Add MTEB results
Browse filesAdd MTEB results for most tasks, excluding a few retrieval tasks because of limited resources. These might be added in future.
README.md
CHANGED
@@ -4,6 +4,1705 @@ tags:
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4 |
- sentence-transformers
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5 |
- feature-extraction
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6 |
- sentence-similarity
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|
7 |
---
|
8 |
|
9 |
# clip-ViT-B-32
|
|
|
4 |
- sentence-transformers
|
5 |
- feature-extraction
|
6 |
- sentence-similarity
|
7 |
+
- mteb
|
8 |
+
model-index:
|
9 |
+
- name: clip-ViT-B-32
|
10 |
+
results:
|
11 |
+
- task:
|
12 |
+
type: Classification
|
13 |
+
dataset:
|
14 |
+
type: mteb/amazon_counterfactual
|
15 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
16 |
+
config: en
|
17 |
+
split: test
|
18 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
19 |
+
metrics:
|
20 |
+
- type: accuracy
|
21 |
+
value: 57.999999999999986
|
22 |
+
- type: ap
|
23 |
+
value: 23.966099106216358
|
24 |
+
- type: f1
|
25 |
+
value: 52.8203944454417
|
26 |
+
- task:
|
27 |
+
type: Classification
|
28 |
+
dataset:
|
29 |
+
type: mteb/amazon_polarity
|
30 |
+
name: MTEB AmazonPolarityClassification
|
31 |
+
config: default
|
32 |
+
split: test
|
33 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
34 |
+
metrics:
|
35 |
+
- type: accuracy
|
36 |
+
value: 62.366
|
37 |
+
- type: ap
|
38 |
+
value: 57.98090324593318
|
39 |
+
- type: f1
|
40 |
+
value: 61.62762218315074
|
41 |
+
- task:
|
42 |
+
type: Classification
|
43 |
+
dataset:
|
44 |
+
type: mteb/amazon_reviews_multi
|
45 |
+
name: MTEB AmazonReviewsClassification (en)
|
46 |
+
config: en
|
47 |
+
split: test
|
48 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
49 |
+
metrics:
|
50 |
+
- type: accuracy
|
51 |
+
value: 28.584
|
52 |
+
- type: f1
|
53 |
+
value: 28.463306116150783
|
54 |
+
- task:
|
55 |
+
type: Retrieval
|
56 |
+
dataset:
|
57 |
+
type: arguana
|
58 |
+
name: MTEB ArguAna
|
59 |
+
config: default
|
60 |
+
split: test
|
61 |
+
revision: None
|
62 |
+
metrics:
|
63 |
+
- type: map_at_1
|
64 |
+
value: 6.259
|
65 |
+
- type: map_at_10
|
66 |
+
value: 11.542
|
67 |
+
- type: map_at_100
|
68 |
+
value: 12.859000000000002
|
69 |
+
- type: map_at_1000
|
70 |
+
value: 12.966
|
71 |
+
- type: map_at_3
|
72 |
+
value: 9.128
|
73 |
+
- type: map_at_5
|
74 |
+
value: 10.262
|
75 |
+
- type: mrr_at_1
|
76 |
+
value: 6.259
|
77 |
+
- type: mrr_at_10
|
78 |
+
value: 11.536
|
79 |
+
- type: mrr_at_100
|
80 |
+
value: 12.859000000000002
|
81 |
+
- type: mrr_at_1000
|
82 |
+
value: 12.967
|
83 |
+
- type: mrr_at_3
|
84 |
+
value: 9.128
|
85 |
+
- type: mrr_at_5
|
86 |
+
value: 10.262
|
87 |
+
- type: ndcg_at_1
|
88 |
+
value: 6.259
|
89 |
+
- type: ndcg_at_10
|
90 |
+
value: 15.35
|
91 |
+
- type: ndcg_at_100
|
92 |
+
value: 22.107
|
93 |
+
- type: ndcg_at_1000
|
94 |
+
value: 25.355
|
95 |
+
- type: ndcg_at_3
|
96 |
+
value: 10.172
|
97 |
+
- type: ndcg_at_5
|
98 |
+
value: 12.22
|
99 |
+
- type: precision_at_1
|
100 |
+
value: 6.259
|
101 |
+
- type: precision_at_10
|
102 |
+
value: 2.795
|
103 |
+
- type: precision_at_100
|
104 |
+
value: 0.603
|
105 |
+
- type: precision_at_1000
|
106 |
+
value: 0.087
|
107 |
+
- type: precision_at_3
|
108 |
+
value: 4.41
|
109 |
+
- type: precision_at_5
|
110 |
+
value: 3.642
|
111 |
+
- type: recall_at_1
|
112 |
+
value: 6.259
|
113 |
+
- type: recall_at_10
|
114 |
+
value: 27.951999999999998
|
115 |
+
- type: recall_at_100
|
116 |
+
value: 60.313
|
117 |
+
- type: recall_at_1000
|
118 |
+
value: 86.771
|
119 |
+
- type: recall_at_3
|
120 |
+
value: 13.229
|
121 |
+
- type: recall_at_5
|
122 |
+
value: 18.208
|
123 |
+
- task:
|
124 |
+
type: Clustering
|
125 |
+
dataset:
|
126 |
+
type: mteb/arxiv-clustering-p2p
|
127 |
+
name: MTEB ArxivClusteringP2P
|
128 |
+
config: default
|
129 |
+
split: test
|
130 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
131 |
+
metrics:
|
132 |
+
- type: v_measure
|
133 |
+
value: 30.95753257205936
|
134 |
+
- task:
|
135 |
+
type: Clustering
|
136 |
+
dataset:
|
137 |
+
type: mteb/arxiv-clustering-s2s
|
138 |
+
name: MTEB ArxivClusteringS2S
|
139 |
+
config: default
|
140 |
+
split: test
|
141 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
142 |
+
metrics:
|
143 |
+
- type: v_measure
|
144 |
+
value: 26.586511396557583
|
145 |
+
- task:
|
146 |
+
type: Reranking
|
147 |
+
dataset:
|
148 |
+
type: mteb/askubuntudupquestions-reranking
|
149 |
+
name: MTEB AskUbuntuDupQuestions
|
150 |
+
config: default
|
151 |
+
split: test
|
152 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
153 |
+
metrics:
|
154 |
+
- type: map
|
155 |
+
value: 51.090393666506415
|
156 |
+
- type: mrr
|
157 |
+
value: 65.19412566503979
|
158 |
+
- task:
|
159 |
+
type: STS
|
160 |
+
dataset:
|
161 |
+
type: mteb/biosses-sts
|
162 |
+
name: MTEB BIOSSES
|
163 |
+
config: default
|
164 |
+
split: test
|
165 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
166 |
+
metrics:
|
167 |
+
- type: cos_sim_pearson
|
168 |
+
value: 69.9163188743249
|
169 |
+
- type: cos_sim_spearman
|
170 |
+
value: 64.1345938803495
|
171 |
+
- type: euclidean_pearson
|
172 |
+
value: 67.36703723549599
|
173 |
+
- type: euclidean_spearman
|
174 |
+
value: 63.067702100617005
|
175 |
+
- type: manhattan_pearson
|
176 |
+
value: 71.6901307580259
|
177 |
+
- type: manhattan_spearman
|
178 |
+
value: 67.04128661733944
|
179 |
+
- task:
|
180 |
+
type: Classification
|
181 |
+
dataset:
|
182 |
+
type: mteb/banking77
|
183 |
+
name: MTEB Banking77Classification
|
184 |
+
config: default
|
185 |
+
split: test
|
186 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
187 |
+
metrics:
|
188 |
+
- type: accuracy
|
189 |
+
value: 73.22402597402598
|
190 |
+
- type: f1
|
191 |
+
value: 73.12739303105114
|
192 |
+
- task:
|
193 |
+
type: Clustering
|
194 |
+
dataset:
|
195 |
+
type: mteb/biorxiv-clustering-p2p
|
196 |
+
name: MTEB BiorxivClusteringP2P
|
197 |
+
config: default
|
198 |
+
split: test
|
199 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
200 |
+
metrics:
|
201 |
+
- type: v_measure
|
202 |
+
value: 28.97385566120484
|
203 |
+
- task:
|
204 |
+
type: Clustering
|
205 |
+
dataset:
|
206 |
+
type: mteb/biorxiv-clustering-s2s
|
207 |
+
name: MTEB BiorxivClusteringS2S
|
208 |
+
config: default
|
209 |
+
split: test
|
210 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
211 |
+
metrics:
|
212 |
+
- type: v_measure
|
213 |
+
value: 27.08579813861177
|
214 |
+
- task:
|
215 |
+
type: Retrieval
|
216 |
+
dataset:
|
217 |
+
type: BeIR/cqadupstack
|
218 |
+
name: MTEB CQADupstackAndroidRetrieval
|
219 |
+
config: default
|
220 |
+
split: test
|
221 |
+
revision: None
|
222 |
+
metrics:
|
223 |
+
- type: map_at_1
|
224 |
+
value: 7.106999999999999
|
225 |
+
- type: map_at_10
|
226 |
+
value: 11.797
|
227 |
+
- type: map_at_100
|
228 |
+
value: 12.6
|
229 |
+
- type: map_at_1000
|
230 |
+
value: 12.711
|
231 |
+
- type: map_at_3
|
232 |
+
value: 10.369
|
233 |
+
- type: map_at_5
|
234 |
+
value: 10.881
|
235 |
+
- type: mrr_at_1
|
236 |
+
value: 9.299
|
237 |
+
- type: mrr_at_10
|
238 |
+
value: 15.076
|
239 |
+
- type: mrr_at_100
|
240 |
+
value: 15.842
|
241 |
+
- type: mrr_at_1000
|
242 |
+
value: 15.928
|
243 |
+
- type: mrr_at_3
|
244 |
+
value: 13.4
|
245 |
+
- type: mrr_at_5
|
246 |
+
value: 14.044
|
247 |
+
- type: ndcg_at_1
|
248 |
+
value: 9.299
|
249 |
+
- type: ndcg_at_10
|
250 |
+
value: 15.21
|
251 |
+
- type: ndcg_at_100
|
252 |
+
value: 19.374
|
253 |
+
- type: ndcg_at_1000
|
254 |
+
value: 22.527
|
255 |
+
- type: ndcg_at_3
|
256 |
+
value: 12.383
|
257 |
+
- type: ndcg_at_5
|
258 |
+
value: 13.096
|
259 |
+
- type: precision_at_1
|
260 |
+
value: 9.299
|
261 |
+
- type: precision_at_10
|
262 |
+
