|
975 |
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value: 47.270443152349415
|
976 |
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- task:
|
977 |
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type: Retrieval
|
978 |
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dataset:
|
979 |
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type: scidocs
|
980 |
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name: MTEB SCIDOCS
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981 |
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config: default
|
982 |
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split: test
|
983 |
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revision: None
|
984 |
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metrics:
|
985 |
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- type: map_at_1
|
986 |
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value: 3.803
|
987 |
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- type: map_at_10
|
988 |
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value: 8.790000000000001
|
989 |
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- type: map_at_100
|
990 |
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value: 10.313
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991 |
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- type: map_at_1000
|
992 |
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value: 10.562000000000001
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993 |
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- type: map_at_3
|
994 |
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value: 6.483
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995 |
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- type: map_at_5
|
996 |
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value: 7.591
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997 |
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- type: mrr_at_1
|
998 |
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value: 18.7
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999 |
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- type: mrr_at_10
|
1000 |
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value: 27.349
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1001 |
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- type: mrr_at_100
|
1002 |
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value: 28.474
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1003 |
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- type: mrr_at_1000
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1004 |
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value: 28.544999999999998
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1005 |
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- type: mrr_at_3
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1006 |
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value: 24.567
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1007 |
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- type: mrr_at_5
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1008 |
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value: 26.172
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1009 |
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- type: ndcg_at_1
|
1010 |
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value: 18.7
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1011 |
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- type: ndcg_at_10
|
1012 |
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value: 15.155
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1013 |
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- type: ndcg_at_100
|
1014 |
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value: 21.63
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1015 |
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- type: ndcg_at_1000
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1016 |
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value: 26.595999999999997
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1017 |
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- type: ndcg_at_3
|
1018 |
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value: 14.706
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1019 |
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- type: ndcg_at_5
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1020 |
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value: 12.681999999999999
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1021 |
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- type: precision_at_1
|
1022 |
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value: 18.7
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1023 |
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- type: precision_at_10
|
1024 |
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value: 7.6899999999999995
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1025 |
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- type: precision_at_100
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1026 |
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value: 1.7080000000000002
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1027 |
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- type: precision_at_1000
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1028 |
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value: 0.291
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1029 |
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- type: precision_at_3
|
1030 |
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value: 13.567000000000002
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1031 |
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- type: precision_at_5
|
1032 |
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value: 10.9
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1033 |
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- type: recall_at_1
|
1034 |
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value: 3.803
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1035 |
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- type: recall_at_10
|
1036 |
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value: 15.607
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1037 |
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- type: recall_at_100
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1038 |
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value: 34.717999999999996
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1039 |
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- type: recall_at_1000
|
1040 |
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value: 59.150000000000006
|
1041 |
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- type: recall_at_3
|
1042 |
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value: 8.258000000000001
|
1043 |
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- type: recall_at_5
|
1044 |
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value: 11.063
|
1045 |
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- task:
|
1046 |
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type: STS
|
1047 |
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dataset:
|
1048 |
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type: mteb/sickr-sts
|
1049 |
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name: MTEB SICK-R
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1050 |
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config: default
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1051 |
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split: test
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1052 |
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revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1053 |
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metrics:
|
1054 |
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- type: cos_sim_pearson
|
1055 |
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value: 81.05755556071047
|
1056 |
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- type: cos_sim_spearman
|
1057 |
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value: 72.44408263672771
|
1058 |
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- type: euclidean_pearson
|
1059 |
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value: 71.65314814604668
|
1060 |
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- type: euclidean_spearman
|
1061 |
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value: 65.1833695751109
|
1062 |
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- type: manhattan_pearson
|
1063 |
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value: 71.81874115177355
|
1064 |
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- type: manhattan_spearman
|
1065 |
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value: 65.45940792270201
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1066 |
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- task:
