Commit
•
7a3937a
1
Parent(s):
777c3ef
Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,2803 @@
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---
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license: apache-2.0
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1 |
---
|
2 |
license: apache-2.0
|
3 |
+
tags:
|
4 |
+
- mteb
|
5 |
+
- arctic
|
6 |
+
- arctic-embed
|
7 |
+
model-index:
|
8 |
+
- name: med
|
9 |
+
results:
|
10 |
+
- task:
|
11 |
+
type: Classification
|
12 |
+
dataset:
|
13 |
+
type: mteb/amazon_counterfactual
|
14 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
15 |
+
config: en
|
16 |
+
split: test
|
17 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
18 |
+
metrics:
|
19 |
+
- type: accuracy
|
20 |
+
value: 74.80597014925374
|
21 |
+
- type: ap
|
22 |
+
value: 37.911466766189875
|
23 |
+
- type: f1
|
24 |
+
value: 68.88606927542106
|
25 |
+
- task:
|
26 |
+
type: Classification
|
27 |
+
dataset:
|
28 |
+
type: mteb/amazon_polarity
|
29 |
+
name: MTEB AmazonPolarityClassification
|
30 |
+
config: default
|
31 |
+
split: test
|
32 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
33 |
+
metrics:
|
34 |
+
- type: accuracy
|
35 |
+
value: 78.402275
|
36 |
+
- type: ap
|
37 |
+
value: 73.03294793248114
|
38 |
+
- type: f1
|
39 |
+
value: 78.3147786132161
|
40 |
+
- task:
|
41 |
+
type: Classification
|
42 |
+
dataset:
|
43 |
+
type: mteb/amazon_reviews_multi
|
44 |
+
name: MTEB AmazonReviewsClassification (en)
|
45 |
+
config: en
|
46 |
+
split: test
|
47 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
48 |
+
metrics:
|
49 |
+
- type: accuracy
|
50 |
+
value: 36.717999999999996
|
51 |
+
- type: f1
|
52 |
+
value: 35.918044248787766
|
53 |
+
- task:
|
54 |
+
type: Retrieval
|
55 |
+
dataset:
|
56 |
+
type: mteb/arguana
|
57 |
+
name: MTEB ArguAna
|
58 |
+
config: default
|
59 |
+
split: test
|
60 |
+
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
|
61 |
+
metrics:
|
62 |
+
- type: map_at_1
|
63 |
+
value: 34.495
|
64 |
+
- type: map_at_10
|
65 |
+
value: 50.236000000000004
|
66 |
+
- type: map_at_100
|
67 |
+
value: 50.944
|
68 |
+
- type: map_at_1000
|
69 |
+
value: 50.94499999999999
|
70 |
+
- type: map_at_3
|
71 |
+
value: 45.341
|
72 |
+
- type: map_at_5
|
73 |
+
value: 48.286
|
74 |
+
- type: mrr_at_1
|
75 |
+
value: 35.135
|
76 |
+
- type: mrr_at_10
|
77 |
+
value: 50.471
|
78 |
+
- type: mrr_at_100
|
79 |
+
value: 51.185
|
80 |
+
- type: mrr_at_1000
|
81 |
+
value: 51.187000000000005
|
82 |
+
- type: mrr_at_3
|
83 |
+
value: 45.602
|
84 |
+
- type: mrr_at_5
|
85 |
+
value: 48.468
|
86 |
+
- type: ndcg_at_1
|
87 |
+
value: 34.495
|
88 |
+
- type: ndcg_at_10
|
89 |
+
value: 59.086000000000006
|
90 |
+
- type: ndcg_at_100
|
91 |
+
value: 61.937
|
92 |
+
- type: ndcg_at_1000
|
93 |
+
value: 61.966
|
94 |
+
- type: ndcg_at_3
|
95 |
+
value: 49.062
|
96 |
+
- type: ndcg_at_5
|
97 |
+
value: 54.367
|
98 |
+
- type: precision_at_1
|
99 |
+
value: 34.495
|
100 |
+
- type: precision_at_10
|
101 |
+
value: 8.734
|
102 |
+
- type: precision_at_100
|
103 |
+
value: 0.9939999999999999
|
104 |
+
- type: precision_at_1000
|
105 |
+
value: 0.1
|
106 |
+
- type: precision_at_3
|
107 |
+
value: 19.962
|
108 |
+
- type: precision_at_5
|
109 |
+
value: 14.552000000000001
|
110 |
+
- type: recall_at_1
|
111 |
+
value: 34.495
|
112 |
+
- type: recall_at_10
|
113 |
+
value: 87.33999999999999
|
114 |
+
- type: recall_at_100
|
115 |
+
value: 99.431
|
116 |
+
- type: recall_at_1000
|
117 |
+
value: 99.644
|
118 |
+
- type: recall_at_3
|
119 |
+
value: 59.885999999999996
|
120 |
+
- type: recall_at_5
|
121 |
+
value: 72.76
|
122 |
+
- task:
|
123 |
+
type: Clustering
|
124 |
+
dataset:
|
125 |
+
type: mteb/arxiv-clustering-p2p
|
126 |
+
name: MTEB ArxivClusteringP2P
|
127 |
+
config: default
|
128 |
+
split: test
|
129 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
130 |
+
metrics:
|
131 |
+
- type: v_measure
|
132 |
+
value: 47.46440874635501
|
133 |
+
- task:
|
134 |
+
type: Clustering
|
135 |
+
dataset:
|
136 |
+
type: mteb/arxiv-clustering-s2s
|
137 |
+
name: MTEB ArxivClusteringS2S
|
138 |
+
config: default
|
139 |
+
split: test
|
140 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
141 |
+
metrics:
|
142 |
+
- type: v_measure
|
143 |
+
value: 38.28720154213723
|
144 |
+
- task:
|
145 |
+
type: Reranking
|
146 |
+
dataset:
|
147 |
+
type: mteb/askubuntudupquestions-reranking
|
148 |
+
name: MTEB AskUbuntuDupQuestions
|
149 |
+
config: default
|
150 |
+
split: test
|
151 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
152 |
+
metrics:
|
153 |
+
- type: map
|
154 |
+
value: 60.34614226394902
|
155 |
+
- type: mrr
|
156 |
+
value: 75.05628105351096
|
157 |
+
- task:
|
158 |
+
type: STS
|
159 |
+
dataset:
|
160 |
+
type: mteb/biosses-sts
|
161 |
+
name: MTEB BIOSSES
|
162 |
+
config: default
|
163 |
+
split: test
|
164 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
165 |
+
metrics:
|
166 |
+
- type: cos_sim_pearson
|
167 |
+
value: 87.41072716728198
|
168 |
+
- type: cos_sim_spearman
|
169 |
+
value: 86.34534093114372
|
170 |
+
- type: euclidean_pearson
|
171 |
+
value: 85.34009667750838
|
172 |
+
- type: euclidean_spearman
|
173 |
+
value: 86.34534093114372
|
174 |
+
- type: manhattan_pearson
|
175 |
+
value: 85.2158833586889
|
176 |
+
- type: manhattan_spearman
|
177 |
+
value: 86.60920236509224
|
178 |
+
- task:
|
179 |
+
type: Classification
|
180 |
+
dataset:
|
181 |
+
type: mteb/banking77
|
182 |
+
name: MTEB Banking77Classification
|
183 |
+
config: default
|
184 |
+
split: test
|
185 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
186 |
+
metrics:
|
187 |
+
- type: accuracy
|
188 |
+
value: 80.06493506493507
|
189 |
+
- type: f1
|
190 |
+
value: 79.28108600339833
|
191 |
+
- task:
|
192 |
+
type: Clustering
|
193 |
+
dataset:
|
194 |
+
type: jinaai/big-patent-clustering
|
195 |
+
name: MTEB BigPatentClustering
|
196 |
+
config: default
|
197 |
+
split: test
|
198 |
+
revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
|
199 |
+
metrics:
|
200 |
+
- type: v_measure
|
201 |
+
value: 20.545049432417287
|
202 |
+
- task:
|
203 |
+
type: Clustering
|
204 |
+
dataset:
|
205 |
+
type: mteb/biorxiv-clustering-p2p
|
206 |
+
name: MTEB BiorxivClusteringP2P
|
207 |
+
config: default
|
208 |
+
split: test
|
209 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
210 |
+
metrics:
|
211 |
+
- type: v_measure
|
212 |
+
value: 37.54369718479804
|
213 |
+
- task:
|
214 |
+
type: Clustering
|
215 |
+
dataset:
|
216 |
+
type: mteb/biorxiv-clustering-s2s
|
217 |
+
name: MTEB BiorxivClusteringS2S
|
218 |
+
config: default
|
219 |
+
split: test
|
220 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
221 |
+
metrics:
|
222 |
+
- type: v_measure
|
223 |
+
value: 32.64941588219162
|
224 |
+
- task:
|
225 |
+
type: Retrieval
|
226 |
+
dataset:
|
227 |
+
type: mteb/cqadupstack-android
|
228 |
+
name: MTEB CQADupstackAndroidRetrieval
|
229 |
+
config: default
|
230 |
+
split: test
|
231 |
+
revision: f46a197baaae43b4f621051089b82a364682dfeb
|
232 |
+
metrics:
|
233 |
+
- type: map_at_1
|
234 |
+
value: 37.264
|
235 |
+
- type: map_at_10
|
236 |
+
value: 49.43
|
237 |
+
- type: map_at_100
|
238 |
+
value: 50.967
|
239 |
+
- type: map_at_1000
|
240 |
+
value: 51.08200000000001
|
241 |
+
- type: map_at_3
|
242 |
+
value: 45.742
|
243 |
+
- type: map_at_5
|
244 |
+
value: 47.764
|
245 |
+
- type: mrr_at_1
|
246 |
+
value: 44.921
|
247 |
+
- type: mrr_at_10
|
248 |
+
value: 54.879999999999995
|
249 |
+
- type: mrr_at_100
|
250 |
+
value: 55.525000000000006
|
251 |
+
- type: mrr_at_1000
|
252 |
+
value: 55.565
|
253 |
+
- type: mrr_at_3
|
254 |
+
value: 52.480000000000004
|
255 |
+
- type: mrr_at_5
|
256 |
+
value: 53.86
|
257 |
+
- type: ndcg_at_1
|
258 |
+
value: 44.921
|
259 |
+
- type: ndcg_at_10
|
260 |
+
value: 55.664
|
261 |
+
- type: ndcg_at_100
|
262 |
+
value: 60.488
|
263 |
+
- type: ndcg_at_1000
|
264 |
+
value: 62.138000000000005
|
265 |
+
- type: ndcg_at_3
|
266 |
+
value: 50.797000000000004
|
267 |
+
- type: ndcg_at_5
|
268 |
+
value: 52.94799999999999
|
269 |
+
- type: precision_at_1
|
270 |
+
value: 44.921
|
271 |
+
- type: precision_at_10
|
272 |
+
value: 10.587
|
273 |
+
- type: precision_at_100
|
274 |
+
value: 1.629
|
275 |
+
- type: precision_at_1000
|
276 |
+
value: 0.203
|
277 |
+
- type: precision_at_3
|
278 |
+
value: 24.034
|
279 |
+
- type: precision_at_5
|
280 |
+
value: 17.224999999999998
|
281 |
+
- type: recall_at_1
|
282 |
+
value: 37.264
|
283 |
+
- type: recall_at_10
|
284 |
+
value: 67.15
|
285 |
+
- type: recall_at_100
|
286 |
+
value: 86.811
|
287 |
+
- type: recall_at_1000
|
288 |
+
value: 97.172
|
289 |
+
- type: recall_at_3
|
290 |
+
value: 53.15800000000001
|
291 |
+
- type: recall_at_5
|
292 |
+
value: 59.116
|
293 |
+
- task:
|
294 |
+
type: Retrieval
|
295 |
+
dataset:
|
296 |
+
type: mteb/cqadupstack-english
|
297 |
+
name: MTEB CQADupstackEnglishRetrieval
|
298 |
+
config: default
|
299 |
+
split: test
|
300 |
+
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
|
301 |
+
metrics:
|
302 |
+
- type: map_at_1
|
303 |
+
value: 36.237
|
304 |
+
- type: map_at_10
|
305 |
+
value: 47.941
|
306 |
+
- type: map_at_100
|
307 |
+
value: 49.131
|
308 |
+
- type: map_at_1000
|
309 |
+
value: 49.26
|
310 |
+
- type: map_at_3
|
311 |
+
value: 44.561
|
312 |
+
- type: map_at_5
|
313 |
+
value: 46.28
|
314 |
+
- type: mrr_at_1
|
315 |
+
value: 45.605000000000004
|
316 |
+
- type: mrr_at_10
|
317 |
+
value: 54.039
|
318 |
+
- type: mrr_at_100
|
319 |
+
value: 54.653
|
320 |
+
- type: mrr_at_1000
|
321 |
+
value: 54.688
|
322 |
+
- type: mrr_at_3
|
323 |
+
value: 52.006
|
324 |
+
- type: mrr_at_5
|
325 |
+
value: 53.096
|
326 |
+
- type: ndcg_at_1
|
327 |
+
value: 45.605000000000004
|
328 |
+
- type: ndcg_at_10
|
329 |
+
value: 53.916
|
330 |
+
- type: ndcg_at_100
|
331 |
+
value: 57.745999999999995
|
332 |
+
- type: ndcg_at_1000
|
333 |
+
value: 59.492999999999995
|
334 |
+
- type: ndcg_at_3
|
335 |
+
value: 49.774
|
336 |
+
- type: ndcg_at_5
|
337 |
+
value: 51.434999999999995
|
338 |
+
- type: precision_at_1
|
339 |
+
value: 45.605000000000004
|
340 |
+
- type: precision_at_10
|
341 |
+
value: 10.229000000000001
|
342 |
+
- type: precision_at_100
|
343 |
+
value: 1.55
|
344 |
+
- type: precision_at_1000
|
345 |
+
value: 0.2
|
346 |
+
- type: precision_at_3
|
347 |
+
value: 24.098
|
348 |
+
- type: precision_at_5
|
349 |
+
value: 16.726
|
350 |
+
- type: recall_at_1
|
351 |
+
value: 36.237
|
352 |
+
- type: recall_at_10
|
353 |
+
value: 64.03
|
354 |
+
- type: recall_at_100
|
355 |
+
value: 80.423
|
356 |
+
- type: recall_at_1000
|
357 |
+
value: 91.03
|
358 |
+
- type: recall_at_3
|
359 |
+
value: 51.20400000000001
|
360 |
+
- type: recall_at_5
|
361 |
+
value: 56.298
|
362 |
+
- task:
|
363 |
+
type: Retrieval
|
364 |
+
dataset:
|
365 |
+
type: mteb/cqadupstack-gaming
|
366 |
+
name: MTEB CQADupstackGamingRetrieval
|
367 |
+
config: default
|
368 |
+
split: test
|
369 |
+
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
|
370 |
+
metrics:
|
371 |
+
- type: map_at_1
|
372 |
+
value: 47.278
|
373 |
+
- type: map_at_10
|
374 |
+
value: 59.757000000000005
|
375 |
+
- type: map_at_100
|
376 |
+
value: 60.67
|
377 |
+
- type: map_at_1000
|
378 |
+
value: 60.714
|
379 |
+
- type: map_at_3
|
380 |
+
value: 56.714
|
381 |
+
- type: map_at_5
|
382 |
+
value: 58.453
|
383 |
+
- type: mrr_at_1
|
384 |
+
value: 53.73
|
385 |
+
- type: mrr_at_10
|
386 |
+
value: 62.970000000000006
|
387 |
+
- type: mrr_at_100
|
388 |
+
value: 63.507999999999996
|
389 |
+
- type: mrr_at_1000
|
390 |
+
value: 63.53
|
391 |
+
- type: mrr_at_3
|
392 |
+
value: 60.909
|
393 |
+
- type: mrr_at_5
|
394 |
+
value: 62.172000000000004
|
395 |
+
- type: ndcg_at_1
|
396 |
+
value: 53.73
|
397 |
+
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398 |
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399 |
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|
400 |
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value: 68.394
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401 |
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|
402 |
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403 |
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404 |
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405 |
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406 |
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value: 62.617999999999995
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407 |
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408 |
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409 |
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|
410 |
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value: 10.056
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411 |
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|
412 |
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value: 1.265
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413 |
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414 |
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415 |
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416 |
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417 |
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418 |
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value: 17.743000000000002
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419 |
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420 |
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value: 47.278
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421 |
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422 |
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value: 76.86500000000001
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423 |
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424 |
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value: 91.582
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425 |
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426 |
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value: 97.583
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427 |
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- type: recall_at_3
|
428 |
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value: 64.443
|
429 |
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- type: recall_at_5
|
430 |
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value: 70.283
|
431 |
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|
432 |
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type: Retrieval
|
433 |
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dataset:
|
434 |
+
type: mteb/cqadupstack-gis
|
435 |
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name: MTEB CQADupstackGisRetrieval
|
436 |
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config: default
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437 |
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split: test
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438 |
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revision: 5003b3064772da1887988e05400cf3806fe491f2
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440 |
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441 |
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442 |
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443 |
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444 |
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445 |
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446 |
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447 |
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448 |
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450 |
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451 |
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452 |
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453 |
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454 |
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455 |
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456 |
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457 |
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458 |
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459 |
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460 |
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461 |
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462 |
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463 |
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464 |
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465 |
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466 |
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467 |
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468 |
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469 |
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470 |
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471 |
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472 |
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473 |
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474 |
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475 |
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476 |