value: 3.1620000000000004
|
263 |
+
- type: precision_at_100
|
264 |
+
value: 0.662
|
265 |
+
- type: precision_at_1000
|
266 |
+
value: 0.11800000000000001
|
267 |
+
- type: precision_at_3
|
268 |
+
value: 6.3420000000000005
|
269 |
+
- type: precision_at_5
|
270 |
+
value: 4.492
|
271 |
+
- type: recall_at_1
|
272 |
+
value: 7.106999999999999
|
273 |
+
- type: recall_at_10
|
274 |
+
value: 22.544
|
275 |
+
- type: recall_at_100
|
276 |
+
value: 41.002
|
277 |
+
- type: recall_at_1000
|
278 |
+
value: 63.67699999999999
|
279 |
+
- type: recall_at_3
|
280 |
+
value: 14.316999999999998
|
281 |
+
- type: recall_at_5
|
282 |
+
value: 16.367
|
283 |
+
- task:
|
284 |
+
type: Retrieval
|
285 |
+
dataset:
|
286 |
+
type: BeIR/cqadupstack
|
287 |
+
name: MTEB CQADupstackEnglishRetrieval
|
288 |
+
config: default
|
289 |
+
split: test
|
290 |
+
revision: None
|
291 |
+
metrics:
|
292 |
+
- type: map_at_1
|
293 |
+
value: 6.632000000000001
|
294 |
+
- type: map_at_10
|
295 |
+
value: 9.067
|
296 |
+
- type: map_at_100
|
297 |
+
value: 9.487
|
298 |
+
- type: map_at_1000
|
299 |
+
value: 9.563
|
300 |
+
- type: map_at_3
|
301 |
+
value: 8.344999999999999
|
302 |
+
- type: map_at_5
|
303 |
+
value: 8.742999999999999
|
304 |
+
- type: mrr_at_1
|
305 |
+
value: 8.599
|
306 |
+
- type: mrr_at_10
|
307 |
+
value: 11.332
|
308 |
+
- type: mrr_at_100
|
309 |
+
value: 11.77
|
310 |
+
- type: mrr_at_1000
|
311 |
+
value: 11.843
|
312 |
+
- type: mrr_at_3
|
313 |
+
value: 10.478
|
314 |
+
- type: mrr_at_5
|
315 |
+
value: 10.959000000000001
|
316 |
+
- type: ndcg_at_1
|
317 |
+
value: 8.599
|
318 |
+
- type: ndcg_at_10
|
319 |
+
value: 10.843
|
320 |
+
- type: ndcg_at_100
|
321 |
+
value: 13.023000000000001
|
322 |
+
- type: ndcg_at_1000
|
323 |
+
value: 15.409
|
324 |
+
- type: ndcg_at_3
|
325 |
+
value: 9.673
|
326 |
+
- type: ndcg_at_5
|
327 |
+
value: 10.188
|
328 |
+
- type: precision_at_1
|
329 |
+
value: 8.599
|
330 |
+
- type: precision_at_10
|
331 |
+
value: 2.038
|
332 |
+
- type: precision_at_100
|
333 |
+
value: 0.383
|
334 |
+
- type: precision_at_1000
|
335 |
+
value: 0.074
|
336 |
+
- type: precision_at_3
|
337 |
+
value: 4.756
|
338 |
+
- type: precision_at_5
|
339 |
+
value: 3.3890000000000002
|
340 |
+
- type: recall_at_1
|
341 |
+
value: 6.632000000000001
|
342 |
+
- type: recall_at_10
|
343 |
+
value: 13.952
|
344 |
+
- type: recall_at_100
|
345 |
+
value: 23.966
|
346 |
+
- type: recall_at_1000
|
347 |
+
value: 41.411
|
348 |
+
- type: recall_at_3
|
349 |
+
value: 10.224
|
350 |
+
- type: recall_at_5
|
351 |
+
value: 11.799
|
352 |
+
- task:
|
353 |
+
type: Retrieval
|
354 |
+
dataset:
|
355 |
+
type: BeIR/cqadupstack
|
356 |
+
name: MTEB CQADupstackGamingRetrieval
|
357 |
+
config: default
|
358 |
+
split: test
|
359 |
+
revision: None
|
360 |
+
metrics:
|
361 |
+
- type: map_at_1
|
362 |
+
value: 11.153
|
363 |
+
- type: map_at_10
|
364 |
+
value: 15.751000000000001
|
365 |
+
- type: map_at_100
|
366 |
+
value: 16.464000000000002
|
367 |
+
- type: map_at_1000
|
368 |
+
value: 16.561
|
369 |
+
- type: map_at_3
|
370 |
+
value: 14.552000000000001
|
371 |
+
- type: map_at_5
|
372 |
+
value: 15.136
|
373 |
+
- type: mrr_at_1
|
374 |
+
value: 13.041
|
375 |
+
- type: mrr_at_10
|
376 |
+
value: 17.777
|
377 |
+
- type: mrr_at_100
|
378 |
+
value: 18.427
|
379 |
+
- type: mrr_at_1000
|
380 |
+
value: 18.504
|
381 |
+
- type: mrr_at_3
|
382 |
+
value: 16.479
|
383 |
+
- type: mrr_at_5
|
384 |
+
value: 17.175
|
385 |
+
- type: ndcg_at_1
|
386 |
+
value: 13.041
|
387 |
+
- type: ndcg_at_10
|
388 |
+
value: 18.581
|
389 |
+
- type: ndcg_at_100
|
390 |
+
value: 22.174
|
391 |
+
- type: ndcg_at_1000
|
392 |
+
value: 24.795
|
393 |
+
- type: ndcg_at_3
|
394 |
+
value: 16.185
|
395 |
+
- type: ndcg_at_5
|
396 |
+
value: 17.183
|
397 |
+
- type: precision_at_1
|
398 |
+
value: 13.041
|
399 |
+
- type: precision_at_10
|
400 |
+
value: 3.2230000000000003
|
401 |
+
- type: precision_at_100
|
402 |
+
value: 0.557
|
403 |
+
- type: precision_at_1000
|
404 |
+
value: 0.086
|
405 |
+
- type: precision_at_3
|
406 |
+
value: 7.544
|
407 |
+
- type: precision_at_5
|
408 |
+
value: 5.279
|
409 |
+
- type: recall_at_1
|
410 |
+
value: 11.153
|
411 |
+
- type: recall_at_10
|
412 |
+
value: 25.052999999999997
|
413 |
+
- type: recall_at_100
|
414 |
+
value: 41.521
|
415 |
+
- type: recall_at_1000
|
416 |
+
value: 61.138000000000005
|
417 |
+
- type: recall_at_3
|
418 |
+
value: 18.673000000000002
|
419 |
+
- type: recall_at_5
|
420 |
+
value: 20.964
|
421 |
+
- task:
|
422 |
+
type: Retrieval
|
423 |
+
dataset:
|
424 |
+
type: BeIR/cqadupstack
|
425 |
+
name: MTEB CQADupstackGisRetrieval
|
426 |
+
config: default
|
427 |
+
split: test
|
428 |
+
revision: None
|
429 |
+
metrics:
|
430 |
+
- type: map_at_1
|
431 |
+
value: 5.303
|
432 |
+
- type: map_at_10
|
433 |
+
value: 7.649
|
434 |
+
- type: map_at_100
|
435 |
+
value: 7.983
|
436 |
+
- type: map_at_1000
|
437 |
+
value: 8.067
|
438 |
+
- type: map_at_3
|
439 |
+
value: 6.938
|
440 |
+
- type: map_at_5
|
441 |
+
value: 7.259
|
442 |
+
- type: mrr_at_1
|
443 |
+
value: 5.763
|
444 |
+
- type: mrr_at_10
|
445 |
+
value: 8.277
|
446 |
+
- type: mrr_at_100
|
447 |
+
value: 8.665000000000001
|
448 |
+
- type: mrr_at_1000
|
449 |
+
value: 8.747
|
450 |
+
- type: mrr_at_3
|
451 |
+
value: 7.457999999999999
|
452 |
+
- type: mrr_at_5
|
453 |
+
value: 7.808
|
454 |
+
- type: ndcg_at_1
|
455 |
+
value: 5.763
|
456 |
+
- type: ndcg_at_10
|
457 |
+
value: 9.1
|
458 |
+
- type: ndcg_at_100
|
459 |
+
value: 11.253
|
460 |
+
- type: ndcg_at_1000
|
461 |
+
value: 13.847999999999999
|
462 |
+
- type: ndcg_at_3
|
463 |
+
value: 7.521999999999999
|
464 |
+
- type: ndcg_at_5
|
465 |
+
value: 8.094
|
466 |
+
- type: precision_at_1
|
467 |
+
value: 5.763
|
468 |
+
- type: precision_at_10
|
469 |
+
value: 1.514
|
470 |
+
- type: precision_at_100
|
471 |
+
value: 0.28700000000000003
|
472 |
+
- type: precision_at_1000
|
473 |
+
value: 0.054
|
474 |
+
- type: precision_at_3
|
475 |
+
value: 3.277
|
476 |
+
- type: precision_at_5
|
477 |
+
value: 2.282
|
478 |
+
- type: recall_at_1
|
479 |
+
value: 5.303
|
480 |
+
- type: recall_at_10
|
481 |
+
value: 13.126
|
482 |
+
- type: recall_at_100
|
483 |
+
value: 23.855
|
484 |
+
- type: recall_at_1000
|
485 |
+
value: 44.417
|
486 |
+
- type: recall_at_3
|
487 |
+
value: 8.556
|
488 |
+
- type: recall_at_5
|
489 |
+
value: 10.006
|
490 |
+
- task:
|
491 |
+
type: Retrieval
|
492 |
+
dataset:
|
493 |
+
type: BeIR/cqadupstack
|
494 |
+
name: MTEB CQADupstackMathematicaRetrieval
|
495 |
+
config: default
|
496 |
+
split: test
|
497 |
+
revision: None
|
498 |
+
metrics:
|
499 |
+
- type: map_at_1
|
500 |
+
value: 2.153
|
501 |
+
- type: map_at_10
|
502 |
+
value: 3.447
|
503 |
+
- type: map_at_100
|
504 |
+
value: 3.73
|
505 |
+
- type: map_at_1000
|
506 |
+
value: 3.8219999999999996
|
507 |
+
- type: map_at_3
|
508 |
+
value: 3.0269999999999997
|
509 |
+
- type: map_at_5
|
510 |
+
value: 3.283
|
511 |
+
- type: mrr_at_1
|
512 |
+
value: 2.612
|
513 |
+
- type: mrr_at_10
|
514 |
+
value: 4.289
|
515 |
+
- type: mrr_at_100
|
516 |
+
value: 4.6080000000000005
|
517 |
+
- type: mrr_at_1000
|
518 |
+
value: 4.713
|
519 |
+
- type: mrr_at_3
|
520 |
+
value: 3.669
|
521 |
+
- type: mrr_at_5
|
522 |
+
value: 4.005
|
523 |
+
- type: ndcg_at_1
|
524 |
+
value: 2.612
|
525 |
+
- type: ndcg_at_10
|
526 |
+
value: 4.422000000000001
|
527 |
+
- type: ndcg_at_100
|
528 |
+
value: 6.15
|
529 |
+
- type: ndcg_at_1000
|
530 |
+
value: 9.25
|
531 |
+
- type: ndcg_at_3
|
532 |
+
value: 3.486
|
533 |
+
- type: ndcg_at_5
|
534 |
+
value: 3.95
|
535 |
+
- type: precision_at_1
|
536 |
+
value: 2.612
|
537 |
+
- type: precision_at_10
|
538 |
+
value: 0.8829999999999999
|
539 |
+
- type: precision_at_100
|
540 |
+
value: 0.211
|
541 |
+
- type: precision_at_1000
|
542 |
+
value: 0.059000000000000004
