Mteb benchmark
Browse files
README.md
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1 |
+
---
|
2 |
+
tags:
|
3 |
+
- mteb
|
4 |
+
model-index:
|
5 |
+
- name: bge-m3
|
6 |
+
results:
|
7 |
+
- task:
|
8 |
+
type: Classification
|
9 |
+
dataset:
|
10 |
+
type: mteb/amazon_counterfactual
|
11 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
12 |
+
config: en
|
13 |
+
split: test
|
14 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
15 |
+
metrics:
|
16 |
+
- type: accuracy
|
17 |
+
value: 75.6268656716418
|
18 |
+
- type: ap
|
19 |
+
value: 39.50276109614102
|
20 |
+
- type: f1
|
21 |
+
value: 70.00224623431103
|
22 |
+
- task:
|
23 |
+
type: Clustering
|
24 |
+
dataset:
|
25 |
+
type: mteb/arxiv-clustering-p2p
|
26 |
+
name: MTEB ArxivClusteringP2P
|
27 |
+
config: default
|
28 |
+
split: test
|
29 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
30 |
+
metrics:
|
31 |
+
- type: v_measure
|
32 |
+
value: 39.409674498704625
|
33 |
+
- task:
|
34 |
+
type: Reranking
|
35 |
+
dataset:
|
36 |
+
type: mteb/askubuntudupquestions-reranking
|
37 |
+
name: MTEB AskUbuntuDupQuestions
|
38 |
+
config: default
|
39 |
+
split: test
|
40 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
41 |
+
metrics:
|
42 |
+
- type: map
|
43 |
+
value: 61.52757354203137
|
44 |
+
- type: mrr
|
45 |
+
value: 74.28241656773513
|
46 |
+
- task:
|
47 |
+
type: STS
|
48 |
+
dataset:
|
49 |
+
type: mteb/biosses-sts
|
50 |
+
name: MTEB BIOSSES
|
51 |
+
config: default
|
52 |
+
split: test
|
53 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
54 |
+
metrics:
|
55 |
+
- type: cos_sim_pearson
|
56 |
+
value: 84.39442490594014
|
57 |
+
- type: cos_sim_spearman
|
58 |
+
value: 83.37599616417513
|
59 |
+
- type: euclidean_pearson
|
60 |
+
value: 83.23317790460271
|
61 |
+
- type: euclidean_spearman
|
62 |
+
value: 83.37599616417513
|
63 |
+
- type: manhattan_pearson
|
64 |
+
value: 83.23182214744224
|
65 |
+
- type: manhattan_spearman
|
66 |
+
value: 83.5428674363298
|
67 |
+
- task:
|
68 |
+
type: Classification
|
69 |
+
dataset:
|
70 |
+
type: mteb/banking77
|
71 |
+
name: MTEB Banking77Classification
|
72 |
+
config: default
|
73 |
+
split: test
|
74 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
75 |
+
metrics:
|
76 |
+
- type: accuracy
|
77 |
+
value: 81.93181818181819
|
78 |
+
- type: f1
|
79 |
+
value: 81.0852312152688
|
80 |
+
- task:
|
81 |
+
type: Classification
|
82 |
+
dataset:
|
83 |
+
type: mteb/emotion
|
84 |
+
name: MTEB EmotionClassification
|
85 |
+
config: default
|
86 |
+
split: test
|
87 |
+
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
88 |
+
metrics:
|
89 |
+
- type: accuracy
|
90 |
+
value: 50.16499999999999
|
91 |
+
- type: f1
|
92 |
+
value: 43.57906972116264
|
93 |
+
- task:
|
94 |
+
type: Classification
|
95 |
+
dataset:
|
96 |
+
type: mteb/mtop_domain
|
97 |
+
name: MTEB MTOPDomainClassification (en)
|
98 |
+
config: en
|
99 |
+
split: test
|
100 |
+
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
101 |
+
metrics:
|
102 |
+
- type: accuracy
|
103 |
+
value: 93.35841313269493
|
104 |
+
- type: f1
|
105 |
+
value: 93.060022693275
|
106 |
+
- task:
|
107 |
+
type: Classification
|
108 |
+
dataset:
|
109 |
+
type: mteb/mtop_intent
|
110 |
+
name: MTEB MTOPIntentClassification (en)
|
111 |
+
config: en
|
112 |
+
split: test
|
113 |
+
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
114 |
+
metrics:
|
115 |
+
- type: accuracy
|
116 |
+
value: 66.58002735978113
|
117 |
+
- type: f1
|
118 |
+
value: 46.995919480823055
|
119 |
+
- task:
|
120 |
+
type: Classification
|
121 |
+
dataset:
|
122 |
+
type: mteb/amazon_massive_intent
|
123 |
+
name: MTEB MassiveIntentClassification (en)
|
124 |
+
config: en
|
125 |
+
split: test
|
126 |
+
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
127 |
+
metrics:
|
128 |
+
- type: accuracy
|
129 |
+