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477 |
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478 |
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|
479 |
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value: 6.768000000000001
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480 |
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481 |
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value: 0.9690000000000001
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482 |
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- type: precision_at_1000
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483 |
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484 |
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485 |
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value: 16.761
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486 |
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487 |
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value: 11.593
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488 |
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489 |
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value: 29.702
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490 |
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491 |
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value: 59.082
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492 |
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- type: recall_at_100
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493 |
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value: 80.92
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494 |
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- type: recall_at_1000
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495 |
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value: 93.728
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496 |
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497 |
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value: 45.212
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498 |
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- type: recall_at_5
|
499 |
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value: 51.449
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500 |
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- task:
|
501 |
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type: Retrieval
|
502 |
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dataset:
|
503 |
+
type: mteb/cqadupstack-mathematica
|
504 |
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name: MTEB CQADupstackMathematicaRetrieval
|
505 |
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config: default
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506 |
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split: test
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507 |
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revision: 90fceea13679c63fe563ded68f3b6f06e50061de
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508 |
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metrics:
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509 |
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510 |
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value: 21.336
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511 |
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512 |
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513 |
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514 |
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515 |
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516 |
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517 |
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518 |
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519 |
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- type: map_at_5
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520 |
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value: 28.772
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521 |
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- type: mrr_at_1
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522 |
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value: 25.871
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523 |
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- type: mrr_at_10
|
524 |
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525 |
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526 |
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527 |
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528 |
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529 |
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530 |
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531 |
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532 |
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533 |
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534 |
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535 |
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|
536 |
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537 |
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|
538 |
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539 |
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540 |
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value: 43.725
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541 |
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542 |
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543 |
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544 |
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545 |
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546 |
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value: 25.871
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547 |
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|
548 |
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value: 6.4799999999999995
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549 |
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550 |
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551 |
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552 |
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553 |
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554 |
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value: 14.469000000000001
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555 |
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556 |
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value: 10.274
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557 |
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558 |
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value: 21.336
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559 |
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560 |
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value: 47.746
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561 |
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562 |
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value: 71.773
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563 |
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564 |
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value: 89.05199999999999
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565 |
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566 |
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value: 34.172999999999995
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567 |
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- type: recall_at_5
|
568 |
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value: 39.397999999999996
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569 |
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- task:
|
570 |
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type: Retrieval
|
571 |
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dataset:
|
572 |
+
type: mteb/cqadupstack-physics
|
573 |
+
name: MTEB CQADupstackPhysicsRetrieval
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574 |
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config: default
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575 |
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split: test
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576 |
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revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
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577 |
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metrics:
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578 |
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579 |
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value: 34.424
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580 |
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|
581 |
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582 |
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583 |
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584 |
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585 |
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586 |
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587 |
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value: 42.427
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588 |
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589 |
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value: 44.285000000000004
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590 |
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591 |
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value: 41.867
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592 |
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593 |
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594 |
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595 |
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596 |
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597 |
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598 |
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599 |
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600 |
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601 |
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602 |
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603 |
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604 |
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605 |
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606 |
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607 |
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608 |
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609 |
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610 |
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611 |
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612 |
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613 |
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614 |
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615 |
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616 |
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|
617 |
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value: 9.134
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618 |
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|
619 |
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value: 1.362
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620 |
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621 |
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622 |
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623 |
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value: 22.073
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624 |
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625 |
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value: 15.495999999999999
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626 |
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627 |
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value: 34.424
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628 |
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629 |
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value: 63.237
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630 |
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631 |
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632 |
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633 |
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634 |
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|
635 |
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value: 49.888
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636 |
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|
637 |
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value: 55.940999999999995
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638 |
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|
639 |
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|
640 |
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dataset:
|
641 |
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type: mteb/cqadupstack-programmers
|
642 |
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name: MTEB CQADupstackProgrammersRetrieval
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643 |
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config: default
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644 |
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645 |
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646 |
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metrics:
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647 |
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648 |
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value: 30.72
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649 |
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|
650 |
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651 |
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652 |
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653 |
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654 |
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655 |
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656 |
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657 |
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658 |
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659 |
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660 |
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661 |
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662 |
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663 |
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664 |
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665 |
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666 |
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667 |
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668 |
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669 |
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671 |
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673 |
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675 |
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677 |
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679 |
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681 |
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682 |
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683 |
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684 |
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685 |
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|
686 |
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value: 8.368
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687 |
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688 |
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689 |
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690 |
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691 |
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692 |
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693 |
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694 |
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695 |
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696 |
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697 |
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699 |
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700 |
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701 |
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702 |
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703 |
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704 |
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705 |
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|