|
543 |
+
- type: precision_at_3
|
544 |
+
value: 1.6580000000000001
|
545 |
+
- type: precision_at_5
|
546 |
+
value: 1.294
|
547 |
+
- type: recall_at_1
|
548 |
+
value: 2.153
|
549 |
+
- type: recall_at_10
|
550 |
+
value: 6.607
|
551 |
+
- type: recall_at_100
|
552 |
+
value: 14.707
|
553 |
+
- type: recall_at_1000
|
554 |
+
value: 37.99
|
555 |
+
- type: recall_at_3
|
556 |
+
value: 4.122
|
557 |
+
- type: recall_at_5
|
558 |
+
value: 5.241
|
559 |
+
- task:
|
560 |
+
type: Retrieval
|
561 |
+
dataset:
|
562 |
+
type: BeIR/cqadupstack
|
563 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
564 |
+
config: default
|
565 |
+
split: test
|
566 |
+
revision: None
|
567 |
+
metrics:
|
568 |
+
- type: map_at_1
|
569 |
+
value: 7.976999999999999
|
570 |
+
- type: map_at_10
|
571 |
+
value: 11.745
|
572 |
+
- type: map_at_100
|
573 |
+
value: 12.427000000000001
|
574 |
+
- type: map_at_1000
|
575 |
+
value: 12.528
|
576 |
+
- type: map_at_3
|
577 |
+
value: 10.478
|
578 |
+
- type: map_at_5
|
579 |
+
value: 11.224
|
580 |
+
- type: mrr_at_1
|
581 |
+
value: 9.432
|
582 |
+
- type: mrr_at_10
|
583 |
+
value: 14.021
|
584 |
+
- type: mrr_at_100
|
585 |
+
value: 14.734
|
586 |
+
- type: mrr_at_1000
|
587 |
+
value: 14.813
|
588 |
+
- type: mrr_at_3
|
589 |
+
value: 12.576
|
590 |
+
- type: mrr_at_5
|
591 |
+
value: 13.414000000000001
|
592 |
+
- type: ndcg_at_1
|
593 |
+
value: 9.432
|
594 |
+
- type: ndcg_at_10
|
595 |
+
value: 14.341000000000001
|
596 |
+
- type: ndcg_at_100
|
597 |
+
value: 18.168
|
598 |
+
- type: ndcg_at_1000
|
599 |
+
value: 21.129
|
600 |
+
- type: ndcg_at_3
|
601 |
+
value: 11.909
|
602 |
+
- type: ndcg_at_5
|
603 |
+
value: 13.139999999999999
|
604 |
+
- type: precision_at_1
|
605 |
+
value: 9.432
|
606 |
+
- type: precision_at_10
|
607 |
+
value: 2.6759999999999997
|
608 |
+
- type: precision_at_100
|
609 |
+
value: 0.563
|
610 |
+
- type: precision_at_1000
|
611 |
+
value: 0.098
|
612 |
+
- type: precision_at_3
|
613 |
+
value: 5.679
|
614 |
+
- type: precision_at_5
|
615 |
+
value: 4.216
|
616 |
+
- type: recall_at_1
|
617 |
+
value: 7.976999999999999
|
618 |
+
- type: recall_at_10
|
619 |
+
value: 19.983999999999998
|
620 |
+
- type: recall_at_100
|
621 |
+
value: 37.181
|
622 |
+
- type: recall_at_1000
|
623 |
+
value: 58.714999999999996
|
624 |
+
- type: recall_at_3
|
625 |
+
value: 13.375
|
626 |
+
- type: recall_at_5
|
627 |
+
value: 16.54
|
628 |
+
- task:
|
629 |
+
type: Retrieval
|
630 |
+
dataset:
|
631 |
+
type: BeIR/cqadupstack
|
632 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
633 |
+
config: default
|
634 |
+
split: test
|
635 |
+
revision: None
|
636 |
+
metrics:
|
637 |
+
- type: map_at_1
|
638 |
+
value: 5.682
|
639 |
+
- type: map_at_10
|
640 |
+
value: 7.817
|
641 |
+
- type: map_at_100
|
642 |
+
value: 8.3
|
643 |
+
- type: map_at_1000
|
644 |
+
value: 8.378
|
645 |
+
- type: map_at_3
|
646 |
+
value: 7.13
|
647 |
+
- type: map_at_5
|
648 |
+
value: 7.467
|
649 |
+
- type: mrr_at_1
|
650 |
+
value: 6.848999999999999
|
651 |
+
- type: mrr_at_10
|
652 |
+
value: 9.687999999999999
|
653 |
+
- type: mrr_at_100
|
654 |
+
value: 10.208
|
655 |
+
- type: mrr_at_1000
|
656 |
+
value: 10.281
|
657 |
+
- type: mrr_at_3
|
658 |
+
value: 8.770999999999999
|
659 |
+
- type: mrr_at_5
|
660 |
+
value: 9.256
|
661 |
+
- type: ndcg_at_1
|
662 |
+
value: 6.848999999999999
|
663 |
+
- type: ndcg_at_10
|
664 |
+
value: 9.519
|
665 |
+
- type: ndcg_at_100
|
666 |
+
value: 12.303
|
667 |
+
- type: ndcg_at_1000
|
668 |
+
value: 15.004999999999999
|
669 |
+
- type: ndcg_at_3
|
670 |
+
value: 8.077
|
671 |
+
- type: ndcg_at_5
|
672 |
+
value: 8.656
|
673 |
+
- type: precision_at_1
|
674 |
+
value: 6.848999999999999
|
675 |
+
- type: precision_at_10
|
676 |
+
value: 1.735
|
677 |
+
- type: precision_at_100
|
678 |
+
value: 0.363
|
679 |
+
- type: precision_at_1000
|
680 |
+
value: 0.073
|
681 |
+
- type: precision_at_3
|
682 |
+
value: 3.7289999999999996
|
683 |
+
- type: precision_at_5
|
684 |
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value: 2.717
|
685 |
+
- type: recall_at_1
|
686 |
+
value: 5.682
|
687 |
+
- type: recall_at_10
|
688 |
+
value: 13.001
|
689 |
+
- type: recall_at_100
|
690 |
+
value: 25.916
|
691 |
+
- type: recall_at_1000
|
692 |
+
value: 46.303
|
693 |
+
- type: recall_at_3
|
694 |
+
value: 8.949
|
695 |
+
- type: recall_at_5
|
696 |
+
value: 10.413
|
697 |
+
- task:
|
698 |
+
type: Retrieval
|
699 |
+
dataset:
|
700 |
+
type: BeIR/cqadupstack
|
701 |
+
name: MTEB CQADupstackRetrieval
|
702 |
+
config: default
|
703 |
+
split: test
|
704 |
+
revision: None
|
705 |
+
metrics:
|
706 |
+
- type: map_at_1
|
707 |
+
value: 5.441
|
708 |
+
- type: map_at_10
|
709 |
+
value: 7.997500000000002
|
710 |
+
- type: map_at_100
|
711 |
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value: 8.47225
|
712 |
+
- type: map_at_1000
|
713 |
+
value: 8.557083333333333
|
714 |
+
- type: map_at_3
|
715 |
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value: 7.17025
|
716 |
+
- type: map_at_5
|
717 |
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value: 7.597833333333333
|
718 |
+
- type: mrr_at_1
|
719 |
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value: 6.6329166666666675
|
720 |
+
- type: mrr_at_10
|
721 |
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value: 9.596583333333333
|
722 |
+
- type: mrr_at_100
|
723 |
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value: 10.094416666666667
|
724 |
+
- type: mrr_at_1000
|
725 |
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value: 10.171583333333334
|
726 |
+
- type: mrr_at_3
|
727 |
+
value: 8.628416666666666
|
728 |
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- type: mrr_at_5
|
729 |
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value: 9.143416666666667
|
730 |
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- type: ndcg_at_1
|
731 |
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value: 6.6329166666666675
|
732 |
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- type: ndcg_at_10
|
733 |
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value: 9.81258333333333
|
734 |
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- type: ndcg_at_100
|
735 |
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value: 12.459416666666666
|
736 |
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- type: ndcg_at_1000
|
737 |
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value: 15.099416666666668
|
738 |
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- type: ndcg_at_3
|
739 |
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value: 8.177499999999998
|
740 |
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- type: ndcg_at_5
|
741 |
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value: 8.8765
|
742 |
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- type: precision_at_1
|
743 |
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value: 6.6329166666666675
|
744 |
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- type: precision_at_10
|
745 |
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value: 1.8355833333333336
|
746 |
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- type: precision_at_100
|
747 |
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value: 0.38033333333333336
|
748 |
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- type: precision_at_1000
|
749 |
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value: 0.07358333333333333
|
750 |
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- type: precision_at_3
|
751 |
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value: 3.912583333333333
|
752 |
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- type: precision_at_5
|
753 |
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value: 2.8570833333333336
|
754 |