value: 71.07935440484196
|
130 |
+
- type: f1
|
131 |
+
value: 69.13197875645403
|
132 |
+
- task:
|
133 |
+
type: Classification
|
134 |
+
dataset:
|
135 |
+
type: mteb/amazon_massive_scenario
|
136 |
+
name: MTEB MassiveScenarioClassification (en)
|
137 |
+
config: en
|
138 |
+
split: test
|
139 |
+
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
140 |
+
metrics:
|
141 |
+
- type: accuracy
|
142 |
+
value: 76.63752521856087
|
143 |
+
- type: f1
|
144 |
+
value: 75.61348469613843
|
145 |
+
- task:
|
146 |
+
type: STS
|
147 |
+
dataset:
|
148 |
+
type: mteb/sickr-sts
|
149 |
+
name: MTEB SICK-R
|
150 |
+
config: default
|
151 |
+
split: test
|
152 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
153 |
+
metrics:
|
154 |
+
- type: cos_sim_pearson
|
155 |
+
value: 83.33269306539026
|
156 |
+
- type: cos_sim_spearman
|
157 |
+
value: 79.71441518631086
|
158 |
+
- type: euclidean_pearson
|
159 |
+
value: 80.98109404189279
|
160 |
+
- type: euclidean_spearman
|
161 |
+
value: 79.71444969096095
|
162 |
+
- type: manhattan_pearson
|
163 |
+
value: 80.97223989357175
|
164 |
+
- type: manhattan_spearman
|
165 |
+
value: 79.64929261210406
|
166 |
+
- task:
|
167 |
+
type: STS
|
168 |
+
dataset:
|
169 |
+
type: mteb/sts12-sts
|
170 |
+
name: MTEB STS12
|
171 |
+
config: default
|
172 |
+
split: test
|
173 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
174 |
+
metrics:
|
175 |
+
- type: cos_sim_pearson
|
176 |
+
value: 83.7127498314437
|
177 |
+
- type: cos_sim_spearman
|
178 |
+
value: 78.73426610516154
|
179 |
+
- type: euclidean_pearson
|
180 |
+
value: 79.72827173736742
|
181 |
+
- type: euclidean_spearman
|
182 |
+
value: 78.731973450314
|
183 |
+
- type: manhattan_pearson
|
184 |
+
value: 79.71391822179304
|
185 |
+
- type: manhattan_spearman
|
186 |
+
value: 78.69626503719782
|
187 |
+
- task:
|
188 |
+
type: STS
|
189 |
+
dataset:
|
190 |
+
type: mteb/sts13-sts
|
191 |
+
name: MTEB STS13
|
192 |
+
config: default
|
193 |
+
split: test
|
194 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
195 |
+
metrics:
|
196 |
+
- type: cos_sim_pearson
|
197 |
+
value: 78.33449726355023
|
198 |
+
- type: cos_sim_spearman
|
199 |
+
value: 79.59703323420547
|
200 |
+
- type: euclidean_pearson
|
201 |
+
value: 79.87238808505464
|
202 |
+
- type: euclidean_spearman
|
203 |
+
value: 79.59703323420547
|
204 |
+
- type: manhattan_pearson
|
205 |
+
value: 79.5006260085966
|
206 |
+
- type: manhattan_spearman
|
207 |
+
value: 79.21864659717262
|
208 |
+
- task:
|
209 |
+
type: STS
|
210 |
+
dataset:
|
211 |
+
type: mteb/sts14-sts
|
212 |
+
name: MTEB STS14
|
213 |
+
config: default
|
214 |
+
split: test
|
215 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
216 |
+
metrics:
|
217 |
+
- type: cos_sim_pearson
|
218 |
+
value: 79.00088445445654
|
219 |
+
- type: cos_sim_spearman
|
220 |
+
value: 78.99977508575147
|
221 |
+
- type: euclidean_pearson
|
222 |
+
value: 78.63222924140206
|
223 |
+
- type: euclidean_spearman
|
224 |
+
value: 78.99976994069327
|
225 |
+
- type: manhattan_pearson
|
226 |
+
value: 78.35504771673297
|
227 |
+
- type: manhattan_spearman
|
228 |
+
value: 78.76306077740067
|
229 |
+
- task:
|
230 |
+
type: STS
|
231 |
+
dataset:
|
232 |
+
type: mteb/sts15-sts
|
233 |
+
name: MTEB STS15
|
234 |
+
config: default
|
235 |
+
split: test
|
236 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
237 |
+
metrics:
|
238 |
+
- type: cos_sim_pearson
|
239 |
+
value: 87.13160613452308
|
240 |
+
- type: cos_sim_spearman
|
241 |
+
value: 87.81435104273643
|
242 |
+
- type: euclidean_pearson
|
243 |
+
value: 87.22395745487297
|
244 |
+
- type: euclidean_spearman
|
245 |
+
value: 87.81435041827874
|
246 |
+
- type: manhattan_pearson
|
247 |
+
value: 87.17630476262896
|
248 |
+
- type: manhattan_spearman
|
249 |
+
value: 87.76535338976686
|
250 |
+
- task:
|
251 |
+
type: STS
|