706 |
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value: 51.426
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707 |
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|
708 |
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709 |
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dataset:
|
710 |
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type: mteb/cqadupstack
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711 |
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name: MTEB CQADupstackRetrieval
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712 |
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713 |
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714 |
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715 |
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718 |
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719 |
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720 |
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723 |
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724 |
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730 |
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731 |
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733 |
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734 |
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736 |
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738 |
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742 |
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743 |
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746 |
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747 |
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748 |
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749 |
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755 |
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756 |
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758 |
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759 |
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761 |
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766 |
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774 |
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775 |
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value: 50.99866666666666
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776 |
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- task:
|
777 |
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|
778 |
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dataset:
|
779 |
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type: mteb/cqadupstack-stats
|
780 |
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name: MTEB CQADupstackStatsRetrieval
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781 |
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787 |
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815 |
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816 |
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817 |
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819 |
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835 |
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841 |
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843 |
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844 |
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845 |
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846 |
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|
847 |
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dataset:
|
848 |
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type: mteb/cqadupstack-tex
|
849 |
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name: MTEB CQADupstackTexRetrieval
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850 |
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851 |
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852 |
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855 |
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856 |
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857 |
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886 |
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892 |
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894 |
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896 |
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913 |
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914 |
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915 |
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916 |
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dataset:
|
917 |
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type: mteb/cqadupstack-unix
|
918 |
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name: MTEB CQADupstackUnixRetrieval
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919 |
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925 |
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944 |
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945 |
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951 |
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953 |
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961 |
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962 |
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963 |
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964 |
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979 |
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980 |
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981 |
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982 |
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983 |
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|
984 |
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985 |
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dataset:
|
986 |
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type: mteb/cqadupstack-webmasters
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987 |
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name: MTEB CQADupstackWebmastersRetrieval
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988 |
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990 |
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991 |
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994 |
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995 |
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996 |
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997 |
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998 |
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999 |
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1000 |
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1004 |
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1006 |
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1007 |
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1008 |
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1009 |
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1010 |
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1011 |
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1012 |
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1014 |
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1017 |
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1020 |
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1023 |
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1037 |
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1038 |
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1042 |
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1050 |
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1051 |
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1052 |
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|
1053 |
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1054 |
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dataset:
|
1055 |
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type: mteb/cqadupstack-wordpress
|
1056 |
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name: MTEB CQADupstackWordpressRetrieval
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1057 |
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1058 |
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1059 |
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1063 |
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1101 |
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1119 |
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1120 |
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1121 |
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|
1122 |
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1123 |
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dataset:
|
1124 |
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type: mteb/climate-fever
|
1125 |
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name: MTEB ClimateFEVER
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1126 |
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1127 |
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1129 |
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1188 |
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1189 |
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1190 |
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|
1191 |
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1192 |
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dataset:
|
1193 |
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type: mteb/dbpedia
|
1194 |
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name: MTEB DBPedia
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1195 |
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1201 |
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1228 |
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1230 |
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1254 |
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1257 |
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1258 |
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1259 |
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|
1260 |
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|
1261 |
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|
1262 |
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1263 |
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1271 |
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1273 |
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1275 |
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1282 |
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1300 |
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1302 |
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1312 |
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1330 |
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1334 |
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1336 |
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1338 |
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1339 |
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1340 |
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1341 |
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1342 |
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1343 |
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1344 |
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1351 |
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1352 |
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1353 |
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1365 |
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1375 |
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1377 |
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1378 |
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1379 |
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1380 |
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1381 |
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1383 |
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1389 |
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1390 |
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1391 |
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1393 |
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1394 |
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1395 |
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1396 |
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1397 |
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1398 |
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1399 |
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value: 22.788
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1400 |
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1401 |
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1402 |
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1403 |
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1404 |
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1405 |
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1406 |
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1407 |
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1408 |
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1409 |
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1410 |
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|
1411 |
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1412 |
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dataset:
|
1413 |
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type: mteb/hotpotqa
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1414 |
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1415 |
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1416 |
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1418 |
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1419 |
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1420 |
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1421 |
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1422 |
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1423 |
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1424 |
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1426 |
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1428 |
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1430 |
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1431 |
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1434 |
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1436 |
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1438 |
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1439 |
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1440 |
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1442 |
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1444 |
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1445 |
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1446 |
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1447 |
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1448 |
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1449 |
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1450 |
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1451 |
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1452 |
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1454 |
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1456 |
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1458 |
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1460 |
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1462 |
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1464 |
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1465 |
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1470 |
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1471 |
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1472 |
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1473 |
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1475 |
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1477 |
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1478 |
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1479 |
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|
1480 |
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1481 |
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|
1482 |
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|
1497 |
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1498 |
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1499 |
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1500 |
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1502 |
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1504 |
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1505 |
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1506 |
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1507 |
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1510 |
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1514 |