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- type: recall_at_1
|
755 |
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value: 5.441
|
756 |
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- type: recall_at_10
|
757 |
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value: 13.79075
|
758 |
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- type: recall_at_100
|
759 |
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value: 26.12841666666667
|
760 |
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- type: recall_at_1000
|
761 |
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value: 46.1115
|
762 |
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- type: recall_at_3
|
763 |
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value: 9.212416666666666
|
764 |
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- type: recall_at_5
|
765 |
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value: 11.006499999999999
|
766 |
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- task:
|
767 |
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type: Retrieval
|
768 |
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dataset:
|
769 |
+
type: BeIR/cqadupstack
|
770 |
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name: MTEB CQADupstackStatsRetrieval
|
771 |
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config: default
|
772 |
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split: test
|
773 |
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revision: None
|
774 |
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metrics:
|
775 |
+
- type: map_at_1
|
776 |
+
value: 4.973000000000001
|
777 |
+
- type: map_at_10
|
778 |
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value: 6.583
|
779 |
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- type: map_at_100
|
780 |
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value: 7.013999999999999
|
781 |
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- type: map_at_1000
|
782 |
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value: 7.084
|
783 |
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- type: map_at_3
|
784 |
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value: 5.987
|
785 |
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- type: map_at_5
|
786 |
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value: 6.283999999999999
|
787 |
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- type: mrr_at_1
|
788 |
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value: 6.135
|
789 |
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- type: mrr_at_10
|
790 |
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value: 7.911
|
791 |
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- type: mrr_at_100
|
792 |
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value: 8.381
|
793 |
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- type: mrr_at_1000
|
794 |
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value: 8.451
|
795 |
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- type: mrr_at_3
|
796 |
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value: 7.234
|
797 |
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- type: mrr_at_5
|
798 |
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value: 7.595000000000001
|
799 |
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- type: ndcg_at_1
|
800 |
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value: 6.135
|
801 |
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- type: ndcg_at_10
|
802 |
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value: 7.8420000000000005
|
803 |
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- type: ndcg_at_100
|
804 |
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value: 10.335999999999999
|
805 |
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- type: ndcg_at_1000
|
806 |
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value: 12.742999999999999
|
807 |
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- type: ndcg_at_3
|
808 |
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value: 6.622
|
809 |
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- type: ndcg_at_5
|
810 |
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value: 7.156
|
811 |
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- type: precision_at_1
|
812 |
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value: 6.135
|
813 |
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- type: precision_at_10
|
814 |
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value: 1.3339999999999999
|
815 |
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- type: precision_at_100
|
816 |
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value: 0.293
|
817 |
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- type: precision_at_1000
|
818 |
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value: 0.053
|
819 |
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- type: precision_at_3
|
820 |
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value: 2.965
|
821 |
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- type: precision_at_5
|
822 |
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value: 2.086
|
823 |
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- type: recall_at_1
|
824 |
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value: 4.973000000000001
|
825 |
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- type: recall_at_10
|
826 |
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value: 10.497
|
827 |
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- type: recall_at_100
|
828 |
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value: 22.389
|
829 |
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- type: recall_at_1000
|
830 |
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value: 41.751
|
831 |
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- type: recall_at_3
|
832 |
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value: 7.248
|
833 |
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- type: recall_at_5
|
834 |
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value: 8.526
|
835 |
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- task:
|
836 |
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type: Retrieval
|
837 |
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dataset:
|
838 |
+
type: BeIR/cqadupstack
|
839 |
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name: MTEB CQADupstackTexRetrieval
|
840 |
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config: default
|
841 |
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split: test
|
842 |
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revision: None
|
843 |
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metrics:
|
844 |
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- type: map_at_1
|
845 |
+
value: 2.541
|
846 |
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- type: map_at_10
|
847 |
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value: 4.168
|
848 |
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- type: map_at_100
|
849 |
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value: 4.492
|
850 |
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- type: map_at_1000
|
851 |
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value: 4.553
|
852 |
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- type: map_at_3
|
853 |
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value: 3.62
|
854 |
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- type: map_at_5
|
855 |
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value: 3.927
|
856 |
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- type: mrr_at_1
|
857 |
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value: 3.131