|
1067 |
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type: STS
|
1068 |
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dataset:
|
1069 |
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type: mteb/sts12-sts
|
1070 |
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name: MTEB STS12
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1071 |
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config: default
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1072 |
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split: test
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1073 |
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revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1074 |
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metrics:
|
1075 |
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- type: cos_sim_pearson
|
1076 |
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value: 81.75836272926722
|
1077 |
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- type: cos_sim_spearman
|
1078 |
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value: 73.63905703662927
|
1079 |
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- type: euclidean_pearson
|
1080 |
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value: 67.58539517215293
|
1081 |
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- type: euclidean_spearman
|
1082 |
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value: 58.88440181413321
|
1083 |
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- type: manhattan_pearson
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1084 |
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value: 66.56872028174024
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1085 |
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- type: manhattan_spearman
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1086 |
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value: 58.48195528793699
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1087 |
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- task:
|
1088 |
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1089 |
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dataset:
|
1090 |
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type: mteb/sts13-sts
|
1091 |
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1092 |
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1093 |
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split: test
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1094 |
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revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
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1095 |
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metrics:
|
1096 |
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- type: cos_sim_pearson
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1097 |
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value: 76.58680032464127
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1098 |
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- type: cos_sim_spearman
|
1099 |
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value: 78.03760988363273
|
1100 |
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- type: euclidean_pearson
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1101 |
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value: 68.23192805876019
|
1102 |
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- type: euclidean_spearman
|
1103 |
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value: 69.21753515532978
|
1104 |
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- type: manhattan_pearson
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1105 |
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value: 68.07876685109447
|
1106 |
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- type: manhattan_spearman
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1107 |
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value: 69.08026107263751
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1108 |
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- task:
|
1109 |
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type: STS
|
1110 |
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dataset:
|
1111 |
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type: mteb/sts14-sts
|
1112 |
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name: MTEB STS14
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1113 |
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1114 |
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split: test
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1115 |
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revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
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1116 |
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metrics:
|
1117 |
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1118 |
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value: 78.72357139489792
|
1119 |
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- type: cos_sim_spearman
|
1120 |
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value: 74.53681843472086
|
1121 |
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- type: euclidean_pearson
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1122 |
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1123 |
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1124 |
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value: 63.81392957525887
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1125 |
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- type: manhattan_pearson
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1126 |
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value: 66.33322201893088
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1127 |
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- type: manhattan_spearman
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1128 |
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value: 63.55218357111819
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1129 |
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- task:
|
1130 |
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type: STS
|
1131 |
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dataset:
|
1132 |
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type: mteb/sts15-sts
|
1133 |
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1134 |
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|
1135 |
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split: test
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1136 |
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1137 |
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metrics:
|
1138 |
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1139 |
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value: 82.62456549757793
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1140 |
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- type: cos_sim_spearman
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1141 |
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value: 83.89301877076606
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1142 |
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- type: euclidean_pearson
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1143 |
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value: 58.128415035981554
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1144 |
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- type: euclidean_spearman
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1145 |
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1146 |
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- type: manhattan_pearson
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1147 |
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value: 58.37634990795807
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1148 |
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- type: manhattan_spearman
|
1149 |
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value: 58.89541748905865
|
1150 |
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- task:
|
1151 |
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|
1152 |
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dataset:
|
1153 |
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|
1154 |
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|
1155 |
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|
1156 |
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split: test
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1157 |
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|
1158 |
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metrics:
|
1159 |
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|
1160 |
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value: 76.79731685895317
|
1161 |
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- type: cos_sim_spearman
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1162 |
