Update README.md
Browse files
README.md
CHANGED
@@ -8,6 +8,1705 @@ 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>
|
|
|
8 |
- jinaai/negation-dataset
|
9 |
language: en
|
10 |
license: apache-2.0
|
11 |
+
model-index:
|
12 |
+
- name: jina-embedding-b-en-v1
|
13 |
+
results:
|
14 |
+
- task:
|
15 |
+
type: Classification
|
16 |
+
dataset:
|
17 |
+
type: mteb/amazon_counterfactual
|
18 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
19 |
+
config: en
|
20 |
+
split: test
|
21 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
22 |
+
metrics:
|
23 |
+
- type: accuracy
|
24 |
+
value: 66.58208955223881
|
25 |
+
- type: ap
|
26 |
+
value: 28.455148149555754
|
27 |
+
- type: f1
|
28 |
+
value: 59.973775371110385
|
29 |
+
- task:
|
30 |
+
type: Classification
|
31 |
+
dataset:
|
32 |
+
type: mteb/amazon_polarity
|
33 |
+
name: MTEB AmazonPolarityClassification
|
34 |
+
config: default
|
35 |
+
split: test
|
36 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
37 |
+
metrics:
|
38 |
+
- type: accuracy
|
39 |
+
value: 65.09505
|
40 |
+
- type: ap
|
41 |
+
value: 61.387245649832614
|
42 |
+
- type: f1
|
43 |
+
value: 62.96831291412068
|
44 |
+
- task:
|
45 |
+
type: Classification
|
46 |
+
dataset:
|
47 |
+
type: mteb/amazon_reviews_multi
|
48 |
+
name: MTEB AmazonReviewsClassification (en)
|
49 |
+
config: en
|
50 |
+
split: test
|
51 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
52 |
+
metrics:
|
53 |
+
- type: accuracy
|
54 |
+
value: 30.633999999999993
|
55 |
+
- type: f1
|
56 |
+
value: 29.638828990078647
|
57 |
+
- task:
|
58 |
+
type: Retrieval
|
59 |
+
dataset:
|
60 |
+
type: arguana
|
61 |
+
name: MTEB ArguAna
|
62 |
+
config: default
|
63 |
+
split: test
|
64 |
+
revision: None
|
65 |
+
metrics:
|
66 |
+
- type: map_at_1
|
67 |
+
value: 25.889
|
68 |
+
- type: map_at_10
|
69 |
+
value: 40.604
|
70 |
+
- type: map_at_100
|
71 |
+
value: 41.697
|
72 |
+
- type: map_at_1000
|
73 |
+
value: 41.705999999999996
|
74 |
+
- type: map_at_3
|
75 |
+
value: 35.217999999999996
|
76 |
+
- type: map_at_5
|
77 |
+
value: 38.326
|
78 |
+
- type: mrr_at_1
|
79 |
+
value: 26.245
|
80 |
+
- type: mrr_at_10
|
81 |
+
value: 40.736
|
82 |
+
- type: mrr_at_100
|
83 |
+
value: 41.829
|
84 |
+
- type: mrr_at_1000
|
85 |
+
value: 41.837999999999994
|
86 |
+
- type: mrr_at_3
|
87 |
+
value: 35.349000000000004
|
88 |
+
- type: mrr_at_5
|
89 |
+
value: 38.425
|
90 |
+
- type: ndcg_at_1
|
91 |
+
value: 25.889
|
92 |
+
- type: ndcg_at_10
|
93 |
+
value: 49.347
|
94 |
+
- type: ndcg_at_100
|
95 |
+
value: 53.956
|
96 |
+
- type: ndcg_at_1000
|
97 |
+
value: 54.2
|
98 |
+
- type: ndcg_at_3
|
99 |
+
value: 38.282
|
100 |
+
- type: ndcg_at_5
|
101 |
+
value: 43.895
|
102 |
+
- type: precision_at_1
|
103 |
+
value: 25.889
|
104 |
+
- type: precision_at_10
|
105 |
+
value: 7.752000000000001
|
106 |
+
- type: precision_at_100
|
107 |
+
value: 0.976
|
108 |
+
- type: precision_at_1000
|
109 |
+
value: 0.1
|
110 |
+
- type: precision_at_3
|
111 |
+
value: 15.717999999999998
|
112 |
+
- type: precision_at_5
|
113 |
+
value: 12.162
|
114 |
+
- type: recall_at_1
|
115 |
+
value: 25.889
|
116 |
+
- type: recall_at_10
|
117 |
+
value: 77.525
|
118 |
+
- type: recall_at_100
|
119 |
+
value: 97.58200000000001
|
120 |
+
- type: recall_at_1000
|
121 |
+
value: 99.502
|
122 |
+
- type: recall_at_3
|
123 |
+
value: 47.155
|
124 |
+
- type: recall_at_5
|
125 |
+
value: 60.81100000000001
|
126 |
+
- task:
|
127 |
+
type: Clustering
|
128 |
+
dataset:
|
129 |
+
type: mteb/arxiv-clustering-p2p
|
130 |
+
name: MTEB ArxivClusteringP2P
|
131 |
+
config: default
|
132 |
+
split: test
|
133 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
134 |
+
metrics:
|
135 |
+
- type: v_measure
|
136 |
+
value: 39.2179862062943
|
137 |
+
- task:
|
138 |
+
type: Clustering
|
139 |
+
dataset:
|
140 |
+
type: mteb/arxiv-clustering-s2s
|
141 |
+
name: MTEB ArxivClusteringS2S
|
142 |
+
config: default
|
143 |
+
split: test
|
144 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
145 |
+
metrics:
|
146 |
+
- type: v_measure
|
147 |
+
value: 29.87826673088078
|
148 |
+
- task:
|
149 |
+
type: Reranking
|
150 |
+
dataset:
|
151 |
+
type: mteb/askubuntudupquestions-reranking
|
152 |
+
name: MTEB AskUbuntuDupQuestions
|
153 |
+
config: default
|
154 |
+
split: test
|
155 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
156 |
+
metrics:
|
157 |
+
- type: map
|
158 |
+
value: 62.72401299412015
|
159 |
+
- type: mrr
|
160 |
+
value: 75.45167743921206
|
161 |
+
- task:
|
162 |
+
type: STS
|
163 |
+
dataset:
|
164 |
+
type: mteb/biosses-sts
|
165 |
+
name: MTEB BIOSSES
|
166 |
+
config: default
|
167 |
+
split: test
|
168 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
169 |
+
metrics:
|
170 |
+
- type: cos_sim_pearson
|
171 |
+
value: 85.96510928112639
|
172 |
+
- type: cos_sim_spearman
|
173 |
+
value: 82.64224450538681
|
174 |
+
- type: euclidean_pearson
|
175 |
+
value: 52.03458755006108
|
176 |
+
- type: euclidean_spearman
|
177 |
+
value: 52.83192670285616
|
178 |
+
- type: manhattan_pearson
|
179 |
+
value: 52.14561955040935
|
180 |
+
- type: manhattan_spearman
|
181 |
+
value: 52.9584356095438
|
182 |
+
- task:
|
183 |
+
type: Classification
|
184 |
+
dataset:
|
185 |
+
type: mteb/banking77
|
186 |
+
name: MTEB Banking77Classification
|
187 |
+
config: default
|
188 |
+
split: test
|
189 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
190 |
+
metrics:
|
191 |
+
- type: accuracy
|
192 |
+
value: 84.11363636363636
|
193 |
+
- type: f1
|
194 |
+
value: 84.01098114920124
|
195 |
+
- task:
|
196 |
+
type: Clustering
|
197 |
+
dataset:
|
198 |
+
type: mteb/biorxiv-clustering-p2p
|
199 |
+
name: MTEB BiorxivClusteringP2P
|
200 |
+
config: default
|
201 |
+
split: test
|
202 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
203 |
+
metrics:
|
204 |
+
- type: v_measure
|
205 |
+
value: 32.991971466919026
|
206 |
+
- task:
|
207 |
+
type: Clustering
|
208 |
+
dataset:
|
209 |
+
type: mteb/biorxiv-clustering-s2s
|
210 |
+
name: MTEB BiorxivClusteringS2S
|
211 |
+
config: default
|
212 |
+
split: test
|
213 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
214 |
+
metrics:
|
215 |
+
- type: v_measure
|
216 |
+
value: 26.48807922559519
|
217 |
+
- task:
|
218 |
+
type: Retrieval
|
219 |
+
dataset:
|
220 |
+
type: climate-fever
|
221 |
+
name: MTEB ClimateFEVER
|
222 |
+
config: default
|
223 |
+
split: test
|
224 |
+
revision: None
|
225 |
+
metrics:
|
226 |
+
- type: map_at_1
|
227 |
+
value: 8.014000000000001
|
228 |
+
- type: map_at_10
|
229 |
+
value: 14.149999999999999
|
230 |
+
- type: map_at_100
|
231 |
+
value: 15.539
|
232 |
+
- type: map_at_1000
|
233 |
+
value: 15.711
|
234 |
+
- type: map_at_3
|
235 |
+
value: 11.913
|
236 |
+
- type: map_at_5
|
237 |
+
value: 12.982
|
238 |
+
- type: mrr_at_1
|
239 |
+
value: 18.046
|
240 |
+
- type: mrr_at_10
|
241 |
+
value: 28.224
|
242 |
+
- type: mrr_at_100
|
243 |
+
value: 29.293000000000003
|
244 |
+
- type: mrr_at_1000
|
245 |
+
value: 29.348999999999997
|
246 |
+
- type: mrr_at_3
|
247 |
+
value: 25.179000000000002
|
248 |
+
- type: mrr_at_5
|
249 |
+
value: 26.827
|
250 |
+
- type: ndcg_at_1
|
251 |
+
value: 18.046
|
252 |
+
- type: ndcg_at_10
|
253 |
+
value: 20.784
|
254 |
+
- type: ndcg_at_100
|
255 |
+
value: 26.939999999999998
|
256 |
+
- type: ndcg_at_1000
|
257 |
+
value: 30.453999999999997
|
258 |
+
- type: ndcg_at_3
|
259 |
+
value: 16.694
|
260 |
+
- type: ndcg_at_5
|
261 |
+
value: 18.049
|
262 |
+
- type: precision_at_1
|
263 |
+
value: 18.046
|
264 |
+
- type: precision_at_10
|
265 |
+
value: 6.5280000000000005
|
266 |
+
- type: precision_at_100
|
267 |
+
value: 1.2959999999999998
|
268 |
+
- type: precision_at_1000
|
269 |
+
value: 0.19499999999999998
|
270 |
+
- type: precision_at_3
|
271 |
+
value: 12.465
|
272 |
+
- type: precision_at_5
|
273 |
+
value: 9.511
|
274 |
+
- type: recall_at_1
|
275 |
+
value: 8.014000000000001
|
276 |
+
- type: recall_at_10
|
277 |
+
value: 26.021
|
278 |
+
- type: recall_at_100
|
279 |
+
value: 47.692
|
280 |
+
- type: recall_at_1000
|
281 |
+
value: 67.63
|
282 |
+
- type: recall_at_3
|
283 |
+
value: 16.122
|
284 |
+
- type: recall_at_5
|
285 |
+
value: 19.817
|
286 |
+
- task:
|
287 |
+
type: Retrieval
|
288 |
+
dataset:
|
289 |
+
type: dbpedia-entity
|
290 |
+
name: MTEB DBPedia
|
291 |
+
config: default
|
292 |
+
split: test
|
293 |
+
revision: None
|
294 |
+
metrics:
|
295 |
+
- type: map_at_1
|
296 |
+
value: 7.396
|
297 |
+
- type: map_at_10
|
298 |
+
value: 14.543000000000001
|
299 |
+
- type: map_at_100
|
300 |
+
value: 19.235
|
301 |
+
- type: map_at_1000
|
302 |
+
value: 20.384
|
303 |
+
- type: map_at_3
|
304 |
+
value: 10.886
|
305 |
+
- type: map_at_5
|
306 |
+
value: 12.61
|
307 |
+
- type: mrr_at_1
|
308 |
+
value: 55.50000000000001
|
309 |
+
- type: mrr_at_10
|
310 |
+
value: 63.731
|
311 |
+
- type: mrr_at_100
|
312 |
+
value: 64.256
|
313 |
+
- type: mrr_at_1000
|
314 |
+
value: 64.27000000000001
|
315 |
+
- type: mrr_at_3
|
316 |
+
value: 61.583
|
317 |
+
- type: mrr_at_5
|
318 |
+
value: 62.92100000000001
|
319 |
+
- type: ndcg_at_1
|
320 |
+
value: 43.375
|
321 |
+
- type: ndcg_at_10
|
322 |
+
value: 31.352000000000004
|
323 |
+
- type: ndcg_at_100
|
324 |
+
value: 34.717999999999996
|
325 |
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- type: ndcg_at_1000
|
326 |
+
value: 41.959
|
327 |
+
- type: ndcg_at_3
|
328 |
+
value: 35.319
|
329 |
+
- type: ndcg_at_5
|
330 |
+
value: 33.222
|
331 |
+
- type: precision_at_1
|
332 |
+
value: 55.50000000000001
|
333 |
+
- type: precision_at_10
|
334 |
+
value: 24.15
|
335 |
+
- type: precision_at_100
|
336 |
+
value: 7.42
|
337 |
+
- type: precision_at_1000
|
338 |
+
value: 1.66
|
339 |
+
- type: precision_at_3
|
340 |
+
value: 37.917
|
341 |
+
- type: precision_at_5
|
342 |
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value: 31.900000000000002
|
343 |
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- type: recall_at_1
|
344 |
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value: 7.396
|
345 |
+
- type: recall_at_10
|
346 |
+
value: 19.686999999999998
|
347 |
+
- type: recall_at_100
|
348 |
+
value: 40.465
|
349 |
+
- type: recall_at_1000
|
350 |
+
value: 63.79899999999999
|
351 |
+
- type: recall_at_3
|
352 |
+
value: 12.124
|
353 |
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- type: recall_at_5
|
354 |
+
value: 15.28
|
355 |
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- task:
|
356 |
+
type: Classification
|
357 |
+
dataset:
|
358 |
+
type: mteb/emotion
|
359 |
+
name: MTEB EmotionClassification
|
360 |
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config: default
|
361 |
+
split: test
|
362 |
+
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
363 |
+
metrics:
|
364 |
+
- type: accuracy
|
365 |
+
value: 41.33
|
366 |
+
- type: f1
|
367 |
+
value: 37.682972473685496
|
368 |
+
- task:
|
369 |
+
type: Retrieval
|
370 |
+
dataset:
|
371 |
+
type: fever
|
372 |
+
name: MTEB FEVER
|
373 |
+
config: default
|
374 |
+
split: test
|
375 |
+
revision: None
|
376 |
+
metrics:
|
377 |
+
- type: map_at_1
|
378 |
+
value: 49.019
|
379 |
+
- type: map_at_10
|
380 |
+
value: 61.219
|
381 |
+
- type: map_at_100
|
382 |
+
value: 61.753
|
383 |
+
- type: map_at_1000
|
384 |
+
value: 61.771
|
385 |
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- type: map_at_3
|
386 |
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value: 58.952000000000005
|
387 |
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- type: map_at_5
|
388 |
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value: 60.239
|
389 |
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- type: mrr_at_1
|
390 |
+
value: 53.0
|
391 |
+
- type: mrr_at_10
|
392 |
+
value: 65.678
|
393 |
+
- type: mrr_at_100
|
394 |
+
value: 66.147
|
395 |
+
- type: mrr_at_1000
|
396 |
+
value: 66.155
|
397 |
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- type: mrr_at_3
|
398 |
+
value: 63.495999999999995
|
399 |
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- type: mrr_at_5
|
400 |
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value: 64.75800000000001
|
401 |
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- type: ndcg_at_1
|
402 |
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value: 53.0
|
403 |
+
- type: ndcg_at_10
|
404 |
+
value: 67.587
|
405 |
+
- type: ndcg_at_100
|
406 |
+
value: 69.877
|
407 |
+
- type: ndcg_at_1000
|
408 |
+
value: 70.25200000000001
|
409 |
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- type: ndcg_at_3
|
410 |
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value: 63.174
|
411 |
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- type: ndcg_at_5
|
412 |
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value: 65.351
|
413 |
+
- type: precision_at_1
|
414 |
+
value: 53.0
|
415 |
+
- type: precision_at_10
|
416 |
+
value: 9.067
|
417 |
+
- type: precision_at_100
|
418 |
+
value: 1.026
|
419 |
+
- type: precision_at_1000
|
420 |
+
value: 0.107
|
421 |
+
- type: precision_at_3
|
422 |
+
value: 25.728
|
423 |
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- type: precision_at_5
|
424 |
+
value: 16.637
|
425 |
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- type: recall_at_1
|
426 |
+
value: 49.019
|
427 |
+
- type: recall_at_10
|
428 |
+
value: 82.962