|
858 |
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- type: mrr_at_10
|
859 |
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value: 5.037
|
860 |
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- type: mrr_at_100
|
861 |
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value: 5.428
|
862 |
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- type: mrr_at_1000
|
863 |
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value: 5.487
|
864 |
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- type: mrr_at_3
|
865 |
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value: 4.422000000000001
|
866 |
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- type: mrr_at_5
|
867 |
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value: 4.752
|
868 |
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- type: ndcg_at_1
|
869 |
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value: 3.131
|
870 |
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- type: ndcg_at_10
|
871 |
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value: 5.315
|
872 |
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- type: ndcg_at_100
|
873 |
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value: 7.207
|
874 |
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- type: ndcg_at_1000
|
875 |
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value: 9.271
|
876 |
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- type: ndcg_at_3
|
877 |
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value: 4.244
|
878 |
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- type: ndcg_at_5
|
879 |
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value: 4.742
|
880 |
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- type: precision_at_1
|
881 |
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value: 3.131
|
882 |
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- type: precision_at_10
|
883 |
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value: 1.0699999999999998
|
884 |
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- type: precision_at_100
|
885 |
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value: 0.247
|
886 |
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- type: precision_at_1000
|
887 |
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value: 0.053
|
888 |
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- type: precision_at_3
|
889 |
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value: 2.1340000000000003
|
890 |
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- type: precision_at_5
|
891 |
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value: 1.624
|
892 |
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- type: recall_at_1
|
893 |
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value: 2.541
|
894 |
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- type: recall_at_10
|
895 |
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value: 7.8740000000000006
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896 |
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- type: recall_at_100
|
897 |
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value: 16.896
|
898 |
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- type: recall_at_1000
|
899 |
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value: 32.423
|
900 |
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- type: recall_at_3
|
901 |
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value: 4.925
|
902 |
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- type: recall_at_5
|
903 |
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value: 6.181
|
904 |
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- task:
|
905 |
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type: Retrieval
|
906 |
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dataset:
|
907 |
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type: BeIR/cqadupstack
|
908 |
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name: MTEB CQADupstackUnixRetrieval
|
909 |
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config: default
|
910 |
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split: test
|
911 |
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revision: None
|
912 |
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metrics:
|
913 |
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- type: map_at_1
|
914 |
+
value: 5.58
|
915 |
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- type: map_at_10
|
916 |
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value: 7.758
|
917 |
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- type: map_at_100
|
918 |
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value: 8.168000000000001
|
919 |
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- type: map_at_1000
|
920 |
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value: 8.239
|
921 |
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- type: map_at_3
|
922 |
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value: 6.895999999999999
|
923 |
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|
924 |
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value: 7.412000000000001
|
925 |
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- type: mrr_at_1
|
926 |
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value: 6.81
|
927 |
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|
928 |
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value: 9.295
|
929 |
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- type: mrr_at_100
|
930 |
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value: 9.763
|
931 |
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- type: mrr_at_1000
|
932 |
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value: 9.835
|
933 |
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- type: mrr_at_3
|
934 |
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value: 8.427
|
935 |
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- type: mrr_at_5
|
936 |
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value: 8.958
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937 |
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- type: ndcg_at_1
|
938 |
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value: 6.81
|
939 |
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- type: ndcg_at_10
|
940 |
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value: 9.436
|
941 |
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- type: ndcg_at_100
|
942 |
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value: 11.955
|
943 |
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- type: ndcg_at_1000
|
944 |
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value: 14.387
|
945 |
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- type: ndcg_at_3
|
946 |
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value: 7.7410000000000005
|
947 |
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- type: ndcg_at_5
|
948 |
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value: 8.622
|
949 |
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- type: precision_at_1
|
950 |
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value: 6.81
|
951 |
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- type: precision_at_10
|
952 |
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value: 1.6230000000000002
|
953 |
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- type: precision_at_100
|
954 |
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value: 0.335
|
955 |
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- type: precision_at_1000
|
956 |
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value: 0.062
|
957 |