252 |
+
dataset:
|
253 |
+
type: mteb/sts16-sts
|
254 |
+
name: MTEB STS16
|
255 |
+
config: default
|
256 |
+
split: test
|
257 |
+
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
258 |
+
metrics:
|
259 |
+
- type: cos_sim_pearson
|
260 |
+
value: 83.76424652225954
|
261 |
+
- type: cos_sim_spearman
|
262 |
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value: 85.39745570134193
|
263 |
+
- type: euclidean_pearson
|
264 |
+
value: 84.6971466556576
|
265 |
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- type: euclidean_spearman
|
266 |
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value: 85.39745570134193
|
267 |
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- type: manhattan_pearson
|
268 |
+
value: 84.61210275324463
|
269 |
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- type: manhattan_spearman
|
270 |
+
value: 85.30727114432379
|
271 |
+
- task:
|
272 |
+
type: STS
|
273 |
+
dataset:
|
274 |
+
type: mteb/sts17-crosslingual-sts
|
275 |
+
name: MTEB STS17 (en-en)
|
276 |
+
config: en-en
|
277 |
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split: test
|
278 |
+
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
279 |
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metrics:
|
280 |
+
- type: cos_sim_pearson
|
281 |
+
value: 86.87956530541486
|
282 |
+
- type: cos_sim_spearman
|
283 |
+
value: 87.13412608536781
|
284 |
+
- type: euclidean_pearson
|
285 |
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value: 87.80084186244981
|
286 |
+
- type: euclidean_spearman
|
287 |
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value: 87.13412608536781
|
288 |
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- type: manhattan_pearson
|
289 |
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value: 87.73101535306475
|
290 |
+
- type: manhattan_spearman
|
291 |
+
value: 87.05897655963285
|
292 |
+
- task:
|
293 |
+
type: STS
|
294 |
+
dataset:
|
295 |
+
type: mteb/stsbenchmark-sts
|
296 |
+
name: MTEB STSBenchmark
|
297 |
+
config: default
|
298 |
+
split: test
|
299 |
+
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
300 |
+
metrics:
|
301 |
+
- type: cos_sim_pearson
|
302 |
+
value: 83.70737517925419
|
303 |
+
- type: cos_sim_spearman
|
304 |
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value: 84.84687698325351
|
305 |
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- type: euclidean_pearson
|
306 |
+
value: 84.36525309890885
|
307 |
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- type: euclidean_spearman
|
308 |
+
value: 84.84688249844098
|
309 |
+
- type: manhattan_pearson
|
310 |
+
value: 84.31171573973266
|
311 |
+
- type: manhattan_spearman
|
312 |
+
value: 84.79550448196474
|
313 |
+
- task:
|
314 |
+
type: PairClassification
|
315 |
+
dataset:
|
316 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
317 |
+
name: MTEB SprintDuplicateQuestions
|
318 |
+
config: default
|
319 |
+
split: test
|
320 |
+
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
321 |
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metrics:
|
322 |
+
- type: cos_sim_accuracy
|
323 |
+
value: 99.87722772277228
|
324 |
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- type: cos_sim_ap
|
325 |
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value: 97.32479581402639
|
326 |
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- type: cos_sim_f1
|
327 |
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value: 93.74369323915236
|
328 |
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- type: cos_sim_precision
|
329 |
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value: 94.60285132382892
|
330 |
+
- type: cos_sim_recall
|
331 |
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value: 92.9
|
332 |
+
- type: dot_accuracy
|
333 |
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value: 99.87722772277228