|
429 |
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- type: recall_at_100
|
430 |
+
value: 92.917
|
431 |
+
- type: recall_at_1000
|
432 |
+
value: 95.511
|
433 |
+
- type: recall_at_3
|
434 |
+
value: 70.838
|
435 |
+
- type: recall_at_5
|
436 |
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value: 76.201
|
437 |
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- task:
|
438 |
+
type: Retrieval
|
439 |
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dataset:
|
440 |
+
type: fiqa
|
441 |
+
name: MTEB FiQA2018
|
442 |
+
config: default
|
443 |
+
split: test
|
444 |
+
revision: None
|
445 |
+
metrics:
|
446 |
+
- type: map_at_1
|
447 |
+
value: 16.714000000000002
|
448 |
+
- type: map_at_10
|
449 |
+
value: 28.041
|
450 |
+
- type: map_at_100
|
451 |
+
value: 29.75
|
452 |
+
- type: map_at_1000
|
453 |
+
value: 29.944
|
454 |
+
- type: map_at_3
|
455 |
+
value: 23.884
|
456 |
+
- type: map_at_5
|
457 |
+
value: 26.468000000000004
|
458 |
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- type: mrr_at_1
|
459 |
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value: 33.796
|
460 |
+
- type: mrr_at_10
|
461 |
+
value: 42.757
|
462 |
+
- type: mrr_at_100
|
463 |
+
value: 43.705
|
464 |
+
- type: mrr_at_1000
|
465 |
+
value: 43.751
|
466 |
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- type: mrr_at_3
|
467 |
+
value: 40.406
|
468 |
+
- type: mrr_at_5
|
469 |
+
value: 41.88
|
470 |
+
- type: ndcg_at_1
|
471 |
+
value: 33.796
|
472 |
+
- type: ndcg_at_10
|
473 |
+
value: 35.482
|
474 |
+
- type: ndcg_at_100
|
475 |
+
value: 42.44
|
476 |
+
- type: ndcg_at_1000
|
477 |
+
value: 45.903
|
478 |
+
- type: ndcg_at_3
|
479 |
+
value: 31.922
|
480 |
+
- type: ndcg_at_5
|
481 |
+
value: 33.516
|
482 |
+
- type: precision_at_1
|
483 |
+
value: 33.796
|
484 |
+
- type: precision_at_10
|
485 |
+
value: 10.108
|
486 |
+
- type: precision_at_100
|
487 |
+
value: 1.735
|
488 |
+
- type: precision_at_1000
|
489 |
+
value: 0.23500000000000001
|
490 |
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- type: precision_at_3
|
491 |
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value: 21.759
|
492 |
+
- type: precision_at_5
|
493 |
+
value: 16.605
|
494 |
+
- type: recall_at_1
|
495 |
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value: 16.714000000000002
|
496 |
+
- type: recall_at_10
|
497 |
+
value: 42.38
|
498 |
+
- type: recall_at_100
|
499 |
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value: 68.84700000000001
|
500 |
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- type: recall_at_1000
|
501 |
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value: 90.036
|
502 |
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- type: recall_at_3
|
503 |
+
value: 28.776000000000003
|
504 |
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- type: recall_at_5
|
505 |
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value: 35.606
|
506 |
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- task:
|
507 |
+
type: Retrieval
|
508 |
+
dataset:
|
509 |
+
type: hotpotqa
|
510 |
+
name: MTEB HotpotQA
|
511 |
+
config: default
|
512 |
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split: test
|
513 |
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revision: None
|
514 |
+
metrics:
|
515 |
+
- type: map_at_1
|
516 |
+
value: 29.534
|
517 |
+
- type: map_at_10
|
518 |
+
value: 40.857
|
519 |
+
- type: map_at_100
|
520 |
+
value: 41.715999999999994
|
521 |
+
- type: map_at_1000
|
522 |
+
value: 41.795
|
523 |
+
- type: map_at_3
|
524 |
+
value: 38.415
|
525 |
+
- type: map_at_5
|
526 |
+
value: 39.833
|
527 |
+
- type: mrr_at_1
|
528 |
+
value: 59.068
|
529 |
+
- type: mrr_at_10
|
530 |
+
value: 66.034
|
531 |
+
- type: mrr_at_100
|
532 |
+
value: 66.479
|
533 |
+
- type: mrr_at_1000
|
534 |
+
value: 66.50399999999999
|
535 |
+
- type: mrr_at_3
|
536 |
+
value: 64.38000000000001
|
537 |
+
- type: mrr_at_5
|
538 |
+
value: 65.40599999999999
|
539 |
+
- type: ndcg_at_1
|
540 |
+
value: 59.068
|
541 |
+
- type: ndcg_at_10
|
542 |
+
value: 49.638
|
543 |
+
- type: ndcg_at_100
|
544 |
+
value: 53.093999999999994
|
545 |
+
- type: ndcg_at_1000
|
546 |
+
value: 54.813
|
547 |
+
- type: ndcg_at_3
|
548 |
+
value: 45.537
|
549 |
+
- type: ndcg_at_5
|
550 |
+
value: 47.671
|
551 |
+
- type: precision_at_1
|
552 |
+
value: 59.068
|
553 |
+
- type: precision_at_10
|
554 |
+
value: 10.313
|
555 |
+
- type: precision_at_100
|
556 |
+
value: 1.304
|
557 |
+
- type: precision_at_1000
|
558 |
+
value: 0.153
|
559 |
+
- type: precision_at_3
|
560 |
+
value: 28.278
|
561 |
+
- type: precision_at_5
|
562 |
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value: 18.658
|
563 |
+
- type: recall_at_1
|
564 |
+
value: 29.534
|
565 |
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- type: recall_at_10
|
566 |
+
value: 51.56699999999999
|
567 |
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- type: recall_at_100
|
568 |
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value: 65.199
|
569 |
+
- type: recall_at_1000
|
570 |
+
value: 76.678
|
571 |
+
- type: recall_at_3
|
572 |
+
value: 42.417
|
573 |
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- type: recall_at_5
|
574 |
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value: 46.644000000000005
|
575 |
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- task:
|
576 |
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type: Classification
|
577 |
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dataset:
|
578 |
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type: mteb/imdb
|
579 |
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name: MTEB ImdbClassification
|
580 |
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config: default
|
581 |
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split: test
|
582 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
583 |
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metrics:
|
584 |
+
- type: accuracy
|
585 |
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value: 65.74719999999999
|
586 |
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- type: ap
|
587 |
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value: 60.57322504947344
|
588 |
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- type: f1
|
589 |
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value: 65.37875006542282
|
590 |
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- task:
|
591 |
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type: Retrieval
|
592 |
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dataset:
|
593 |
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type: msmarco
|
594 |
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name: MTEB MSMARCO
|
595 |
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config: default
|
596 |
+
split: dev
|
597 |
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revision: None
|
598 |
+
metrics:
|
599 |
+
- type: map_at_1
|
600 |
+
value: 15.695999999999998
|
601 |
+
- type: map_at_10
|
602 |
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value: 26.661
|
603 |
+
- type: map_at_100
|
604 |
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value: 27.982000000000003
|
605 |
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- type: map_at_1000
|
606 |
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value: 28.049000000000003
|
607 |
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- type: map_at_3
|
608 |
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value: 23.057
|
609 |
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- type: map_at_5
|
610 |
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value: 25.079
|
611 |
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- type: mrr_at_1
|
612 |
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value: 16.16
|
613 |
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- type: mrr_at_10
|
614 |
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value: 27.150999999999996
|
615 |
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- type: mrr_at_100
|
616 |
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value: 28.423
|
617 |
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- type: mrr_at_1000
|
618 |
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value: 28.483999999999998
|
619 |
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- type: mrr_at_3
|
620 |
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value: 23.577
|
621 |
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- type: mrr_at_5
|
622 |
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value: 25.585
|
623 |
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- type: ndcg_at_1
|
624 |
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value: 16.16
|
625 |
+
- type: ndcg_at_10
|
626 |
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value: 33.017
|
627 |
+
- type: ndcg_at_100
|
628 |
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value: 39.582
|
629 |
+
- type: ndcg_at_1000
|
630 |
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value: 41.28
|
631 |
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- type: ndcg_at_3
|
632 |
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value: 25.607000000000003
|
633 |
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- type: ndcg_at_5
|
634 |
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value: 29.214000000000002
|
635 |
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- type: precision_at_1
|
636 |
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value: 16.16
|
637 |
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- type: precision_at_10
|
638 |
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value: 5.506
|
639 |
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- type: precision_at_100
|
640 |
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value: 0.882
|
641 |
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- type: precision_at_1000
|
642 |
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value: 0.10300000000000001
|
643 |
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- type: precision_at_3
|
644 |
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value: 11.199
|
645 |
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- type: precision_at_5
|
646 |
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value: 8.55
|
647 |
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- type: recall_at_1
|
648 |
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value: 15.695999999999998
|
649 |
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- type: recall_at_10
|
650 |
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value: 52.736000000000004
|
651 |
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- type: recall_at_100
|
652 |
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value: 83.523
|
653 |
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- type: recall_at_1000
|
654 |
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value: 96.588
|
655 |
+
- type: recall_at_3
|
656 |
+
value: 32.484
|
657 |
+
- type: recall_at_5
|
658 |
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value: 41.117
|
659 |
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- task:
|
660 |
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type: Classification
|
661 |
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dataset:
|
662 |
+
type: mteb/mtop_domain
|
663 |
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name: MTEB MTOPDomainClassification (en)
|
664 |
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config: en
|
665 |
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split: test
|
666 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
667 |
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metrics:
|
668 |
+
- type: accuracy
|
669 |
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value: 91.71682626538988
|
670 |
+
- type: f1
|
671 |
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value: 91.60647677401211
|
672 |
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- task:
|
673 |
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type: Classification
|
674 |
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dataset:
|
675 |
+
type: mteb/mtop_intent
|
676 |
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name: MTEB MTOPIntentClassification (en)
|
677 |
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config: en
|
678 |
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split: test
|
679 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
680 |
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metrics:
|
681 |
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- type: accuracy
|
682 |
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value: 74.94756041951665
|
683 |
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- type: f1
|
684 |
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value: 57.26936028487369
|
685 |
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- task:
|
686 |
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type: Classification
|
687 |
+
dataset:
|
688 |
+
type: mteb/amazon_massive_intent
|
689 |
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name: MTEB MassiveIntentClassification (en)