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- type: precision_at_3
|
958 |
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value: 3.576
|
959 |
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- type: precision_at_5
|
960 |
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value: 2.6870000000000003
|
961 |
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- type: recall_at_1
|
962 |
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value: 5.58
|
963 |
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- type: recall_at_10
|
964 |
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value: 13.232
|
965 |
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- type: recall_at_100
|
966 |
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value: 25.233
|
967 |
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- type: recall_at_1000
|
968 |
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value: 43.864999999999995
|
969 |
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- type: recall_at_3
|
970 |
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value: 8.549
|
971 |
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- type: recall_at_5
|
972 |
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value: 10.799
|
973 |
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- task:
|
974 |
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type: Retrieval
|
975 |
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dataset:
|
976 |
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type: BeIR/cqadupstack
|
977 |
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name: MTEB CQADupstackWebmastersRetrieval
|
978 |
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config: default
|
979 |
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split: test
|
980 |
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revision: None
|
981 |
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metrics:
|
982 |
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- type: map_at_1
|
983 |
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value: 3.8739999999999997
|
984 |
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- type: map_at_10
|
985 |
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value: 6.491
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986 |
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|
987 |
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value: 7.065
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988 |
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- type: map_at_1000
|
989 |
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value: 7.185
|
990 |
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|
991 |
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value: 5.568
|
992 |
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|
993 |
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value: 6.1080000000000005
|
994 |
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|
995 |
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value: 5.335999999999999
|
996 |
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|
997 |
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value: 8.288
|
998 |
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- type: mrr_at_100
|
999 |
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value: 8.886
|
1000 |
+
- type: mrr_at_1000
|
1001 |
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value: 8.976
|
1002 |
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- type: mrr_at_3
|
1003 |
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value: 7.115
|
1004 |
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- type: mrr_at_5
|
1005 |
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value: 7.846
|
1006 |
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- type: ndcg_at_1
|
1007 |
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value: 5.335999999999999
|
1008 |
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- type: ndcg_at_10
|
1009 |
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value: 8.463
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1010 |
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- type: ndcg_at_100
|
1011 |
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value: 11.456
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1012 |
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- type: ndcg_at_1000
|
1013 |
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value: 14.662
|
1014 |
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- type: ndcg_at_3
|
1015 |
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value: 6.7589999999999995
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1016 |
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|
1017 |
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value: 7.5969999999999995
|
1018 |
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- type: precision_at_1
|
1019 |
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value: 5.335999999999999
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1020 |
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|
1021 |
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value: 1.9369999999999998
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1022 |
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|
1023 |
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value: 0.498
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1024 |
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- type: precision_at_1000
|
1025 |
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value: 0.116
|
1026 |
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- type: precision_at_3
|
1027 |
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value: 3.689
|
1028 |
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- type: precision_at_5
|
1029 |
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value: 2.9250000000000003
|
1030 |
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- type: recall_at_1
|
1031 |
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value: 3.8739999999999997
|
1032 |
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- type: recall_at_10
|
1033 |
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value: 12.281
|
1034 |
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- type: recall_at_100
|
1035 |
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value: 26.368000000000002
|
1036 |
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- type: recall_at_1000
|
1037 |
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value: 50.422
|
1038 |
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- type: recall_at_3
|
1039 |
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value: 7.353
|
1040 |
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- type: recall_at_5
|
1041 |
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value: 9.66
|
1042 |
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- task:
|
1043 |
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type: Retrieval
|
1044 |
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dataset:
|
1045 |
+
type: BeIR/cqadupstack
|
1046 |
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name: MTEB CQADupstackWordpressRetrieval
|
1047 |
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config: default
|
1048 |
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split: test
|
1049 |
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revision: None
|
1050 |
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metrics:
|
1051 |
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- type: map_at_1
|
1052 |
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value: 2.317
|
1053 |
+
- type: map_at_10
|
1054 |