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1516 |
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1517 |
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1518 |
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1519 |
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1520 |
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1521 |
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1522 |
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1528 |
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1529 |
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1530 |
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1531 |
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1532 |
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1533 |
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1534 |
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1535 |
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1536 |
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1537 |
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1538 |
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1540 |
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1541 |
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1542 |
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1543 |
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1544 |
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1545 |
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1546 |
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1547 |
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1548 |
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1549 |
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1550 |
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1551 |
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1552 |
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1553 |
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1554 |
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1555 |
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1556 |
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1558 |
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1559 |
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1560 |
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1561 |
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1562 |
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1563 |
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|
1564 |
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1565 |
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dataset:
|
1566 |
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type: mteb/mtop_domain
|
1567 |
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name: MTEB MTOPDomainClassification (en)
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1568 |
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1569 |
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1575 |
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1577 |
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1578 |
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|
1579 |
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1580 |
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1590 |
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|
1592 |
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|
1593 |
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name: MTEB MasakhaNEWSClassification (eng)
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1601 |
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1602 |
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1603 |
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1604 |
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dataset:
|
1605 |
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|
1606 |
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1613 |
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- task:
|
1614 |
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1615 |
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dataset:
|
1616 |
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type: masakhane/masakhanews
|
1617 |
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dataset:
|
1627 |
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|
1628 |
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name: MTEB MassiveIntentClassification (en)
|
1629 |
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config: en
|
1630 |
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|
1640 |
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|
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|
1662 |
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1664 |
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1673 |
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type: Reranking
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|
1675 |
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1755 |
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dataset:
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1757 |
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metrics:
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1764 |
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1790 |
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1792 |
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value: 43.685
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1802 |
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value: 9.962
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1803 |
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1804 |
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value: 1.174
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1806 |
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value: 0.121
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value: 24.961
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1810 |
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value: 17.352
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1812 |
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value: 39.117000000000004
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1813 |
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value: 64.364
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1821 |
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1822 |
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value: 73.573
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1823 |
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- task:
|
1824 |
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type: Classification
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1825 |
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dataset:
|
1826 |
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type: ag_news
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1827 |
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name: MTEB NewsClassification
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1828 |
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1829 |
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1834 |
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1835 |
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1836 |
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|
1837 |
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1838 |
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dataset:
|
1839 |
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type: GEM/opusparcus
|
1840 |
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name: MTEB OpusparcusPC (en)
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1841 |
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config: en
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1842 |
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1843 |
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1844 |
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|
1845 |
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1851 |
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1853 |
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1857 |
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1859 |
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1861 |
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1863 |
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1865 |
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1867 |
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1869 |
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1871 |
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1873 |
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1877 |
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1889 |
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1890 |
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1891 |
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- task:
|
1892 |
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1893 |
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dataset:
|
1894 |
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type: paws-x
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1895 |
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name: MTEB PawsX (en)
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1896 |
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1897 |
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split: test
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1898 |
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1899 |
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metrics:
|
1900 |
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|
1901 |
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value: 62
|
1902 |
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|
1903 |
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1904 |
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1906 |
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|
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1908 |
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|
1909 |
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1910 |
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|
1911 |
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|
1912 |
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1913 |
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|
1914 |
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1915 |
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|
1916 |
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1917 |
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|
1918 |
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|
1919 |
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|
1920 |
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- type: euclidean_accuracy
|
1921 |
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|
1922 |
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|
1923 |
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|
1924 |
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1925 |
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|
1926 |
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|
1927 |
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|
1928 |
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- type: euclidean_recall
|
1929 |
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value: 96.36163175303197
|
1930 |
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- type: manhattan_accuracy
|
1931 |
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value: 62
|
1932 |
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- type: manhattan_ap
|
1933 |
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value: 62.26223761507973
|
1934 |
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- type: manhattan_f1
|
1935 |
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|
1936 |
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- type: manhattan_precision
|
1937 |
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|
1938 |
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- type: manhattan_recall
|
1939 |
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|
1940 |
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- type: max_accuracy
|
1941 |
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value: 62
|
1942 |
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- type: max_ap
|
1943 |
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value: 62.26837791655737
|
1944 |
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- type: max_f1
|
1945 |
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value: 62.607449856733524
|
1946 |
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- task:
|
1947 |
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type: Retrieval
|
1948 |
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dataset:
|
1949 |
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type: mteb/quora
|
1950 |
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name: MTEB QuoraRetrieval
|
1951 |
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config: default
|
1952 |
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split: test
|
1953 |
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revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
|
1954 |
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metrics:
|
1955 |
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- type: map_at_1
|
1956 |
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value: 69.90899999999999
|
1957 |
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- type: map_at_10
|
1958 |
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value: 83.56700000000001
|
1959 |
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- type: map_at_100
|
1960 |
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value: 84.19200000000001
|
1961 |
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|
1962 |
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value: 84.212
|
1963 |
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- type: map_at_3
|
1964 |
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value: 80.658
|
1965 |
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- type: map_at_5
|
1966 |
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value: 82.473
|
1967 |
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- type: mrr_at_1
|
1968 |
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value: 80.4
|
1969 |
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- type: mrr_at_10
|
1970 |
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value: 86.699
|
1971 |
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|
1972 |
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value: 86.798
|
1973 |
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- type: mrr_at_1000
|
1974 |
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value: 86.80099999999999
|
1975 |
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|
1976 |
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value: 85.677
|
1977 |
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- type: mrr_at_5
|
1978 |
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value: 86.354
|
1979 |
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- type: ndcg_at_1
|
1980 |
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value: 80.43
|
1981 |
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- type: ndcg_at_10
|
1982 |
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value: 87.41
|
1983 |
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- type: ndcg_at_100
|
1984 |
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value: 88.653
|
1985 |
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- type: ndcg_at_1000
|
1986 |
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value: 88.81599999999999
|
1987 |
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- type: ndcg_at_3
|
1988 |
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value: 84.516
|
1989 |
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|
1990 |
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value: 86.068
|
1991 |
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- type: precision_at_1
|
1992 |
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value: 80.43
|
1993 |
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- type: precision_at_10
|
1994 |
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value: 13.234000000000002
|
1995 |
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- type: precision_at_100
|
1996 |
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value: 1.513
|
1997 |
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- type: precision_at_1000
|
1998 |
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value: 0.156
|
1999 |
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- type: precision_at_3
|
2000 |
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value: 36.93
|
2001 |
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- type: precision_at_5