|
690 |
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config: en
|
691 |
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split: test
|
692 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
693 |
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metrics:
|
694 |
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- type: accuracy
|
695 |
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value: 71.43241425689307
|
696 |
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- type: f1
|
697 |
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value: 68.80370629448252
|
698 |
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- task:
|
699 |
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type: Classification
|
700 |
+
dataset:
|
701 |
+
type: mteb/amazon_massive_scenario
|
702 |
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name: MTEB MassiveScenarioClassification (en)
|
703 |
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config: en
|
704 |
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split: test
|
705 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
706 |
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metrics:
|
707 |
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- type: accuracy
|
708 |
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value: 77.04774714189642
|
709 |
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- type: f1
|
710 |
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value: 76.93545888412446
|
711 |
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- task:
|
712 |
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type: Clustering
|
713 |
+
dataset:
|
714 |
+
type: mteb/medrxiv-clustering-p2p
|
715 |
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name: MTEB MedrxivClusteringP2P
|
716 |
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config: default
|
717 |
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split: test
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718 |
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revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
719 |
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metrics:
|
720 |
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- type: v_measure
|
721 |
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value: 30.009784989313765
|
722 |
+
- task:
|
723 |
+
type: Clustering
|
724 |
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dataset:
|
725 |
+
type: mteb/medrxiv-clustering-s2s
|
726 |
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name: MTEB MedrxivClusteringS2S
|
727 |
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config: default
|
728 |
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split: test
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729 |
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revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
730 |
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metrics:
|
731 |
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- type: v_measure
|
732 |
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value: 25.568442512328872
|
733 |
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- task:
|
734 |
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type: Reranking
|
735 |
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dataset:
|
736 |
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type: mteb/mind_small
|
737 |
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name: MTEB MindSmallReranking
|
738 |
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config: default
|
739 |
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split: test
|
740 |
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revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
741 |
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metrics:
|
742 |
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- type: map
|
743 |
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value: 31.013959341949697
|
744 |
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- type: mrr
|
745 |
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value: 31.998487836684575
|
746 |
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- task:
|
747 |
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type: Retrieval
|
748 |
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dataset:
|
749 |
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type: nfcorpus
|
750 |
+
name: MTEB NFCorpus
|
751 |
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config: default
|
752 |
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split: test
|
753 |
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revision: None
|
754 |
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metrics:
|
755 |
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- type: map_at_1
|
756 |
+
value: 4.316
|
757 |
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- type: map_at_10
|
758 |
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value: 10.287
|
759 |
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- type: map_at_100
|
760 |
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value: 12.817
|
761 |
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- type: map_at_1000
|
762 |
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value: 14.141
|
763 |
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- type: map_at_3
|
764 |
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value: 7.728
|
765 |
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- type: map_at_5
|
766 |
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value: 8.876000000000001
|
767 |
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- type: mrr_at_1
|
768 |
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value: 39.628
|
769 |
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- type: mrr_at_10
|
770 |
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value: 48.423
|
771 |
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- type: mrr_at_100
|
772 |
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value: 49.153999999999996
|
773 |
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- type: mrr_at_1000
|
774 |
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value: 49.198
|
775 |
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- type: mrr_at_3
|
776 |
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value: 45.666000000000004
|
777 |
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- type: mrr_at_5
|
778 |
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value: 47.477000000000004
|
779 |
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- type: ndcg_at_1
|
780 |
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value: 36.533
|
781 |
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- type: ndcg_at_10
|
782 |
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value: 29.304000000000002
|
783 |
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- type: ndcg_at_100
|
784 |
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value: 27.078000000000003
|
785 |
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- type: ndcg_at_1000
|
786 |
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value: 36.221
|
787 |
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- type: ndcg_at_3
|
788 |
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value: 33.256
|
789 |
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- type: ndcg_at_5
|
790 |
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value: 31.465
|
791 |
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- type: precision_at_1
|
792 |
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value: 39.009
|
793 |
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- type: precision_at_10
|
794 |
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value: 22.043
|
795 |
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- type: precision_at_100
|
796 |
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value: 7.115
|
797 |
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- type: precision_at_1000
|
798 |
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value: 1.991
|
799 |
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- type: precision_at_3
|
800 |
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value: 31.476
|
801 |
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- type: precision_at_5
|
802 |
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value: 27.616000000000003
|
803 |
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- type: recall_at_1
|
804 |
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value: 4.316
|
805 |
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- type: recall_at_10
|
806 |
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value: 14.507
|
807 |
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- type: recall_at_100
|
808 |
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value: 28.847
|
809 |
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- type: recall_at_1000
|
810 |
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value: 61.758
|
811 |
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- type: recall_at_3
|
812 |
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value: 8.753
|
813 |
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- type: recall_at_5
|
814 |
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value: 11.153
|
815 |
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- task:
|
816 |
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type: Retrieval
|
817 |
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dataset:
|
818 |
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type: nq
|
819 |
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name: MTEB NQ
|
820 |
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config: default
|
821 |
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split: test
|
822 |
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revision: None
|
823 |
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metrics:
|
824 |
+
- type: map_at_1
|
825 |
+
value: 22.374
|
826 |
+
- type: map_at_10
|
827 |
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value: 36.095
|
828 |
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- type: map_at_100
|
829 |
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value: 37.413999999999994
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830 |
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- type: map_at_1000
|
831 |
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value: 37.46
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832 |
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- type: map_at_3
|
833 |
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value: 31.711
|
834 |
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- type: map_at_5
|
835 |
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value: 34.294999999999995
|
836 |
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- type: mrr_at_1
|
837 |
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value: 25.406000000000002
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838 |
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- type: mrr_at_10
|
839 |
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value: 38.424
|
840 |
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- type: mrr_at_100
|
841 |
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value: 39.456
|
842 |
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- type: mrr_at_1000
|
843 |
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value: 39.488
|
844 |
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- type: mrr_at_3
|
845 |
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value: 34.613
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846 |
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- type: mrr_at_5
|
847 |
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value: 36.864999999999995
|
848 |
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- type: ndcg_at_1
|
849 |
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value: 25.406000000000002
|
850 |
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- type: ndcg_at_10
|
851 |
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value: 43.614000000000004
|
852 |
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- type: ndcg_at_100
|
853 |
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value: 49.166
|
854 |
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- type: ndcg_at_1000
|
855 |
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value: 50.212
|
856 |
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- type: ndcg_at_3
|
857 |
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value: 35.221999999999994
|
858 |
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- type: ndcg_at_5
|
859 |
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value: 39.571
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860 |
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- type: precision_at_1
|
861 |