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value: 79.04240201103201
|
1163 |
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- type: euclidean_pearson
|
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|
1172 |
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|
1174 |
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1175 |
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name: MTEB STS17 (en-en)
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config: en-en
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1180 |
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value: 86.30962737077412
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1191 |
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|
1193 |
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type: STS
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1194 |
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dataset:
|
1195 |
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1196 |
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1197 |
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1200 |
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|
1201 |
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1203 |
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|
1214 |
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|
1215 |
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dataset:
|
1216 |
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1217 |
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1221 |
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|
1222 |
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1223 |
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1224 |
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- type: cos_sim_spearman
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|
1235 |
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type: Reranking
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1236 |
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dataset:
|
1237 |
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1238 |
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1239 |
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1240 |
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|
1243 |
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- type: map
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1244 |
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- task:
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1248 |
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1249 |
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|
1250 |
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1251 |
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name: MTEB SciFact
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1252 |
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config: default
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1253 |
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split: test
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1254 |
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revision: None
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1255 |
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|
1256 |
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1257 |
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value: 39.983000000000004
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1258 |
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- type: precision_at_1000
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1299 |
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value: 0.108
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1300 |
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- type: precision_at_3
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1301 |
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value: 19.444
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1302 |
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- type: precision_at_5
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1303 |
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value: 13.067
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1304 |
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- type: recall_at_1
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1305 |
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value: 39.983000000000004
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1306 |
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- type: recall_at_10
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1307 |
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value: 66.333
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1309 |
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value: 80.256
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1310 |
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- type: recall_at_1000
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1311 |
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value: 95.667
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1312 |
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1313 |
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value: 53.449999999999996
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1314 |
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- type: recall_at_5
|
1315 |
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value: 58.989000000000004
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1316 |
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- task:
|
1317 |
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type: PairClassification
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1318 |
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dataset:
|
1319 |
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type: mteb/sprintduplicatequestions-pairclassification
|
1320 |
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name: MTEB SprintDuplicateQuestions
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1321 |
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config: default
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1322 |
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split: test
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1323 |
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revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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1324 |
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metrics:
|
1325 |
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- type: cos_sim_accuracy
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1326 |
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value: 99.6930693069307
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1327 |
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- type: cos_sim_ap
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1330 |
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1331 |
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1332 |
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1333 |
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- type: cos_sim_recall
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1334 |
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value: 84.2
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1335 |
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- type: dot_accuracy
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1336 |
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1337 |
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1338 |
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1339 |
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- type: dot_f1
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1341 |
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- type: dot_precision
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1342 |
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1343 |
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- type: dot_recall
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1344 |
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value: 52.800000000000004
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1345 |
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- type: euclidean_accuracy
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1346 |
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value: 99.55049504950495
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1347 |
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- type: euclidean_ap
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1348 |
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1349 |
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- type: euclidean_f1
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1350 |
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value: 74.54645409565696
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1351 |
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- type: euclidean_precision
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1352 |