|
2002 |
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value: 24.26
|
2003 |
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- type: recall_at_1
|
2004 |
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value: 69.90899999999999
|
2005 |
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- type: recall_at_10
|
2006 |
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value: 94.687
|
2007 |
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- type: recall_at_100
|
2008 |
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value: 98.96000000000001
|
2009 |
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- type: recall_at_1000
|
2010 |
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value: 99.79599999999999
|
2011 |
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- type: recall_at_3
|
2012 |
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value: 86.25699999999999
|
2013 |
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- type: recall_at_5
|
2014 |
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value: 90.70700000000001
|
2015 |
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- task:
|
2016 |
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type: Clustering
|
2017 |
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dataset:
|
2018 |
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type: mteb/reddit-clustering
|
2019 |
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name: MTEB RedditClustering
|
2020 |
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config: default
|
2021 |
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split: test
|
2022 |
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|
2023 |
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metrics:
|
2024 |
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- type: v_measure
|
2025 |
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value: 46.02256865360266
|
2026 |
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- task:
|
2027 |
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type: Clustering
|
2028 |
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dataset:
|
2029 |
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type: mteb/reddit-clustering-p2p
|
2030 |
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name: MTEB RedditClusteringP2P
|
2031 |
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config: default
|
2032 |
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split: test
|
2033 |
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|
2034 |
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metrics:
|
2035 |
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|
2036 |
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value: 62.43157528757563
|
2037 |
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- task:
|
2038 |
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type: Retrieval
|
2039 |
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dataset:
|
2040 |
+
type: mteb/scidocs
|
2041 |
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name: MTEB SCIDOCS
|
2042 |
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config: default
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2043 |
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split: test
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2044 |
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revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
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2045 |
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metrics:
|
2046 |
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- type: map_at_1
|
2047 |
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value: 5.093
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2048 |
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- type: map_at_10
|
2049 |
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value: 12.982
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2050 |
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2051 |
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value: 15.031
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2052 |
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- type: map_at_1000
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2053 |
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value: 15.334
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2054 |
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2055 |
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value: 9.339
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2056 |
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2057 |
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value: 11.183
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2058 |
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- type: mrr_at_1
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2059 |
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value: 25.1
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2060 |
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2061 |
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value: 36.257
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2062 |
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- type: mrr_at_100
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2063 |
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value: 37.351
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2064 |
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- type: mrr_at_1000
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2065 |
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value: 37.409
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2066 |
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- type: mrr_at_3
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2067 |
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value: 33.050000000000004
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2068 |
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- type: mrr_at_5
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2069 |
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value: 35.205
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2070 |
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- type: ndcg_at_1
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2071 |
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value: 25.1
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2072 |
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- type: ndcg_at_10
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2073 |
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value: 21.361
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2074 |
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- type: ndcg_at_100
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2075 |
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value: 29.396
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2076 |
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- type: ndcg_at_1000
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2077 |
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value: 34.849999999999994
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2078 |
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- type: ndcg_at_3
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2079 |
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value: 20.704
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2080 |
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- type: ndcg_at_5
|
2081 |
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value: 18.086
|
2082 |
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- type: precision_at_1
|
2083 |
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value: 25.1
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2084 |
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- type: precision_at_10
|
2085 |
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value: 10.94
|
2086 |
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- type: precision_at_100
|
2087 |
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value: 2.257
|
2088 |
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- type: precision_at_1000
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2089 |
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value: 0.358
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2090 |
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- type: precision_at_3
|
2091 |
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value: 19.467000000000002
|
2092 |
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- type: precision_at_5
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2093 |
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value: 15.98
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2094 |
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- type: recall_at_1
|
2095 |
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value: 5.093
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2096 |
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- type: recall_at_10
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2097 |
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value: 22.177
|
2098 |
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- type: recall_at_100
|
2099 |
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value: 45.842
|
2100 |
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- type: recall_at_1000
|
2101 |
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value: 72.598
|
2102 |
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- type: recall_at_3
|
2103 |
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value: 11.833
|
2104 |
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- type: recall_at_5
|
2105 |
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value: 16.173000000000002
|
2106 |
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- task:
|
2107 |
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type: STS
|
2108 |
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dataset:
|
2109 |
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type: mteb/sickr-sts
|
2110 |
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name: MTEB SICK-R
|
2111 |
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config: default
|
2112 |
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split: test
|
2113 |
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revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
|
2114 |
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metrics:
|
2115 |
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- type: cos_sim_pearson
|
2116 |
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value: 73.56535226754596
|
2117 |
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- type: cos_sim_spearman
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2118 |
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2119 |
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- type: euclidean_pearson
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2120 |
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value: 71.32425703470898
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2121 |
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- type: euclidean_spearman
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2122 |
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2123 |
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- type: manhattan_pearson
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2124 |
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2125 |
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- type: manhattan_spearman
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2126 |
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value: 69.27132577049578
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2127 |
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- task:
|
2128 |
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type: STS
|
2129 |
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dataset:
|
2130 |
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type: mteb/sts12-sts
|
2131 |
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name: MTEB STS12
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2132 |
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config: default
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2133 |
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split: test
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2134 |
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revision: a0d554a64d88156834ff5ae9920b964011b16384
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2135 |
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metrics:
|
2136 |
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- type: cos_sim_pearson
|
2137 |
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value: 69.66387868726018
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2138 |
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- type: cos_sim_spearman
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2139 |
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value: 67.85470749045027
|
2140 |
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- type: euclidean_pearson
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2141 |
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value: 66.62075098063795
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2142 |
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- type: euclidean_spearman
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2143 |
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2144 |
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- type: manhattan_pearson
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2145 |
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value: 66.61455061901262
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2146 |
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- type: manhattan_spearman
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2147 |
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value: 67.87229618498695
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2148 |
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- task:
|
2149 |
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type: STS
|
2150 |
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dataset:
|
2151 |
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type: mteb/sts13-sts
|
2152 |
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name: MTEB STS13
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2153 |
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config: default
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2154 |
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split: test
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2155 |
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revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
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2156 |
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metrics:
|
2157 |
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- type: cos_sim_pearson
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2158 |
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value: 75.65731331392575
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2159 |
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- type: cos_sim_spearman
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2160 |
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value: 77.48991626780108
|
2161 |
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- type: euclidean_pearson
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2162 |
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value: 77.19884738623692
|
2163 |
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- type: euclidean_spearman
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2164 |
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value: 77.48985836619045
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2165 |
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- type: manhattan_pearson
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2166 |
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value: 77.0656684243772
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2167 |
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- type: manhattan_spearman
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2168 |
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value: 77.30289226582691
|
2169 |
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- task:
|
2170 |
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type: STS
|
2171 |
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dataset:
|
2172 |
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type: mteb/sts14-sts
|
2173 |