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value: 25.406000000000002
|
862 |
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- type: precision_at_10
|
863 |
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value: 7.654
|
864 |
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- type: precision_at_100
|
865 |
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value: 1.0699999999999998
|
866 |
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- type: precision_at_1000
|
867 |
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value: 0.117
|
868 |
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- type: precision_at_3
|
869 |
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value: 16.425
|
870 |
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- type: precision_at_5
|
871 |
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value: 12.352
|
872 |
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- type: recall_at_1
|
873 |
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value: 22.374
|
874 |
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- type: recall_at_10
|
875 |
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value: 64.337
|
876 |
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- type: recall_at_100
|
877 |
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value: 88.374
|
878 |
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- type: recall_at_1000
|
879 |
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value: 96.101
|
880 |
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- type: recall_at_3
|
881 |
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value: 42.5
|
882 |
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- type: recall_at_5
|
883 |
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value: 52.556000000000004
|
884 |
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- task:
|
885 |
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type: Retrieval
|
886 |
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dataset:
|
887 |
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type: quora
|
888 |
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name: MTEB QuoraRetrieval
|
889 |
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config: default
|
890 |
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split: test
|
891 |
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revision: None
|
892 |
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metrics:
|
893 |
+
- type: map_at_1
|
894 |
+
value: 69.301
|
895 |
+
- type: map_at_10
|
896 |
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value: 83.128
|
897 |
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- type: map_at_100
|
898 |
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value: 83.779
|
899 |
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- type: map_at_1000
|
900 |
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value: 83.798
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901 |
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- type: map_at_3
|
902 |
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value: 80.11399999999999
|
903 |
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- type: map_at_5
|
904 |
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value: 82.00699999999999
|
905 |
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- type: mrr_at_1
|
906 |
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value: 79.81
|
907 |
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- type: mrr_at_10
|
908 |
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value: 86.28
|
909 |
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- type: mrr_at_100
|
910 |
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value: 86.399
|
911 |
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- type: mrr_at_1000
|
912 |
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value: 86.401
|
913 |
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- type: mrr_at_3
|
914 |
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value: 85.26
|
915 |
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- type: mrr_at_5
|
916 |
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value: 85.93499999999999
|
917 |
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- type: ndcg_at_1
|
918 |
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value: 79.80000000000001
|
919 |
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- type: ndcg_at_10
|
920 |
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value: 87.06700000000001
|
921 |
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- type: ndcg_at_100
|
922 |
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value: 88.41799999999999
|
923 |
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- type: ndcg_at_1000
|
924 |
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value: 88.554
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925 |
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- type: ndcg_at_3
|
926 |
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value: 84.052
|
927 |
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- type: ndcg_at_5
|
928 |
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value: 85.711
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929 |
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- type: precision_at_1
|
930 |
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value: 79.80000000000001
|
931 |
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- type: precision_at_10
|
932 |
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value: 13.224
|
933 |
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- type: precision_at_100
|
934 |
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value: 1.5230000000000001
|
935 |
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- type: precision_at_1000
|
936 |
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value: 0.157
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937 |
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- type: precision_at_3
|
938 |
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value: 36.723
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939 |
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- type: precision_at_5
|
940 |
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value: 24.192
|
941 |
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- type: recall_at_1
|
942 |
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value: 69.301
|
943 |
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- type: recall_at_10
|
944 |
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value: 94.589
|
945 |
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- type: recall_at_100
|
946 |
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value: 99.29299999999999
|
947 |
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- type: recall_at_1000
|
948 |
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value: 99.965
|
949 |
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- type: recall_at_3
|
950 |
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value: 86.045
|
951 |
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- type: recall_at_5
|
952 |
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value: 90.656
|
953 |
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- task:
|
954 |
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type: Clustering
|
955 |
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dataset:
|
956 |
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type: mteb/reddit-clustering
|
957 |
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name: MTEB RedditClustering
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958 |
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config: default
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959 |
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split: test
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960 |
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revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
961 |
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metrics:
|
962 |
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- type: v_measure
|
963 |
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value: 43.09903181165838
|
964 |
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- task:
|
965 |
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type: Clustering
|
966 |
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dataset:
|
967 |
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type: mteb/reddit-clustering-p2p
|
968 |
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name: MTEB RedditClusteringP2P
|
969 |
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config: default
|
970 |
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split: test
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971 |
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revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
972 |
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metrics:
|
973 |
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- type: v_measure
|
974 |
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value: 51.710378422887594
|
975 |
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- task:
|
976 |
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type: Retrieval
|
977 |
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dataset:
|
978 |
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type: scidocs
|
979 |
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name: MTEB SCIDOCS
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980 |
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config: default
|
981 |
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split: test
|
982 |
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revision: None
|
983 |
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metrics:
|
984 |
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- type: map_at_1
|
985 |
+
value: 4.138
|
986 |
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- type: map_at_10
|
987 |
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value: 10.419
|
988 |
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- type: map_at_100
|
989 |
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value: 12.321
|
990 |
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- type: map_at_1000
|
991 |
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value: 12.605
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992 |
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- type: map_at_3
|
993 |
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value: 7.445
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994 |
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- type: map_at_5
|
995 |
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value: 8.859
|
996 |
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- type: mrr_at_1
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997 |
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value: 20.4
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998 |
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999 |
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value: 30.148999999999997
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1000 |
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- type: mrr_at_100
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1001 |
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value: 31.357000000000003
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1002 |
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- type: mrr_at_1000
|
1003 |
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value: 31.424999999999997
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1004 |
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- type: mrr_at_3
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1005 |
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value: 26.983
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1006 |
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1007 |
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value: 28.883
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1008 |
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- type: ndcg_at_1
|
1009 |
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value: 20.4
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1010 |
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- type: ndcg_at_10
|
1011 |
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value: 17.713
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1012 |
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- type: ndcg_at_100
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1013 |
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value: 25.221
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1014 |
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- type: ndcg_at_1000
|
1015 |
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value: 30.381999999999998