|
334 |
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- type: dot_ap
|
335 |
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value: 97.32479581402637
|
336 |
+
- type: dot_f1
|
337 |
+
value: 93.74369323915236
|
338 |
+
- type: dot_precision
|
339 |
+
value: 94.60285132382892
|
340 |
+
- type: dot_recall
|
341 |
+
value: 92.9
|
342 |
+
- type: euclidean_accuracy
|
343 |
+
value: 99.87722772277228
|
344 |
+
- type: euclidean_ap
|
345 |
+
value: 97.32479581402639
|
346 |
+
- type: euclidean_f1
|
347 |
+
value: 93.74369323915236
|
348 |
+
- type: euclidean_precision
|
349 |
+
value: 94.60285132382892
|
350 |
+
- type: euclidean_recall
|
351 |
+
value: 92.9
|
352 |
+
- type: manhattan_accuracy
|
353 |
+
value: 99.87524752475248
|
354 |
+
- type: manhattan_ap
|
355 |
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value: 97.29133330261223
|
356 |
+
- type: manhattan_f1
|
357 |
+
value: 93.59359359359361
|
358 |
+
- type: manhattan_precision
|
359 |
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value: 93.687374749499
|
360 |
+
- type: manhattan_recall
|
361 |
+
value: 93.5
|
362 |
+
- type: max_accuracy
|
363 |
+
value: 99.87722772277228
|
364 |
+
- type: max_ap
|
365 |
+
value: 97.32479581402639
|
366 |
+
- type: max_f1
|
367 |
+
value: 93.74369323915236
|
368 |
+
- task:
|
369 |
+
type: Classification
|
370 |
+
dataset:
|
371 |
+
type: mteb/toxic_conversations_50k
|
372 |
+
name: MTEB ToxicConversationsClassification
|
373 |
+
config: default
|
374 |
+
split: test
|
375 |
+
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
376 |
+
metrics:
|
377 |
+
- type: accuracy
|
378 |
+
value: 72.60060000000001
|
379 |
+
- type: ap
|
380 |
+
value: 15.719924742317021
|
381 |
+
- type: f1
|
382 |
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value: 56.30561683159878
|
383 |
+
- task:
|
384 |
+
type: Classification
|
385 |
+
dataset:
|
386 |
+
type: mteb/tweet_sentiment_extraction
|
387 |
+
name: MTEB TweetSentimentExtractionClassification
|
388 |
+
config: default
|
389 |
+
split: test
|
390 |
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revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
391 |
+
metrics:
|
392 |
+
- type: accuracy
|
393 |
+
value: 63.71250707413696
|
394 |
+
- type: f1
|
395 |
+
value: 63.54808116265952
|
396 |
+
- task:
|
397 |
+
type: PairClassification
|
398 |
+
dataset:
|
399 |
+
type: mteb/twittersemeval2015-pairclassification
|
400 |
+
name: MTEB TwitterSemEval2015
|
401 |
+
config: default
|
402 |
+
split: test
|
403 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
404 |
+
metrics:
|
405 |
+
- type: cos_sim_accuracy
|
406 |
+
value: 85.110568039578
|
407 |
+
- type: cos_sim_ap
|
408 |
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value: 70.28927714315245
|
409 |
+
- type: cos_sim_f1
|
410 |
+
value: 65.03893361488716
|
411 |
+
- type: cos_sim_precision
|
412 |
+
value: 65.06469500924214
|
413 |
+
- type: cos_sim_recall
|
414 |
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value: 65.0131926121372
|
415 |
+
- type: dot_accuracy
|
416 |
+
value: 85.110568039578
|
417 |
+
- type: dot_ap
|
418 |
+
value: 70.28928082939848
|
419 |
+
- type: dot_f1
|
420 |
+
value: 65.03893361488716
|
421 |
+
- type: dot_precision
|
422 |
+
value: 65.06469500924214
|
423 |
+
- type: dot_recall
|
424 |
+
value: 65.0131926121372
|
425 |
+
- type: euclidean_accuracy
|
426 |
+
value: 85.110568039578
|
427 |
+
- type: euclidean_ap
|
428 |
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value: 70.28928621260852
|
429 |
+
- type: euclidean_f1
|
430 |
+
value: 65.03893361488716
|
431 |
+
- type: euclidean_precision
|
432 |
+
value: 65.06469500924214
|
433 |
+
- type: euclidean_recall
|
434 |
+
value: 65.0131926121372
|
435 |
+
- type: manhattan_accuracy
|
436 |
+
value: 85.02115992132086
|
437 |
+
- type: manhattan_ap
