Update README.md
Browse files
README.md
CHANGED
@@ -5,6 +5,1158 @@ tags:
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5 |
- feature-extraction
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6 |
- sentence-similarity
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7 |
- transformers
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8 |
language: pl
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9 |
license: apache-2.0
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10 |
widget:
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5 |
- feature-extraction
|
6 |
- sentence-similarity
|
7 |
- transformers
|
8 |
+
- mteb
|
9 |
+
model-index:
|
10 |
+
- name: mmlw-e5-large
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11 |
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results:
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12 |
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- task:
|
13 |
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type: Clustering
|
14 |
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dataset:
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15 |
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type: PL-MTEB/8tags-clustering
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16 |
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name: MTEB 8TagsClustering
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17 |
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config: default
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18 |
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split: test
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19 |
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revision: None
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20 |
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metrics:
|
21 |
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- type: v_measure
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22 |
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value: 30.623921415441725
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23 |
+
- task:
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24 |
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type: Classification
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25 |
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dataset:
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26 |
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type: PL-MTEB/allegro-reviews
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27 |
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name: MTEB AllegroReviews
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28 |
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config: default
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29 |
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split: test
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30 |
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revision: None
|
31 |
+
metrics:
|
32 |
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- type: accuracy
|
33 |
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value: 37.683896620278325
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34 |
+
- type: f1
|
35 |
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value: 34.19193027014284
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36 |
+
- task:
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37 |
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type: Retrieval
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38 |
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dataset:
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39 |
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type: arguana-pl
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40 |
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name: MTEB ArguAna-PL
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41 |
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config: default
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42 |
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split: test
|
43 |
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revision: None
|
44 |
+
metrics:
|
45 |
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- type: map_at_1
|
46 |
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value: 38.407000000000004
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47 |
+
- type: map_at_10
|
48 |
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value: 55.147
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49 |
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- type: map_at_100
|
50 |
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value: 55.757
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51 |
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- type: map_at_1000
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52 |
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value: 55.761
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53 |
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- type: map_at_3
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54 |
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value: 51.268
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55 |
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- type: map_at_5
|
56 |
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value: 53.696999999999996
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57 |