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1016 |
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- type: ndcg_at_3
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1017 |
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value: 16.607
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1018 |
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|
1019 |
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value: 14.559
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1020 |
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- type: precision_at_1
|
1021 |
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value: 20.4
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1022 |
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- type: precision_at_10
|
1023 |
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value: 9.3
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1024 |
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|
1025 |
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value: 2.0060000000000002
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1026 |
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- type: precision_at_1000
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1027 |
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value: 0.32399999999999995
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1028 |
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|
1029 |
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value: 15.5
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1030 |
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- type: precision_at_5
|
1031 |
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value: 12.839999999999998
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1032 |
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- type: recall_at_1
|
1033 |
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value: 4.138
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1034 |
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- type: recall_at_10
|
1035 |
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value: 18.813
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1036 |
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- type: recall_at_100
|
1037 |
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value: 40.692
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1038 |
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- type: recall_at_1000
|
1039 |
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value: 65.835
|
1040 |
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- type: recall_at_3
|
1041 |
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value: 9.418
|
1042 |
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- type: recall_at_5
|
1043 |
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value: 12.983
|
1044 |
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- task:
|
1045 |
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type: STS
|
1046 |
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dataset:
|
1047 |
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type: mteb/sickr-sts
|
1048 |
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name: MTEB SICK-R
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1049 |
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config: default
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1050 |
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split: test
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1051 |
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revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1052 |
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metrics:
|
1053 |
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- type: cos_sim_pearson
|
1054 |
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value: 83.25944192442188
|
1055 |
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- type: cos_sim_spearman
|
1056 |
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value: 75.04296759426568
|
1057 |
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- type: euclidean_pearson
|
1058 |
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value: 74.8130340249869
|
1059 |
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- type: euclidean_spearman
|
1060 |
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value: 68.40180320816793
|
1061 |
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- type: manhattan_pearson
|
1062 |
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value: 74.9149619199144
|
1063 |
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- type: manhattan_spearman
|
1064 |
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value: 68.52380798258379
|
1065 |
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- task:
|
1066 |
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type: STS
|
1067 |
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dataset:
|
1068 |
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type: mteb/sts12-sts
|
1069 |
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name: MTEB STS12
|
1070 |
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config: default
|
1071 |
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split: test
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1072 |
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revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1073 |
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metrics:
|
1074 |
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- type: cos_sim_pearson
|
1075 |
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value: 81.91983072545858
|
1076 |
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- type: cos_sim_spearman
|
1077 |
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value: 73.5129498787296
|
1078 |
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- type: euclidean_pearson
|
1079 |
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value: 66.76535523270856
|
1080 |
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- type: euclidean_spearman
|
1081 |
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value: 56.64797879544097
|
1082 |
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- type: manhattan_pearson
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1083 |
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value: 66.12191731384162
|
1084 |
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- type: manhattan_spearman
|
1085 |
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value: 56.37753861965956
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1086 |
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- task:
|
1087 |
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type: STS
|
1088 |
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dataset:
|
1089 |
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type: mteb/sts13-sts
|
1090 |
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name: MTEB STS13
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1091 |
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config: default
|
1092 |
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split: test
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1093 |
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revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1094 |
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metrics:
|
1095 |
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- type: cos_sim_pearson
|
1096 |
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value: 77.71164758747632
|
1097 |
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- type: cos_sim_spearman
|
1098 |
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value: 79.1530762030973
|
1099 |
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- type: euclidean_pearson
|
1100 |
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value: 69.50621786400177
|
1101 |
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- type: euclidean_spearman
|
1102 |
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value: 70.44898083428744
|
1103 |
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- type: manhattan_pearson
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1104 |
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value: 69.04018458995307
|
1105 |
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- type: manhattan_spearman
|
1106 |
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value: 70.00888532086853
|
1107 |
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- task:
|
1108 |
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type: STS
|
1109 |
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dataset:
|
1110 |
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type: mteb/sts14-sts
|
1111 |
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name: MTEB STS14
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1112 |
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|
1113 |
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split: test
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1114 |
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revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
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1115 |
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metrics:
|
1116 |
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- type: cos_sim_pearson
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1117 |
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value: 78.90774995778577
|
1118 |
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- type: cos_sim_spearman
|
1119 |
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value: 75.24229403562713
|
1120 |
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- type: euclidean_pearson
|
1121 |
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value: 68.5838924571539
|
1122 |
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- type: euclidean_spearman
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1123 |
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value: 65.06652398167358
|
1124 |
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- type: manhattan_pearson
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1125 |
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value: 68.23143277902628
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1126 |
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- type: manhattan_spearman
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1127 |
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value: 64.79624516012709
|
1128 |
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- task:
|
1129 |
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type: STS
|
1130 |
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dataset:
|
1131 |
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type: mteb/sts15-sts
|
1132 |
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name: MTEB STS15
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1133 |
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config: default
|
1134 |
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split: test
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1135 |
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revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
1136 |
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metrics:
|
1137 |
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- type: cos_sim_pearson
|
1138 |
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value: 83.78074322110155
|
1139 |
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- type: cos_sim_spearman
|
1140 |
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value: 85.12071478276958
|
1141 |
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- type: euclidean_pearson
|
1142 |
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value: 65.00147804089737
|
1143 |
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- type: euclidean_spearman
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1144 |
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1145 |
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- type: manhattan_pearson
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1146 |
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value: 65.01270190203297
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1147 |
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- type: manhattan_spearman
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1148 |
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value: 66.13038450207748
|
1149 |
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- task:
|
1150 |
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type: STS
|
1151 |
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dataset:
|
1152 |
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type: mteb/sts16-sts
|
1153 |
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name: MTEB STS16
|
1154 |
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config: default
|
1155 |