|
438 |
+
value: 70.05813255171925
|
439 |
+
- type: manhattan_f1
|
440 |
+
value: 64.59658311510164
|
441 |
+
- type: manhattan_precision
|
442 |
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value: 61.24379285883188
|
443 |
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- type: manhattan_recall
|
444 |
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value: 68.33773087071239
|
445 |
+
- type: max_accuracy
|
446 |
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value: 85.110568039578
|
447 |
+
- type: max_ap
|
448 |
+
value: 70.28928621260852
|
449 |
+
- type: max_f1
|
450 |
+
value: 65.03893361488716
|
451 |
+
- task:
|
452 |
+
type: PairClassification
|
453 |
+
dataset:
|
454 |
+
type: mteb/twitterurlcorpus-pairclassification
|
455 |
+
name: MTEB TwitterURLCorpus
|
456 |
+
config: default
|
457 |
+
split: test
|
458 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
459 |
+
metrics:
|
460 |
+
- type: cos_sim_accuracy
|
461 |
+
value: 88.99949547871309
|
462 |
+
- type: cos_sim_ap
|
463 |
+
value: 85.82819569154559
|
464 |
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- type: cos_sim_f1
|
465 |
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value: 78.37315338318439
|
466 |
+
- type: cos_sim_precision
|
467 |
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value: 74.46454564358494
|
468 |
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- type: cos_sim_recall
|
469 |
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value: 82.71481367416075
|
470 |
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- type: dot_accuracy
|
471 |
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value: 88.99949547871309
|
472 |
+
- type: dot_ap
|
473 |
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value: 85.82820043407936
|
474 |
+
- type: dot_f1
|
475 |
+
value: 78.37315338318439
|
476 |
+
- type: dot_precision
|
477 |
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value: 74.46454564358494
|
478 |
+
- type: dot_recall
|
479 |
+
value: 82.71481367416075
|
480 |
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- type: euclidean_accuracy
|
481 |
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value: 88.99949547871309
|
482 |
+
- type: euclidean_ap
|
483 |
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value: 85.82819622588083
|
484 |
+
- type: euclidean_f1
|
485 |
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value: 78.37315338318439
|
486 |
+
- type: euclidean_precision
|
487 |
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value: 74.46454564358494
|
488 |
+
- type: euclidean_recall
|
489 |
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value: 82.71481367416075
|
490 |
+
- type: manhattan_accuracy
|
491 |
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value: 88.98009081383165
|
492 |
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- type: manhattan_ap
|
493 |
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value: 85.77393389750326
|
494 |
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- type: manhattan_f1
|
495 |
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value: 78.38852097130243
|
496 |
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- type: manhattan_precision
|
497 |
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value: 75.06341600901916
|
498 |
+
- type: manhattan_recall
|
499 |
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value: 82.0218663381583
|
500 |
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- type: max_accuracy
|
501 |
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value: 88.99949547871309
|
502 |
+
- type: max_ap
|
503 |
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value: 85.82820043407936
|
504 |
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- type: max_f1
|
505 |
+
value: 78.38852097130243
|
506 |
+
---
|