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value: 3.697
|
1055 |
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- type: map_at_100
|
1056 |
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value: 3.9370000000000003
|
1057 |
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- type: map_at_1000
|
1058 |
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value: 3.994
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1059 |
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- type: map_at_3
|
1060 |
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value: 3.1329999999999996
|
1061 |
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- type: map_at_5
|
1062 |
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value: 3.45
|
1063 |
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- type: mrr_at_1
|
1064 |
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value: 2.588
|
1065 |
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- type: mrr_at_10
|
1066 |
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value: 4.168
|
1067 |
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- type: mrr_at_100
|
1068 |
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value: 4.421
|
1069 |
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- type: mrr_at_1000
|
1070 |
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value: 4.481
|
1071 |
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- type: mrr_at_3
|
1072 |
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value: 3.512
|
1073 |
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|
1074 |
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value: 3.909
|
1075 |
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- type: ndcg_at_1
|
1076 |
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value: 2.588
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1077 |
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|
1078 |
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value: 4.679
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1079 |
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|
1080 |
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value: 6.114
|
1081 |
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- type: ndcg_at_1000
|
1082 |
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value: 8.167
|
1083 |
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|
1084 |
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value: 3.5290000000000004
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1085 |
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|
1086 |
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value: 4.093999999999999
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1087 |
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|
1088 |
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value: 2.588
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1089 |
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- type: precision_at_10
|
1090 |
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value: 0.832
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1091 |
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- type: precision_at_100
|
1092 |
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value: 0.165
|
1093 |
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- type: precision_at_1000
|
1094 |
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value: 0.037
|
1095 |
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- type: precision_at_3
|
1096 |
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value: 1.6019999999999999
|
1097 |
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- type: precision_at_5
|
1098 |
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value: 1.294
|
1099 |
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- type: recall_at_1
|
1100 |
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value: 2.317
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1101 |
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- type: recall_at_10
|
1102 |
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value: 7.338
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1103 |
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- type: recall_at_100
|
1104 |
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value: 14.507
|
1105 |
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- type: recall_at_1000
|
1106 |
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value: 31.226
|
1107 |
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- type: recall_at_3
|
1108 |
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value: 4.258
|
1109 |
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- type: recall_at_5
|
1110 |
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value: 5.582
|
1111 |
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- task:
|
1112 |
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type: Classification
|
1113 |
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dataset:
|
1114 |
+
type: mteb/emotion
|
1115 |
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name: MTEB EmotionClassification
|
1116 |
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config: default
|
1117 |
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split: test
|
1118 |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1119 |
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metrics:
|
1120 |
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- type: accuracy
|
1121 |
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value: 33.535
|
1122 |
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- type: f1
|
1123 |
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value: 29.64261331714107
|
1124 |
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- task:
|
1125 |
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type: Classification
|
1126 |
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dataset:
|
1127 |
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type: mteb/imdb
|
1128 |
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name: MTEB ImdbClassification
|
1129 |
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|
1130 |
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1131 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1132 |
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metrics:
|
1133 |
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- type: accuracy
|
1134 |
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value: 57.03359999999999
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1135 |
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- type: ap
|
1136 |
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value: 54.289515246345985
|
1137 |
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- type: f1
|
1138 |
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value: 56.404319444675686
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1139 |
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- task:
|
1140 |
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type: Classification
|
1141 |
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dataset:
|
1142 |
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type: mteb/mtop_domain
|
1143 |
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name: MTEB MTOPDomainClassification (en)
|
1144 |
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config: en
|
1145 |
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split: test
|
1146 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
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1147 |
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metrics:
|
1148 |
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- type: accuracy