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split: test
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1156 |
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|
1157 |
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metrics:
|
1158 |
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- type: cos_sim_pearson
|
1159 |
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value: 77.29395327338185
|
1160 |
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- type: cos_sim_spearman
|
1161 |
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value: 80.07128686563352
|
1162 |
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- type: euclidean_pearson
|
1163 |
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value: 65.97939065455975
|
1164 |
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- type: euclidean_spearman
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1165 |
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value: 66.80283051081129
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1166 |
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- type: manhattan_pearson
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1167 |
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value: 65.6750450606584
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1168 |
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- type: manhattan_spearman
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1170 |
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- task:
|
1171 |
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1172 |
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|
1173 |
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|
1174 |
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name: MTEB STS17 (en-en)
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1175 |
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config: en-en
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1176 |
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split: test
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1177 |
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revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
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1178 |
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metrics:
|
1179 |
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- type: cos_sim_pearson
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1180 |
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value: 87.64956503192369
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1181 |
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- type: cos_sim_spearman
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- type: manhattan_pearson
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- type: manhattan_spearman
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1190 |
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|
1191 |
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- task:
|
1192 |
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type: STS
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1193 |
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dataset:
|
1194 |
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type: mteb/sts22-crosslingual-sts
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1195 |
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name: MTEB STS22 (en)
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1196 |
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config: en
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1198 |
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revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
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1199 |
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metrics:
|
1200 |
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1201 |
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value: 66.61640922485357
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1202 |
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- type: cos_sim_spearman
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|
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- type: euclidean_pearson
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- type: manhattan_spearman
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1211 |
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|
1212 |
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- task:
|
1213 |
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type: STS
|
1214 |
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dataset:
|
1215 |
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type: mteb/stsbenchmark-sts
|
1216 |
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name: MTEB STSBenchmark
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1217 |
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1218 |
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split: test
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1219 |
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1220 |
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|
1221 |
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|
1222 |
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value: 81.73624666044613
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1223 |
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- type: cos_sim_spearman
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|
1225 |
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- type: euclidean_pearson
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1226 |
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- type: euclidean_spearman
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1228 |
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1229 |
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- type: manhattan_pearson
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1230 |
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1231 |
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- type: manhattan_spearman
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1232 |
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|
1233 |
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- task:
|
1234 |
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type: Reranking
|
1235 |
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dataset:
|
1236 |
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type: mteb/scidocs-reranking
|
1237 |
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name: MTEB SciDocsRR
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1238 |
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1239 |
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1240 |
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revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
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1241 |
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metrics:
|
1242 |
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- type: map
|
1243 |
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1244 |
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- type: mrr
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1245 |
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1246 |
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- task:
|
1247 |
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1248 |
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dataset:
|
1249 |
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type: scifact
|
1250 |
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name: MTEB SciFact
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1251 |
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config: default
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1252 |
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split: test
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1253 |
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revision: None
|
1254 |
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metrics:
|
1255 |
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- type: map_at_1
|
1256 |
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value: 43.761
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1257 |
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|
1258 |
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1259 |
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1262 |
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1265 |
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1266 |
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1267 |
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1268 |
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1269 |
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1270 |
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1271 |
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1273 |
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- type: mrr_at_1000
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1274 |
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1275 |
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1276 |
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value: 53.5
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1277 |
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1278 |
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1279 |
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- type: ndcg_at_1
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1280 |
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1281 |
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1285 |
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- type: ndcg_at_1000
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1286 |
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1287 |
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- type: ndcg_at_3
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1288 |
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1289 |
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- type: ndcg_at_5
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1291 |
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- type: precision_at_1
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1292 |
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1293 |
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- type: precision_at_10
|
1294 |
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value: 8.033
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1295 |
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- type: precision_at_100
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1296 |
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value: 0.963
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1297 |
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- type: precision_at_1000
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1298 |
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value: 0.11
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1299 |
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- type: precision_at_3
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1300 |
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value: 21.667
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1301 |
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- type: precision_at_5
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1302 |
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value: 14.066999999999998
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1303 |
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- type: recall_at_1
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1304 |
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value: 43.761
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1305 |
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- type: recall_at_10
|
1306 |
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value: 71.65599999999999
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1307 |
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- type: recall_at_100
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1308 |
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value: 84.433
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1309 |
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- type: recall_at_1000
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1310 |
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value: 97.5
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1311 |
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- type: recall_at_3
|
1312 |
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value: 59.522
|
1313 |
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- type: recall_at_5
|
1314 |
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value: 63.632999999999996
|
1315 |
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- task:
|
1316 |
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type: PairClassification