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name: MTEB STS14
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2174 |
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config: default
|
2175 |
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split: test
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2176 |
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revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
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2177 |
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metrics:
|
2178 |
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- type: cos_sim_pearson
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2179 |
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value: 69.37003253666457
|
2180 |
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- type: cos_sim_spearman
|
2181 |
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value: 69.77157648098141
|
2182 |
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- type: euclidean_pearson
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2183 |
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value: 69.39543876030432
|
2184 |
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- type: euclidean_spearman
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2185 |
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value: 69.77157648098141
|
2186 |
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- type: manhattan_pearson
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2187 |
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value: 69.29901600459745
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2188 |
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- type: manhattan_spearman
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2189 |
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value: 69.65074167527128
|
2190 |
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- task:
|
2191 |
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type: STS
|
2192 |
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dataset:
|
2193 |
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type: mteb/sts15-sts
|
2194 |
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name: MTEB STS15
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2195 |
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config: default
|
2196 |
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split: test
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2197 |
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revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
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2198 |
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metrics:
|
2199 |
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- type: cos_sim_pearson
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2200 |
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value: 78.56777256540136
|
2201 |
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- type: cos_sim_spearman
|
2202 |
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value: 80.16458787843023
|
2203 |
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- type: euclidean_pearson
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2204 |
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value: 80.16475730686916
|
2205 |
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- type: euclidean_spearman
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2206 |
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value: 80.16458787843023
|
2207 |
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- type: manhattan_pearson
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2208 |
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value: 80.12814463670401
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2209 |
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- type: manhattan_spearman
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2210 |
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value: 80.1357907984809
|
2211 |
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- task:
|
2212 |
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type: STS
|
2213 |
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dataset:
|
2214 |
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type: mteb/sts16-sts
|
2215 |
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name: MTEB STS16
|
2216 |
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config: default
|
2217 |
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split: test
|
2218 |
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revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2219 |
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metrics:
|
2220 |
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- type: cos_sim_pearson
|
2221 |
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value: 76.09572350919031
|
2222 |
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- type: cos_sim_spearman
|
2223 |
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value: 77.94490233429326
|
2224 |
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- type: euclidean_pearson
|
2225 |
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value: 78.36595251203524
|
2226 |
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- type: euclidean_spearman
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2227 |
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|
2228 |
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- type: manhattan_pearson
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2229 |
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value: 78.41538768125166
|
2230 |
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- type: manhattan_spearman
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2231 |
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value: 78.01244379569542
|
2232 |
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- task:
|
2233 |
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type: STS
|
2234 |
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dataset:
|
2235 |
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type: mteb/sts17-crosslingual-sts
|
2236 |
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name: MTEB STS17 (en-en)
|
2237 |
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config: en-en
|
2238 |
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split: test
|
2239 |
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revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2240 |
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metrics:
|
2241 |
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- type: cos_sim_pearson
|
2242 |
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value: 80.7843552187951
|
2243 |
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- type: cos_sim_spearman
|
2244 |
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value: 82.28085055047386
|
2245 |
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- type: euclidean_pearson
|
2246 |
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value: 82.37373672515267
|
2247 |
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- type: euclidean_spearman
|
2248 |
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value: 82.28085055047386
|
2249 |
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- type: manhattan_pearson
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2250 |
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value: 82.39387241346917
|
2251 |
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- type: manhattan_spearman
|
2252 |
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value: 82.36503339515906
|
2253 |
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- task:
|
2254 |
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type: STS
|
2255 |
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dataset:
|
2256 |
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type: mteb/sts22-crosslingual-sts
|
2257 |
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name: MTEB STS22 (en)
|
2258 |
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config: en
|
2259 |
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split: test
|
2260 |
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revision: eea2b4fe26a775864c896887d910b76a8098ad3f
|
2261 |
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metrics:
|
2262 |
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- type: cos_sim_pearson
|
2263 |
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value: 68.29963929962095
|
2264 |
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- type: cos_sim_spearman
|
2265 |
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|
2266 |
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- type: euclidean_pearson
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2267 |
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value: 68.93524903869285
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2268 |
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- type: euclidean_spearman
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2269 |
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value: 67.96868942546051
|
2270 |
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- type: manhattan_pearson
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2271 |
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value: 68.79144468444811
|
2272 |
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- type: manhattan_spearman
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2273 |
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value: 67.69311483884324
|
2274 |
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- task:
|
2275 |
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type: STS
|
2276 |
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dataset:
|
2277 |
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type: mteb/stsbenchmark-sts
|
2278 |
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name: MTEB STSBenchmark
|
2279 |
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config: default
|
2280 |
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split: test
|
2281 |
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revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
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2282 |
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metrics:
|
2283 |
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- type: cos_sim_pearson
|
2284 |
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value: 72.84789696700685
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2285 |
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- type: cos_sim_spearman
|
2286 |
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value: 75.67875747588545
|
2287 |
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- type: euclidean_pearson
|
2288 |
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value: 75.07752300463038
|
2289 |
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- type: euclidean_spearman
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2290 |
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value: 75.67875747588545
|
2291 |
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- type: manhattan_pearson
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2292 |
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value: 74.97934248140928
|
2293 |
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- type: manhattan_spearman
|
2294 |
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value: 75.62525644178724
|
2295 |
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- task:
|
2296 |
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type: STS
|
2297 |
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dataset:
|
2298 |
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type: PhilipMay/stsb_multi_mt
|
2299 |
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name: MTEB STSBenchmarkMultilingualSTS (en)
|
2300 |
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config: en
|
2301 |
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split: test
|
2302 |
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revision: 93d57ef91790589e3ce9c365164337a8a78b7632
|
2303 |
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metrics:
|
2304 |
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- type: cos_sim_pearson
|
2305 |
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value: 72.84789702519309
|
2306 |
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- type: cos_sim_spearman
|
2307 |
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value: 75.67875747588545
|
2308 |
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- type: euclidean_pearson
|
2309 |
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value: 75.07752310061133
|
2310 |
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- type: euclidean_spearman
|
2311 |
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value: 75.67875747588545
|
2312 |
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- type: manhattan_pearson
|
2313 |
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value: 74.97934257159595
|
2314 |
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- type: manhattan_spearman
|
2315 |
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value: 75.62525644178724
|
2316 |
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- task:
|
2317 |
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type: Reranking
|
2318 |
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dataset:
|
2319 |
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type: mteb/scidocs-reranking
|
2320 |
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name: MTEB SciDocsRR
|
2321 |
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config: default
|
2322 |
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split: test
|
2323 |
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revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
2324 |
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metrics:
|
2325 |
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- type: map
|
2326 |
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value: 81.55557720431086
|
2327 |
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- type: mrr
|
2328 |
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value: 94.91178665198272
|
2329 |
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- task:
|
2330 |
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type: Retrieval
|
2331 |
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dataset:
|
2332 |
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type: mteb/scifact
|
2333 |
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name: MTEB SciFact
|
2334 |
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config: default
|
2335 |
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split: test
|
2336 |
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revision: 0228b52cf27578f30900b9e5271d331663a030d7
|
2337 |
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metrics:
|
2338 |
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- type: map_at_1
|
2339 |
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value: 59.260999999999996
|
2340 |
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- type: map_at_10
|
2341 |
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value: 69.36099999999999
|
2342 |
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- type: map_at_100
|
2343 |
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value: 69.868
|
2344 |
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- type: map_at_1000
|
2345 |
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value: 69.877
|
2346 |
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- type: map_at_3
|
2347 |
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value: 66.617
|
2348 |
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- type: map_at_5
|
2349 |
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value: 68.061
|
2350 |
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- type: mrr_at_1
|
2351 |
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value: 62.333000000000006
|
2352 |
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- type: mrr_at_10
|
2353 |
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value: 70.533
|
2354 |
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|
2355 |
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value: 70.966
|
2356 |
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- type: mrr_at_1000
|
2357 |
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value: 70.975
|
2358 |
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- type: mrr_at_3
|
2359 |
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value: 68.667
|
2360 |
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- type: mrr_at_5
|
2361 |
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value: 69.717