|
1149 |
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value: 86.70770633834928
|
1150 |
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- type: f1
|
1151 |
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value: 86.3521440956975
|
1152 |
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- task:
|
1153 |
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type: Classification
|
1154 |
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dataset:
|
1155 |
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type: mteb/mtop_intent
|
1156 |
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name: MTEB MTOPIntentClassification (en)
|
1157 |
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config: en
|
1158 |
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split: test
|
1159 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
1160 |
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metrics:
|
1161 |
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- type: accuracy
|
1162 |
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value: 62.35750113999089
|
1163 |
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- type: f1
|
1164 |
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value: 41.01929492285308
|
1165 |
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- task:
|
1166 |
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type: Classification
|
1167 |
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|
1168 |
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|
1181 |
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1203 |
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|
1205 |
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1214 |
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|
1216 |
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1240 |
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1438 |
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dataset:
|
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1451 |
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dataset:
|
1453 |
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1454 |
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name: MTEB SprintDuplicateQuestions
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1455 |
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1459 |
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|
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1516 |
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|
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|
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|
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1556 |
+
value: 19.17304603866006
|
1557 |
+
- task:
|
1558 |
+
type: Classification
|
1559 |
+
dataset:
|
1560 |
+
type: mteb/toxic_conversations_50k
|
1561 |
+
name: MTEB ToxicConversationsClassification
|
1562 |
+
config: default
|
1563 |
+
split: test
|
1564 |
+
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
1565 |
+
metrics:
|
1566 |
+
- type: accuracy
|
1567 |
+
value: 63.2888
|
1568 |
+
- type: ap
|
1569 |
+
value: 11.062527367094436
|
1570 |
+
- type: f1
|
1571 |
+
value: 48.6893658037416
|
1572 |
+
- task:
|
1573 |
+
type: Classification
|
1574 |
+
dataset:
|
1575 |
+
type: mteb/tweet_sentiment_extraction
|
1576 |
+
name: MTEB TweetSentimentExtractionClassification
|
1577 |
+
config: default
|
1578 |
+
split: test
|
1579 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
1580 |
+
metrics:
|
1581 |
+
- type: accuracy
|
1582 |
+
value: 49.275608375778155
|
1583 |
+
- type: f1
|
1584 |
+
value: 49.487704374827324
|
1585 |
+
- task:
|
1586 |
+
type: Clustering
|
1587 |
+
dataset:
|
1588 |
+
type: mteb/twentynewsgroups-clustering
|
1589 |
+
name: MTEB TwentyNewsgroupsClustering
|
1590 |
+
config: default
|
1591 |
+
split: test
|
1592 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
1593 |
+
metrics:
|
1594 |
+
- type: v_measure
|
1595 |
+
value: 37.31132794113957
|
1596 |
+
- task:
|
1597 |
+
type: PairClassification
|
1598 |
+
dataset:
|
1599 |
+
type: mteb/twittersemeval2015-pairclassification
|
1600 |
+
name: MTEB TwitterSemEval2015
|
1601 |
+
config: default
|
1602 |
+
split: test
|
1603 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
1604 |
+
metrics:
|
1605 |
+
- type: cos_sim_accuracy
|
1606 |
+
value: 80.008344757704
|
1607 |
+
- type: cos_sim_ap
|
1608 |
+
value: 50.955726976655036
|
1609 |
+
- type: cos_sim_f1
|
1610 |
+
value: 49.800796812749006
|
1611 |
+
- type: cos_sim_precision
|
1612 |
+
value: 42.8898208158597
|
1613 |
+
- type: cos_sim_recall
|
1614 |
+
value: 59.36675461741425
|
1615 |
+
- type: dot_accuracy
|
1616 |
+
value: 77.42743041068128
|
1617 |
+
- type: dot_ap
|
1618 |
+
value: 19.216239898966027
|
1619 |
+
- type: dot_f1
|
1620 |
+
value: 36.95323548056761
|
1621 |
+
- type: dot_precision
|
1622 |
+
value: 22.665550038882575
|
1623 |
+
- type: dot_recall
|
1624 |
+
value: 99.9736147757256
|
1625 |
+
- type: euclidean_accuracy
|
1626 |
+
value: 81.12296596530965
|
1627 |
+
- type: euclidean_ap
|
1628 |
+
value: 55.99371814327642
|
1629 |
+
- type: euclidean_f1
|
1630 |
+
value: 54.55376528396755
|
1631 |
+
- type: euclidean_precision
|
1632 |
+
value: 48.11529933481153
|
1633 |
+
- type: euclidean_recall
|
1634 |
+
value: 62.98153034300792
|
1635 |
+
- type: manhattan_accuracy
|
1636 |
+
value: 81.3673481552125
|
1637 |
+
- type: manhattan_ap
|
1638 |
+
value: 57.126538198748456
|
1639 |
+
- type: manhattan_f1
|
1640 |
+
value: 55.38567651454189
|
1641 |
+
- type: manhattan_precision
|
1642 |
+
value: 49.073130983907106
|
1643 |
+
- type: manhattan_recall
|
1644 |
+
value: 63.562005277044854
|
1645 |
+
- type: max_accuracy
|
1646 |
+
value: 81.3673481552125
|
1647 |
+
- type: max_ap
|
1648 |
+
value: 57.126538198748456
|
1649 |
+
- type: max_f1
|
1650 |
+
value: 55.38567651454189
|
1651 |
+
- task:
|
1652 |
+
type: PairClassification
|
1653 |
+
dataset:
|
1654 |
+
type: mteb/twitterurlcorpus-pairclassification
|
1655 |
+
name: MTEB TwitterURLCorpus
|
1656 |
+
config: default
|
1657 |
+
split: test
|
1658 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
1659 |
+
metrics:
|
1660 |
+
- type: cos_sim_accuracy
|
1661 |
+
value: 84.02607986960065
|
1662 |
+
- type: cos_sim_ap
|
1663 |
+
value: 74.07757228336027
|
1664 |
+
- type: cos_sim_f1
|
1665 |
+
value: 66.0694778239021
|
1666 |
+
- type: cos_sim_precision
|
1667 |
+
value: 62.67790520934089
|
1668 |
+
- type: cos_sim_recall
|
1669 |
+
value: 69.84909146904835
|
1670 |
+
- type: dot_accuracy
|
1671 |
+
value: 74.79722125198897
|
1672 |
+
- type: dot_ap
|
1673 |
+
value: 25.478024888904727
|
1674 |
+
- type: dot_f1
|
1675 |
+
value: 40.76642277589147
|
1676 |
+
- type: dot_precision
|
1677 |
+
value: 25.705095989546688
|
1678 |
+
- type: dot_recall
|
1679 |
+
value: 98.45241761626117
|
1680 |
+
- type: euclidean_accuracy
|
1681 |
+
value: 85.51053673303062
|
1682 |
+
- type: euclidean_ap
|
1683 |
+
value: 78.24178926488659
|
1684 |
+
- type: euclidean_f1
|
1685 |
+
value: 70.50944224857267
|
1686 |
+
- type: euclidean_precision
|
1687 |
+
value: 67.19447544642857
|
1688 |
+
- type: euclidean_recall
|
1689 |
+
value: 74.16846319679703
|
1690 |
+
- type: manhattan_accuracy
|
1691 |
+
value: 85.72398804672643
|
1692 |
+
- type: manhattan_ap
|
1693 |
+
value: 78.90411073933831
|
1694 |
+
- type: manhattan_f1
|
1695 |
+
value: 70.90586145648314
|
1696 |
+
- type: manhattan_precision
|
1697 |
+
value: 65.8224508640021
|
1698 |
+
- type: manhattan_recall
|
1699 |
+
value: 76.84016014782877
|
1700 |
+
- type: max_accuracy
|
1701 |
+
value: 85.72398804672643
|
1702 |
+
- type: max_ap
|
1703 |
+
value: 78.90411073933831
|
1704 |
+
- type: max_f1
|
1705 |
+
value: 70.90586145648314
|
1706 |
---
|
1707 |
|
1708 |
# clip-ViT-B-32
|