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value: 82.78388278388277
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1353 |
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- type: euclidean_recall
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1354 |
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value: 67.80000000000001
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1355 |
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- type: manhattan_accuracy
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1356 |
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value: 99.54257425742574
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1357 |
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- type: manhattan_ap
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1358 |
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1359 |
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- type: manhattan_f1
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1361 |
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- type: manhattan_precision
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1362 |
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1363 |
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- type: manhattan_recall
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1364 |
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value: 67.4
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1365 |
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- type: max_accuracy
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1366 |
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value: 99.6930693069307
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1367 |
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1368 |
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1369 |
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- type: max_f1
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1370 |
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1371 |
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- task:
|
1372 |
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type: Clustering
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1373 |
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dataset:
|
1374 |
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type: mteb/stackexchange-clustering
|
1375 |
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name: MTEB StackExchangeClustering
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1376 |
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config: default
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1377 |
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split: test
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1378 |
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1379 |
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metrics:
|
1380 |
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- type: v_measure
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1381 |
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value: 47.81120799399627
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1382 |
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- task:
|
1383 |
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type: Clustering
|
1384 |
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dataset:
|
1385 |
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type: mteb/stackexchange-clustering-p2p
|
1386 |
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name: MTEB StackExchangeClusteringP2P
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1387 |
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1388 |
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1389 |
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1390 |
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metrics:
|
1391 |
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- type: v_measure
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1392 |
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1393 |
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- task:
|
1394 |
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|
1395 |
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dataset:
|
1396 |
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type: mteb/stackoverflowdupquestions-reranking
|
1397 |
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name: MTEB StackOverflowDupQuestions
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1398 |
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1399 |
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1400 |
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1401 |
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metrics:
|
1402 |
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1403 |
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1404 |
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1405 |
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1406 |
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- task:
|
1407 |
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1408 |
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dataset:
|
1409 |
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1410 |
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1411 |
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1413 |
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1414 |
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metrics:
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1415 |
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value: 30.09237795780992
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1417 |
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1421 |
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1423 |
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- task:
|
1424 |
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1425 |
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dataset:
|
1426 |
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type: trec-covid
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1427 |
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name: MTEB TRECCOVID
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1428 |
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1429 |
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split: test
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1430 |
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revision: None
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1431 |
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metrics:
|
1432 |
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1433 |
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value: 0.169
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1434 |
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1435 |
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1436 |
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1437 |
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1438 |
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1440 |
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1441 |
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1442 |
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1443 |
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1447 |
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1448 |
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1454 |
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1455 |
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1456 |
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1459 |
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1460 |
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1461 |
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1462 |
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1463 |
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1464 |
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1465 |
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1466 |
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1467 |
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1468 |
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1469 |
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1470 |
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1471 |
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1472 |
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1473 |
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1474 |
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1475 |
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1476 |
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1477 |
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1478 |
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1479 |
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value: 60.4
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1480 |
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1481 |
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value: 0.169
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1482 |