|
2362 |
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- type: ndcg_at_1
|
2363 |
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value: 62.333000000000006
|
2364 |
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- type: ndcg_at_10
|
2365 |
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value: 73.82300000000001
|
2366 |
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- type: ndcg_at_100
|
2367 |
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value: 76.122
|
2368 |
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- type: ndcg_at_1000
|
2369 |
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value: 76.374
|
2370 |
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- type: ndcg_at_3
|
2371 |
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value: 69.27499999999999
|
2372 |
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- type: ndcg_at_5
|
2373 |
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value: 71.33
|
2374 |
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- type: precision_at_1
|
2375 |
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value: 62.333000000000006
|
2376 |
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- type: precision_at_10
|
2377 |
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value: 9.8
|
2378 |
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- type: precision_at_100
|
2379 |
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value: 1.097
|
2380 |
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- type: precision_at_1000
|
2381 |
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value: 0.11199999999999999
|
2382 |
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- type: precision_at_3
|
2383 |
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value: 26.889000000000003
|
2384 |
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- type: precision_at_5
|
2385 |
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value: 17.599999999999998
|
2386 |
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- type: recall_at_1
|
2387 |
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value: 59.260999999999996
|
2388 |
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- type: recall_at_10
|
2389 |
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value: 86.2
|
2390 |
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- type: recall_at_100
|
2391 |
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value: 96.667
|
2392 |
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- type: recall_at_1000
|
2393 |
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value: 98.667
|
2394 |
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- type: recall_at_3
|
2395 |
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value: 74.006
|
2396 |
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- type: recall_at_5
|
2397 |
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value: 79.167
|
2398 |
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- task:
|
2399 |
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type: PairClassification
|
2400 |
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dataset:
|
2401 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
2402 |
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name: MTEB SprintDuplicateQuestions
|
2403 |
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config: default
|
2404 |
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split: test
|
2405 |
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revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2406 |
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metrics:
|
2407 |
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- type: cos_sim_accuracy
|
2408 |
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value: 99.81881188118813
|
2409 |
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- type: cos_sim_ap
|
2410 |
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value: 95.20169041096409
|
2411 |
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- type: cos_sim_f1
|
2412 |
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value: 90.76224129227664
|
2413 |
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- type: cos_sim_precision
|
2414 |
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value: 91.64118246687055
|
2415 |
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- type: cos_sim_recall
|
2416 |
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value: 89.9
|
2417 |
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- type: dot_accuracy
|
2418 |
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value: 99.81881188118813
|
2419 |
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- type: dot_ap
|
2420 |
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value: 95.20169041096409
|
2421 |
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- type: dot_f1
|
2422 |
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value: 90.76224129227664
|
2423 |
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- type: dot_precision
|
2424 |
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value: 91.64118246687055
|
2425 |
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- type: dot_recall
|
2426 |
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value: 89.9
|
2427 |
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- type: euclidean_accuracy
|
2428 |
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value: 99.81881188118813
|
2429 |
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- type: euclidean_ap
|
2430 |
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2431 |
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- type: euclidean_f1
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2432 |
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2435 |
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2436 |
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2437 |
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- type: manhattan_accuracy
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2438 |
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value: 99.81881188118813
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2439 |
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2441 |
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|
2445 |
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- type: manhattan_recall
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value: 90.2
|
2447 |
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- type: max_accuracy
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2448 |
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value: 99.81881188118813
|
2449 |
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- type: max_ap
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|
2451 |
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- type: max_f1
|
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|
2453 |
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- task:
|
2454 |
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type: Clustering
|
2455 |
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dataset:
|
2456 |
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type: mteb/stackexchange-clustering
|
2457 |
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name: MTEB StackExchangeClustering
|
2458 |
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config: default
|
2459 |
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split: test
|
2460 |
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revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
2461 |
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metrics:
|
2462 |
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- type: v_measure
|
2463 |
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value: 57.8638628701308
|
2464 |
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- task:
|
2465 |
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type: Clustering
|
2466 |
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dataset:
|
2467 |
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type: mteb/stackexchange-clustering-p2p
|
2468 |
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name: MTEB StackExchangeClusteringP2P
|
2469 |
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config: default
|
2470 |
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split: test
|
2471 |
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revision: 815ca46b2622cec33ccafc3735d572c266efdb44
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metrics:
|
2473 |
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- type: v_measure
|
2474 |
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value: 37.82028248106046
|
2475 |
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- task:
|
2476 |
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type: Reranking
|
2477 |
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dataset:
|
2478 |
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type: mteb/stackoverflowdupquestions-reranking
|
2479 |
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name: MTEB StackOverflowDupQuestions
|
2480 |
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config: default
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2481 |
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split: test
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2482 |
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revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
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metrics:
|
2484 |
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- type: map
|
2485 |
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value: 50.870860210170946
|
2486 |
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- type: mrr
|
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|
2489 |
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type: Summarization
|
2490 |
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dataset:
|
2491 |
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|
2492 |
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split: test
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|
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value: 31.60384207444685
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2499 |
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- type: cos_sim_spearman
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|
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2503 |
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- type: dot_spearman
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2505 |
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- task:
|
2506 |
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type: Retrieval
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2507 |
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dataset:
|
2508 |
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type: mteb/trec-covid
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2509 |
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name: MTEB TRECCOVID
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2510 |
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2511 |
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2512 |
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2513 |
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metrics:
|
2514 |
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2515 |
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value: 0.246
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2516 |
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2519 |
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- type: map_at_1000
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2523 |
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2524 |
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2525 |
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2526 |
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2527 |
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2528 |
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2529 |
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2533 |
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2534 |
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2536 |
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2538 |
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- type: ndcg_at_1
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2539 |
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2540 |
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2541 |
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2542 |
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- type: ndcg_at_100
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2543 |
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2544 |
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2545 |
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2546 |
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- type: ndcg_at_3
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2547 |
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value: 84.531
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2548 |
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- type: ndcg_at_5
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2549 |
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value: 84.777
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2550 |
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- type: precision_at_1
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2551 |
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value: 94
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2552 |
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- type: precision_at_10
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2553 |
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value: 84.6
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2554 |
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- type: precision_at_100
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2555 |
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value: 66.03999999999999
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2556 |
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- type: precision_at_1000
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2557 |
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value: 24.878
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2558 |
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- type: precision_at_3
|
2559 |
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value: 88.667
|
2560 |
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- type: precision_at_5
|
2561 |
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value: 89.60000000000001
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2562 |
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- type: recall_at_1
|
2563 |
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value: 0.246
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2564 |
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- type: recall_at_10
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2565 |
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value: 2.2079999999999997
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2566 |
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- type: recall_at_100
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2567 |
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value: 15.895999999999999
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2568 |
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- type: recall_at_1000
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2569 |
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value: 52.683
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2570 |
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- type: recall_at_3
|
2571 |
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value: 0.7040000000000001
|
2572 |
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- type: recall_at_5
|
2573 |
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value: 1.163
|
2574 |
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- task:
|
2575 |
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type: Retrieval
|
2576 |
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dataset:
|
2577 |
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type: mteb/touche2020
|
2578 |
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name: MTEB Touche2020
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2579 |
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config: default
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split: test
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2581 |
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2582 |
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metrics:
|
2583 |