|
1317 |
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dataset:
|
1318 |
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type: mteb/sprintduplicatequestions-pairclassification
|
1319 |
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name: MTEB SprintDuplicateQuestions
|
1320 |
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config: default
|
1321 |
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split: test
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1322 |
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revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
1323 |
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metrics:
|
1324 |
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- type: cos_sim_accuracy
|
1325 |
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value: 99.68811881188118
|
1326 |
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- type: cos_sim_ap
|
1327 |
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|
1328 |
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- type: cos_sim_f1
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1329 |
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value: 84.38570729319628
|
1330 |
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- type: cos_sim_precision
|
1331 |
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value: 82.64621284755513
|
1332 |
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- type: cos_sim_recall
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1333 |
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value: 86.2
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1334 |
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- type: dot_accuracy
|
1335 |
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value: 99.14653465346535
|
1336 |
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- type: dot_ap
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1337 |
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|
1338 |
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- type: dot_f1
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1339 |
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value: 46.470062555853445
|
1340 |
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- type: dot_precision
|
1341 |
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value: 42.003231017770595
|
1342 |
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- type: dot_recall
|
1343 |
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value: 52.0
|
1344 |
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- type: euclidean_accuracy
|
1345 |
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value: 99.56930693069307
|
1346 |
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- type: euclidean_ap
|
1347 |
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value: 80.28575652582506
|
1348 |
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- type: euclidean_f1
|
1349 |
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value: 75.52054023635341
|
1350 |
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- type: euclidean_precision
|
1351 |
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value: 86.35778635778635
|
1352 |
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- type: euclidean_recall
|
1353 |
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value: 67.10000000000001
|
1354 |
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- type: manhattan_accuracy
|
1355 |
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value: 99.56039603960396
|
1356 |
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- type: manhattan_ap
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1357 |
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value: 79.74630510301085
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1358 |
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- type: manhattan_f1
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1359 |
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value: 74.67569091934575
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1360 |
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- type: manhattan_precision
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1361 |
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value: 85.64036222509702
|
1362 |
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- type: manhattan_recall
|
1363 |
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value: 66.2
|
1364 |
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- type: max_accuracy
|
1365 |
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value: 99.68811881188118
|
1366 |
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- type: max_ap
|
1367 |
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value: 91.08077352794682
|
1368 |
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- type: max_f1
|
1369 |
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value: 84.38570729319628
|
1370 |
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- task:
|
1371 |
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type: Clustering
|
1372 |
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dataset:
|
1373 |
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type: mteb/stackexchange-clustering
|
1374 |
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name: MTEB StackExchangeClustering
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1375 |
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config: default
|
1376 |
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split: test
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1377 |
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revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
1378 |
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metrics:
|
1379 |
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- type: v_measure
|
1380 |
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value: 52.0788049295693
|
1381 |
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- task:
|
1382 |
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type: Clustering
|
1383 |
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dataset:
|
1384 |
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type: mteb/stackexchange-clustering-p2p
|
1385 |
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name: MTEB StackExchangeClusteringP2P
|
1386 |
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config: default
|
1387 |
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split: test
|
1388 |
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1389 |
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metrics:
|
1390 |
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- type: v_measure
|
1391 |
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value: 31.606006030205545
|
1392 |
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- task:
|
1393 |
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type: Reranking
|
1394 |
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dataset:
|
1395 |
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type: mteb/stackoverflowdupquestions-reranking
|
1396 |
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name: MTEB StackOverflowDupQuestions
|
1397 |
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config: default
|
1398 |
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split: test
|
1399 |
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revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
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1400 |
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metrics:
|
1401 |
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- type: map
|
1402 |
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value: 50.87384988372756
|
1403 |
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- type: mrr
|
1404 |
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value: 51.62476922587217
|
1405 |
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- task:
|
1406 |
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type: Summarization
|
1407 |
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dataset:
|
1408 |
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|
1409 |
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name: MTEB SummEval
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1410 |
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config: default
|
1411 |
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split: test
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1412 |
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revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
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1413 |
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metrics:
|
1414 |
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- type: cos_sim_pearson
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1415 |
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value: 30.355859978837156
|
1416 |
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- type: cos_sim_spearman
|
1417 |
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value: 30.0847548337847
|
1418 |
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- type: dot_pearson
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1419 |
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value: 19.391736817587557
|
1420 |
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- type: dot_spearman
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1421 |
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value: 20.732256259543014
|
1422 |
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- task:
|
1423 |
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type: Retrieval
|
1424 |
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dataset:
|
1425 |
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type: trec-covid
|
1426 |
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name: MTEB TRECCOVID
|
1427 |
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config: default
|
1428 |
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split: test
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1429 |
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revision: None
|
1430 |
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metrics:
|
1431 |
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- type: map_at_1
|
1432 |
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value: 0.19
|
1433 |
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- type: map_at_10
|
1434 |
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value: 1.2850000000000001
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1435 |
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1436 |
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1437 |
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1438 |
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value: 15.21
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1439 |
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|
1440 |
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value: 0.492
|
1441 |
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|
1442 |
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value: 0.776
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1443 |
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1444 |
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value: 68.0
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1445 |
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|
1446 |
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value: 79.783
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1447 |
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- type: mrr_at_100
|
1448 |
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value: 79.783
|
1449 |
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- type: mrr_at_1000
|
1450 |
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value: 79.783
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1451 |
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- type: mrr_at_3
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1452 |
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value: 77.333
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1453 |
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1454 |
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value: 79.533
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1455 |
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- type: ndcg_at_1
|
1456 |
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value: 62.0
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1457 |
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|
1458 |
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value: 54.635
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1459 |
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|
1460 |
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value: 40.939
|
1461 |
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- type: ndcg_at_1000