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1483 |
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1488 |
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1489 |
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value: 0.532
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1490 |
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1491 |
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value: 0.777
|
1492 |
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- task:
|
1493 |
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type: Retrieval
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1494 |
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dataset:
|
1495 |
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type: webis-touche2020
|
1496 |
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name: MTEB Touche2020
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1497 |
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config: default
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1498 |
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1499 |
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revision: None
|
1500 |
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metrics:
|
1501 |
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|
1502 |
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value: 2.018
|
1503 |
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1504 |
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value: 8.036
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1505 |
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1511 |
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1512 |
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1513 |
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1514 |
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1515 |
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1517 |
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1518 |
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1519 |
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1520 |
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1521 |
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1522 |
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1523 |
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1524 |
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1525 |
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1529 |
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1530 |
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1531 |
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1532 |
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1533 |
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1534 |
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1535 |
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1536 |
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1537 |
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1538 |
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1539 |
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1540 |
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1541 |
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1543 |
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1547 |
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1548 |
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1549 |
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1550 |
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1551 |
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1554 |
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1555 |
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1556 |
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1557 |
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1558 |
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value: 4.884
|
1559 |
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- type: recall_at_5
|
1560 |
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value: 8.203000000000001
|
1561 |
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- task:
|
1562 |
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type: Classification
|
1563 |
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dataset:
|
1564 |
+
type: mteb/toxic_conversations_50k
|
1565 |
+
name: MTEB ToxicConversationsClassification
|
1566 |
+
config: default
|
1567 |
+
split: test
|
1568 |
+
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
1569 |
+
metrics:
|
1570 |
+
- type: accuracy
|
1571 |
+
value: 59.69140000000001
|
1572 |
+
- type: ap
|
1573 |
+
value: 10.299275820958274
|
1574 |
+
- type: f1
|
1575 |
+
value: 45.697311005218154
|
1576 |
+
- task:
|
1577 |
+
type: Classification
|
1578 |
+
dataset:
|
1579 |
+
type: mteb/tweet_sentiment_extraction
|
1580 |
+
name: MTEB TweetSentimentExtractionClassification
|
1581 |
+
config: default
|
1582 |
+
split: test
|
1583 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
1584 |
+
metrics:
|
1585 |
+
- type: accuracy
|
1586 |
+
value: 53.542727787209955
|
1587 |
+
- type: f1
|
1588 |
+
value: 53.59495510018717
|
1589 |
+
- task:
|
1590 |
+
type: Clustering
|
1591 |
+
dataset:
|
1592 |
+
type: mteb/twentynewsgroups-clustering
|
1593 |
+
name: MTEB TwentyNewsgroupsClustering
|
1594 |
+
config: default
|
1595 |
+
split: test
|
1596 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
1597 |
+
metrics:
|
1598 |
+
- type: v_measure
|
1599 |
+
value: 32.405659957745534
|
1600 |
+
- task:
|
1601 |
+
type: PairClassification
|
1602 |
+
dataset:
|
1603 |
+
type: mteb/twittersemeval2015-pairclassification
|
1604 |
+
name: MTEB TwitterSemEval2015
|
1605 |
+
config: default
|
1606 |
+
split: test
|
1607 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
1608 |
+
metrics:
|
1609 |
+
- type: cos_sim_accuracy
|
1610 |
+
value: 82.34487691482386
|
1611 |
+
- type: cos_sim_ap
|
1612 |
+
value: 61.4880638625752
|
1613 |
+
- type: cos_sim_f1
|
1614 |
+
value: 59.350775193798455
|
1615 |
+
- type: cos_sim_precision
|
1616 |
+
value: 54.858934169278996
|
1617 |
+
- type: cos_sim_recall
|
1618 |
+
value: 64.64379947229551
|
1619 |
+
- type: dot_accuracy
|
1620 |
+
value: 77.68373368301842
|
1621 |
+
- type: dot_ap
|
1622 |
+
value: 36.846940578266626
|
1623 |
+
- type: dot_f1
|
1624 |
+
value: 42.67407473787974
|
1625 |
+
- type: dot_precision
|
1626 |
+
value: 32.311032704573215
|
1627 |
+
- type: dot_recall
|
1628 |
+
value: 62.82321899736147
|
1629 |
+
- type: euclidean_accuracy
|
1630 |
+
value: 80.40770101925256
|
1631 |
+
- type: euclidean_ap
|
1632 |
+
value: 53.51906185864526
|
1633 |
+
- type: euclidean_f1
|
1634 |
+
value: 53.24030024315466
|
1635 |
+
- type: euclidean_precision
|
1636 |
+
value: 44.41700476274475
|
1637 |
+
- type: euclidean_recall
|
1638 |
+
value: 66.43799472295514
|
1639 |
+
- type: manhattan_accuracy
|
1640 |
+
value: 80.31829290099542
|
1641 |
+
- type: manhattan_ap
|
1642 |
+
value: 53.67183195163967
|
1643 |
+
- type: manhattan_f1
|
1644 |
+
value: 53.28358208955224
|
1645 |
+
- type: manhattan_precision
|
1646 |
+
value: 44.70483005366726
|
1647 |
+
- type: manhattan_recall
|
1648 |
+
value: 65.93667546174143
|
1649 |
+
- type: max_accuracy
|
1650 |
+
value: 82.34487691482386
|
1651 |
+
- type: max_ap
|
1652 |
+
value: 61.4880638625752
|
1653 |
+
- type: max_f1
|
1654 |
+
value: 59.350775193798455
|
1655 |
+
- task:
|
1656 |
+
type: PairClassification
|
1657 |
+
dataset:
|
1658 |
+
type: mteb/twitterurlcorpus-pairclassification
|
1659 |
+
name: MTEB TwitterURLCorpus
|
1660 |
+
config: default
|
1661 |
+
split: test
|
1662 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
1663 |
+
metrics:
|
1664 |
+
- type: cos_sim_accuracy
|
1665 |
+
value: 87.71684713005007
|
1666 |
+
- type: cos_sim_ap
|
1667 |
+
value: 82.85441942604702
|
1668 |
+
- type: cos_sim_f1
|
1669 |
+
value: 75.69942543843179
|
1670 |
+
- type: cos_sim_precision
|
1671 |
+
value: 73.88754490140019
|
1672 |
+
- type: cos_sim_recall
|
1673 |
+
value: 77.60240221743148
|
1674 |
+
- type: dot_accuracy
|
1675 |
+
value: 82.23696976753212
|
1676 |
+
- type: dot_ap
|
1677 |
+
value: 68.47562727147806
|
1678 |
+
- type: dot_f1
|
1679 |
+
value: 64.99698249849123
|
1680 |
+
- type: dot_precision
|
1681 |
+
value: 57.566219265946074
|
1682 |
+
- type: dot_recall
|
1683 |
+
value: 74.63042808746535
|
1684 |
+
- type: euclidean_accuracy
|
1685 |
+
value: 81.52481856638336
|
1686 |
+
- type: euclidean_ap
|
1687 |
+
value: 65.96678666430529
|
1688 |
+
- type: euclidean_f1
|
1689 |
+
value: 59.14671467146715
|
1690 |
+
- type: euclidean_precision
|
1691 |
+
value: 55.54879285859201
|
1692 |
+
- type: euclidean_recall
|
1693 |
+
value: 63.24299353249153
|
1694 |
+
- type: manhattan_accuracy
|
1695 |
+
value: 81.56750882912253
|
1696 |
+
- type: manhattan_ap
|
1697 |
+
value: 66.07646774834106
|
1698 |
+
- type: manhattan_f1
|
1699 |
+
value: 59.161485036907756
|
1700 |
+
- type: manhattan_precision
|
1701 |
+
value: 56.05319368841728
|
1702 |
+
- type: manhattan_recall
|
1703 |
+
value: 62.634739759778256
|
1704 |
+
- type: max_accuracy
|
1705 |
+
value: 87.71684713005007
|
1706 |
+
- type: max_ap
|
1707 |
+
value: 82.85441942604702
|
1708 |
+
- type: max_f1
|
1709 |
+
value: 75.69942543843179
|
1710 |
+
---
|
1711 |
---
|
1712 |
|
1713 |
<br><br>
|