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- type: map_at_1
|
2584 |
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value: 3.852
|
2585 |
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- type: map_at_10
|
2586 |
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value: 14.316
|
2587 |
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- type: map_at_100
|
2588 |
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value: 20.982
|
2589 |
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- type: map_at_1000
|
2590 |
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value: 22.58
|
2591 |
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- type: map_at_3
|
2592 |
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value: 7.767
|
2593 |
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- type: map_at_5
|
2594 |
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value: 10.321
|
2595 |
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- type: mrr_at_1
|
2596 |
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value: 51.019999999999996
|
2597 |
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- type: mrr_at_10
|
2598 |
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value: 66.365
|
2599 |
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- type: mrr_at_100
|
2600 |
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value: 66.522
|
2601 |
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- type: mrr_at_1000
|
2602 |
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value: 66.522
|
2603 |
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- type: mrr_at_3
|
2604 |
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value: 62.925
|
2605 |
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- type: mrr_at_5
|
2606 |
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value: 64.762
|
2607 |
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- type: ndcg_at_1
|
2608 |
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value: 46.939
|
2609 |
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- type: ndcg_at_10
|
2610 |
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value: 34.516999999999996
|
2611 |
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- type: ndcg_at_100
|
2612 |
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value: 44.25
|
2613 |
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- type: ndcg_at_1000
|
2614 |
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value: 54.899
|
2615 |
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- type: ndcg_at_3
|
2616 |
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value: 40.203
|
2617 |
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- type: ndcg_at_5
|
2618 |
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value: 37.004
|
2619 |
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- type: precision_at_1
|
2620 |
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value: 51.019999999999996
|
2621 |
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- type: precision_at_10
|
2622 |
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value: 29.796
|
2623 |
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- type: precision_at_100
|
2624 |
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value: 8.633000000000001
|
2625 |
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- type: precision_at_1000
|
2626 |
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value: 1.584
|
2627 |
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- type: precision_at_3
|
2628 |
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value: 40.816
|
2629 |
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- type: precision_at_5
|
2630 |
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value: 35.918
|
2631 |
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- type: recall_at_1
|
2632 |
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value: 3.852
|
2633 |
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- type: recall_at_10
|
2634 |
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value: 20.891000000000002
|
2635 |
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- type: recall_at_100
|
2636 |
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value: 52.428
|
2637 |
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- type: recall_at_1000
|
2638 |
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value: 84.34899999999999
|
2639 |
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- type: recall_at_3
|
2640 |
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value: 8.834
|
2641 |
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- type: recall_at_5
|
2642 |
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value: 12.909
|
2643 |
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- task:
|
2644 |
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type: Classification
|
2645 |
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dataset:
|
2646 |
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type: mteb/toxic_conversations_50k
|
2647 |
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name: MTEB ToxicConversationsClassification
|
2648 |
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config: default
|
2649 |
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split: test
|
2650 |
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|
2651 |
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metrics:
|
2652 |
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- type: accuracy
|
2653 |
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value: 64.7092
|
2654 |
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- type: ap
|
2655 |
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value: 11.972915012305819
|
2656 |
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- type: f1
|
2657 |
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value: 49.91050149892115
|
2658 |
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- task:
|
2659 |
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type: Classification
|
2660 |
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dataset:
|
2661 |
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type: mteb/tweet_sentiment_extraction
|
2662 |
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name: MTEB TweetSentimentExtractionClassification
|
2663 |
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config: default
|
2664 |
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split: test
|
2665 |
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revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2666 |
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metrics:
|
2667 |
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- type: accuracy
|
2668 |
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value: 56.737408036219584
|
2669 |
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- type: f1
|
2670 |
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value: 57.07235266246011
|
2671 |
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- task:
|
2672 |
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type: Clustering
|
2673 |
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dataset:
|
2674 |
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type: mteb/twentynewsgroups-clustering
|
2675 |
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name: MTEB TwentyNewsgroupsClustering
|
2676 |
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config: default
|
2677 |
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split: test
|
2678 |
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|
2679 |
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metrics:
|
2680 |
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- type: v_measure
|
2681 |
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value: 35.9147539025798
|
2682 |
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- task:
|
2683 |
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type: PairClassification
|
2684 |
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dataset:
|
2685 |
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type: mteb/twittersemeval2015-pairclassification
|
2686 |
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name: MTEB TwitterSemEval2015
|
2687 |
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config: default
|
2688 |
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split: test
|
2689 |
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revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
2690 |
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metrics:
|
2691 |
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|
2692 |
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value: 82.52369315133814
|
2693 |
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- type: cos_sim_ap
|
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value: 62.34858091376534
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2695 |
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value: 58.18225190839694
|
2697 |
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- type: cos_sim_precision
|
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value: 53.09098824553766
|
2699 |
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- type: cos_sim_recall
|
2700 |
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value: 64.35356200527704
|
2701 |
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- type: dot_accuracy
|
2702 |
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|
2703 |
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|
2704 |
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- type: dot_f1
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|
2707 |
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- type: dot_precision
|
2708 |
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|
2709 |
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- type: dot_recall
|
2710 |
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value: 64.35356200527704
|
2711 |
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- type: euclidean_accuracy
|
2712 |
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value: 82.52369315133814
|
2713 |
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- type: euclidean_ap
|
2714 |
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value: 62.34857756663386
|
2715 |
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- type: euclidean_f1
|
2716 |
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|
2717 |
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- type: euclidean_precision
|
2718 |
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|
2719 |
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- type: euclidean_recall
|
2720 |
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value: 64.35356200527704
|
2721 |
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- type: manhattan_accuracy
|
2722 |
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value: 82.49389044525243
|
2723 |
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- type: manhattan_ap
|
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2725 |
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- type: manhattan_f1
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2726 |
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|
2727 |
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- type: manhattan_precision
|
2728 |
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|
2729 |
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- type: manhattan_recall
|
2730 |
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value: 64.9868073878628
|
2731 |
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- type: max_accuracy
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2732 |
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|
2733 |
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- type: max_ap
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2734 |
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2735 |
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- type: max_f1
|
2736 |
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|
2737 |
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- task:
|
2738 |
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type: PairClassification
|
2739 |
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dataset:
|
2740 |
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type: mteb/twitterurlcorpus-pairclassification
|
2741 |
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name: MTEB TwitterURLCorpus
|
2742 |
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config: default
|
2743 |
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split: test
|
2744 |
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revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2745 |
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metrics:
|
2746 |
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|
2747 |
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value: 88.34555827220863
|
2748 |
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- type: cos_sim_ap
|
2749 |
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|
2750 |
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- type: cos_sim_f1
|
2751 |
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|
2752 |
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- type: cos_sim_precision
|
2753 |
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value: 72.21470150263978
|
2754 |
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- type: cos_sim_recall
|
2755 |
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value: 82.14505697566985
|
2756 |
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- type: dot_accuracy
|
2757 |
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|
2758 |
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- type: dot_ap
|
2759 |
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|
2760 |
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|
2761 |
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|
2762 |
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- type: dot_precision
|
2763 |
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|
2764 |
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- type: dot_recall
|
2765 |
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|
2766 |
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- type: euclidean_accuracy
|
2767 |
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|
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- type: euclidean_ap
|
2769 |
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|
2770 |
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- type: euclidean_f1
|
2771 |
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|
2772 |
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- type: euclidean_precision
|
2773 |
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|
2774 |
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- type: euclidean_recall
|
2775 |
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|
2776 |
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- type: manhattan_accuracy
|
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|
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|
2780 |
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- type: manhattan_f1
|
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|
2782 |
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- type: manhattan_precision
|
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|
2784 |
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- type: manhattan_recall
|
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|
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- type: max_accuracy
|
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|
2788 |
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- type: max_ap
|
2789 |
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|
2790 |
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- type: max_f1
|
2791 |
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value: 76.860456739428
|
2792 |
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- task:
|
2793 |
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type: Clustering
|
2794 |
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dataset:
|
2795 |
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type: jinaai/cities_wiki_clustering
|
2796 |
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name: MTEB WikiCitiesClustering
|
2797 |
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config: default
|
2798 |
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split: test
|
2799 |
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revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
|
2800 |
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metrics:
|
2801 |
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- type: v_measure
|
2802 |
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value: 85.5314389263015
|
2803 |
+
---
|