|
1462 |
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value: 37.716
|
1463 |
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|
1464 |
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value: 58.531
|
1465 |
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- type: ndcg_at_5
|
1466 |
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value: 58.762
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1467 |
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- type: precision_at_1
|
1468 |
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value: 68.0
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1469 |
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- type: precision_at_10
|
1470 |
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value: 58.8
|
1471 |
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- type: precision_at_100
|
1472 |
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value: 41.74
|
1473 |
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- type: precision_at_1000
|
1474 |
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value: 16.938
|
1475 |
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- type: precision_at_3
|
1476 |
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value: 64.0
|
1477 |
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- type: precision_at_5
|
1478 |
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value: 64.8
|
1479 |
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- type: recall_at_1
|
1480 |
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value: 0.19
|
1481 |
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- type: recall_at_10
|
1482 |
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value: 1.547
|
1483 |
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- type: recall_at_100
|
1484 |
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value: 9.739
|
1485 |
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- type: recall_at_1000
|
1486 |
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value: 35.815000000000005
|
1487 |
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- type: recall_at_3
|
1488 |
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value: 0.528
|
1489 |
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- type: recall_at_5
|
1490 |
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value: 0.894
|
1491 |
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- task:
|
1492 |
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type: Retrieval
|
1493 |
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dataset:
|
1494 |
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type: webis-touche2020
|
1495 |
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name: MTEB Touche2020
|
1496 |
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config: default
|
1497 |
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split: test
|
1498 |
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revision: None
|
1499 |
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metrics:
|
1500 |
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- type: map_at_1
|
1501 |
+
value: 1.514
|
1502 |
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- type: map_at_10
|
1503 |
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value: 7.163
|
1504 |
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- type: map_at_100
|
1505 |
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value: 11.623999999999999
|
1506 |
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- type: map_at_1000
|
1507 |
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value: 13.062999999999999
|
1508 |
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|
1509 |
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value: 3.51
|
1510 |
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- type: map_at_5
|
1511 |
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value: 4.661
|
1512 |
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- type: mrr_at_1
|
1513 |
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value: 20.408
|
1514 |
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|
1515 |
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value: 33.993
|
1516 |
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|
1517 |
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value: 35.257
|
1518 |
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- type: mrr_at_1000
|
1519 |
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value: 35.313
|
1520 |
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- type: mrr_at_3
|
1521 |
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value: 30.272
|
1522 |
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|
1523 |
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value: 31.701
|
1524 |
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- type: ndcg_at_1
|
1525 |
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value: 18.367
|
1526 |
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- type: ndcg_at_10
|
1527 |
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value: 18.062
|
1528 |
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- type: ndcg_at_100
|
1529 |
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value: 28.441
|
1530 |
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- type: ndcg_at_1000
|
1531 |
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value: 40.748
|
1532 |
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- type: ndcg_at_3
|
1533 |
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value: 18.651999999999997
|
1534 |
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- type: ndcg_at_5
|
1535 |
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value: 17.055
|
1536 |
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- type: precision_at_1
|
1537 |
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value: 20.408
|
1538 |
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- type: precision_at_10
|
1539 |
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value: 17.551
|
1540 |
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- type: precision_at_100
|
1541 |
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value: 6.223999999999999
|
1542 |
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- type: precision_at_1000
|
1543 |
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value: 1.427
|
1544 |
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- type: precision_at_3
|
1545 |
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value: 20.408
|
1546 |
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- type: precision_at_5
|
1547 |
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value: 17.959
|
1548 |
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- type: recall_at_1
|
1549 |
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value: 1.514
|
1550 |
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- type: recall_at_10
|
1551 |
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value: 13.447000000000001
|
1552 |
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- type: recall_at_100
|
1553 |
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value: 39.77
|
1554 |
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- type: recall_at_1000
|
1555 |
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value: 76.95
|
1556 |
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- type: recall_at_3
|
1557 |
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value: 4.806
|
1558 |
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- type: recall_at_5
|
1559 |
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value: 6.873
|
1560 |
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- task:
|
1561 |
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type: Classification
|
1562 |
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dataset:
|
1563 |
+
type: mteb/toxic_conversations_50k
|
1564 |
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name: MTEB ToxicConversationsClassification
|
1565 |
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config: default
|
1566 |
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split: test
|
1567 |
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revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
1568 |
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metrics:
|
1569 |
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- type: accuracy
|
1570 |
+
value: 65.53179999999999
|
1571 |
+
- type: ap
|
1572 |
+
value: 11.504743595308318
|
1573 |
+
- type: f1
|
1574 |
+
value: 49.74264614001562
|
1575 |
+
- task:
|
1576 |
+
type: Classification
|
1577 |
+
dataset:
|
1578 |
+
type: mteb/tweet_sentiment_extraction
|
1579 |
+
name: MTEB TweetSentimentExtractionClassification
|
1580 |
+
config: default
|
1581 |
+
split: test
|
1582 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
1583 |
+
metrics:
|
1584 |
+
- type: accuracy
|
1585 |
+
value: 56.47425014148275
|
1586 |
+
- type: f1
|
1587 |
+
value: 56.555750746223346
|
1588 |
+
- task:
|
1589 |
+
type: Clustering
|
1590 |
+
dataset:
|
1591 |
+
type: mteb/twentynewsgroups-clustering
|
1592 |
+
name: MTEB TwentyNewsgroupsClustering
|
1593 |
+
config: default
|
1594 |
+
split: test
|
1595 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
1596 |
+
metrics:
|
1597 |
+
- type: v_measure
|
1598 |
+
value: 39.27004599453324
|
1599 |
+
- task:
|
1600 |
+
type: PairClassification
|
1601 |
+
dataset:
|
1602 |
+
type: mteb/twittersemeval2015-pairclassification
|
1603 |
+
name: MTEB TwitterSemEval2015
|
1604 |
+
config: default
|
1605 |
+
split: test
|
1606 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
1607 |
+
metrics:
|
1608 |
+
- type: cos_sim_accuracy
|
1609 |
+
value: 84.47875067056088
|
1610 |
+
- type: cos_sim_ap
|
1611 |
+
value: 68.630858164926
|
1612 |
+
- type: cos_sim_f1
|
1613 |
+
value: 64.5112402121748
|
1614 |
+
- type: cos_sim_precision
|
1615 |
+
value: 61.87015503875969
|
1616 |
+
- type: cos_sim_recall
|
1617 |
+
value: 67.38786279683377
|
1618 |
+
- type: dot_accuracy
|
1619 |
+
value: 77.68969422423557
|
1620 |
+
- type: dot_ap
|
1621 |
+
value: 37.28838556128439
|
1622 |
+
- type: dot_f1
|
1623 |
+
value: 43.27918525376652
|
1624 |
+
- type: dot_precision
|
1625 |
+
value: 31.776047460140898
|
1626 |
+
- type: dot_recall
|
1627 |
+
value: 67.83641160949868
|
1628 |
+
- type: euclidean_accuracy
|
1629 |
+
value: 82.67866722298385
|
1630 |
+
- type: euclidean_ap
|
1631 |
+
value: 62.72011158877603
|
1632 |
+
- type: euclidean_f1
|
1633 |
+
value: 60.39579770339605
|
1634 |
+
- type: euclidean_precision
|
1635 |
+
value: 56.23293903548681
|
1636 |
+
- type: euclidean_recall
|
1637 |
+
value: 65.22427440633246
|
1638 |
+
- type: manhattan_accuracy
|
1639 |
+
value: 82.67866722298385
|
1640 |
+
- type: manhattan_ap
|
1641 |
+
value: 62.80364769571995
|
1642 |
+
- type: manhattan_f1
|
1643 |
+
value: 60.413827282864574
|
1644 |
+
- type: manhattan_precision
|
1645 |
+
value: 56.94931090866619
|
1646 |
+
- type: manhattan_recall
|
1647 |
+
value: 64.32717678100263
|
1648 |
+
- type: max_accuracy
|
1649 |
+
value: 84.47875067056088
|
1650 |
+
- type: max_ap
|
1651 |
+
value: 68.630858164926
|
1652 |
+
- type: max_f1
|
1653 |
+
value: 64.5112402121748
|
1654 |
+
- task:
|
1655 |
+
type: PairClassification
|
1656 |
+
dataset:
|
1657 |
+
type: mteb/twitterurlcorpus-pairclassification
|
1658 |
+
name: MTEB TwitterURLCorpus
|
1659 |
+
config: default
|
1660 |
+
split: test
|
1661 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
1662 |
+
metrics:
|
1663 |
+
- type: cos_sim_accuracy
|
1664 |
+
value: 88.4192959987581
|
1665 |
+
- type: cos_sim_ap
|
1666 |
+
value: 84.81803796578367
|
1667 |
+
- type: cos_sim_f1
|
1668 |
+
value: 77.1643709825528
|
1669 |
+
- type: cos_sim_precision
|
1670 |
+
value: 73.77958839643183
|
1671 |
+
- type: cos_sim_recall
|
1672 |
+
value: 80.874653526332
|
1673 |
+
- type: dot_accuracy
|
1674 |
+
value: 81.99441145651414
|
1675 |
+
- type: dot_ap
|
1676 |
+
value: 67.908510950511
|
1677 |
+
- type: dot_f1
|
1678 |
+
value: 64.4734255193656
|
1679 |
+
- type: dot_precision
|
1680 |
+
value: 56.120935539075866
|
1681 |
+
- type: dot_recall
|
1682 |
+
value: 75.74684323991376
|
1683 |
+
- type: euclidean_accuracy
|
1684 |
+
value: 82.67163426087632
|
1685 |
+
- type: euclidean_ap
|
1686 |
+
value: 70.1466353903414
|
1687 |
+
- type: euclidean_f1
|
1688 |
+
value: 62.686024087617795
|
1689 |
+
- type: euclidean_precision
|
1690 |
+
value: 59.42738875474301
|
1691 |
+
- type: euclidean_recall
|
1692 |
+
value: 66.32275947028026
|
1693 |
+
- type: manhattan_accuracy
|
1694 |
+
value: 82.6483486630186
|
1695 |
+
- type: manhattan_ap
|
1696 |
+
value: 70.12958345267741
|
1697 |
+
- type: manhattan_f1
|
1698 |
+
value: 62.5966218150587
|
1699 |
+
- type: manhattan_precision
|
1700 |
+
value: 58.47820272800214
|
1701 |
+
- type: manhattan_recall
|
1702 |
+
value: 67.33908222975053
|
1703 |
+
- type: max_accuracy
|
1704 |
+
value: 88.4192959987581
|
1705 |
+
- type: max_ap
|
1706 |
+
value: 84.81803796578367
|
1707 |
+
- type: max_f1
|
1708 |
+
value: 77.1643709825528
|
1709 |
+
---
|
1710 |
---
|
1711 |
|
1712 |
<br><br>
|