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- type: mrr_at_1
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58 |
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value: 40.043
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59 |
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- type: mrr_at_10
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60 |
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value: 55.840999999999994
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61 |
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- type: mrr_at_100
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62 |
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value: 56.459
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63 |
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- type: mrr_at_1000
|
64 |
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value: 56.462999999999994
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65 |
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- type: mrr_at_3
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66 |
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value: 52.074
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67 |
+
- type: mrr_at_5
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68 |
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value: 54.364999999999995
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69 |
+
- type: ndcg_at_1
|
70 |
+
value: 38.407000000000004
|
71 |
+
- type: ndcg_at_10
|
72 |
+
value: 63.248000000000005
|
73 |
+
- type: ndcg_at_100
|
74 |
+
value: 65.717
|
75 |
+
- type: ndcg_at_1000
|
76 |
+
value: 65.79
|
77 |
+
- type: ndcg_at_3
|
78 |
+
value: 55.403999999999996
|
79 |
+
- type: ndcg_at_5
|
80 |
+
value: 59.760000000000005
|
81 |
+
- type: precision_at_1
|
82 |
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value: 38.407000000000004
|
83 |
+
- type: precision_at_10
|
84 |
+
value: 8.862
|
85 |
+
- type: precision_at_100
|
86 |
+
value: 0.991
|
87 |
+
- type: precision_at_1000
|
88 |
+
value: 0.1
|
89 |
+
- type: precision_at_3
|
90 |
+
value: 22.451
|
91 |
+
- type: precision_at_5
|
92 |
+
value: 15.576
|
93 |
+
- type: recall_at_1
|
94 |
+
value: 38.407000000000004
|
95 |
+
- type: recall_at_10
|
96 |
+
value: 88.62
|
97 |
+
- type: recall_at_100
|
98 |
+
value: 99.075
|
99 |
+
- type: recall_at_1000
|
100 |
+
value: 99.57300000000001
|
101 |
+
- type: recall_at_3
|
102 |
+
value: 67.354
|
103 |
+
- type: recall_at_5
|
104 |
+
value: 77.881
|
105 |
+
- task:
|
106 |
+
type: Classification
|
107 |
+
dataset:
|
108 |
+
type: PL-MTEB/cbd
|
109 |
+
name: MTEB CBD
|
110 |
+
config: default
|
111 |
+
split: test
|
112 |
+
revision: None
|
113 |
+
metrics:
|
114 |
+
- type: accuracy
|
115 |
+
value: 66.14999999999999
|
116 |
+
- type: ap
|
117 |
+
value: 21.69513674684204
|
118 |
+
- type: f1
|
119 |
+
value: 56.48142830893528
|
120 |
+
- task:
|
121 |
+
type: PairClassification
|
122 |
+
dataset:
|
123 |
+
type: PL-MTEB/cdsce-pairclassification
|
124 |
+
name: MTEB CDSC-E
|
125 |
+
config: default
|
126 |
+
split: test
|
127 |
+
revision: None
|
128 |
+
metrics:
|
129 |
+
- type: cos_sim_accuracy
|
130 |
+
value: 89.4
|
131 |
+
- type: cos_sim_ap
|
132 |
+
value: 76.83228768203222
|
133 |
+
- type: cos_sim_f1
|
134 |
+
value: 65.3658536585366
|
135 |
+
- type: cos_sim_precision
|
136 |
+
value: 60.909090909090914
|
137 |
+
- type: cos_sim_recall
|
138 |
+
value: 70.52631578947368
|
139 |
+
- type: dot_accuracy
|
140 |
+
value: 84.1
|
141 |
+
- type: dot_ap
|
142 |
+
value: 57.26072201751864
|
143 |
+
- type: dot_f1
|
144 |
+
value: 62.75395033860045
|
145 |
+
- type: dot_precision
|
146 |
+
value: 54.9407114624506
|
147 |
+
- type: dot_recall
|
148 |
+
value: 73.15789473684211
|
149 |
+
- type: euclidean_accuracy
|
150 |
+
value: 89.4
|
151 |
+
- type: euclidean_ap
|
152 |
+
value: 76.59095263388942
|
153 |
+
- type: euclidean_f1
|
154 |
+
value: 65.21739130434783
|
155 |
+
- type: euclidean_precision
|
156 |
+
value: 60.26785714285714
|
157 |
+
- type: euclidean_recall
|
158 |
+
value: 71.05263157894737
|
159 |
+
- type: manhattan_accuracy
|
160 |
+
value: 89.4
|
161 |
+
- type: manhattan_ap
|
162 |
+
value: 76.58825999753456
|
163 |
+
- type: manhattan_f1
|
164 |
+
value: 64.72019464720195
|
165 |
+
- type: manhattan_precision
|
166 |
+
value: 60.18099547511312
|
167 |
+
- type: manhattan_recall
|
168 |
+
value: 70.0
|
169 |
+
- type: max_accuracy
|
170 |
+
value: 89.4
|
171 |
+
- type: max_ap
|
172 |
+
value: 76.83228768203222
|
173 |
+
- type: max_f1
|
174 |
+
value: 65.3658536585366
|
175 |
+
- task:
|
176 |
+
type: STS
|
177 |
+
dataset:
|
178 |
+
type: PL-MTEB/cdscr-sts
|
179 |
+
name: MTEB CDSC-R
|
180 |
+
config: default
|
181 |
+
split: test
|
182 |
+
revision: None
|
183 |
+
metrics:
|
184 |
+
- type: cos_sim_pearson
|
185 |
+
value: 93.73949495291659
|
186 |
+
- type: cos_sim_spearman
|
187 |
+
value: 93.50397366192922
|
188 |
+
- type: euclidean_pearson
|
189 |
+
value: 92.47498888987636
|
190 |
+
- type: euclidean_spearman
|
191 |
+
value: 93.39315936230747
|
192 |
+
- type: manhattan_pearson
|
193 |
+
value: 92.47250250777654
|
194 |
+
- type: manhattan_spearman
|
195 |
+
value: 93.36739690549109
|
196 |
+
- task:
|
197 |
+
type: Retrieval
|
198 |
+
dataset:
|
199 |
+
type: dbpedia-pl
|
200 |
+
name: MTEB DBPedia-PL
|
201 |
+
config: default
|
202 |
+
split: test
|
203 |
+
revision: None
|
204 |
+
metrics:
|
205 |
+
- type: map_at_1
|
206 |
+
value: 8.434
|
207 |
+
- type: map_at_10
|
208 |
+
value: 18.424
|
209 |
+
- type: map_at_100
|
210 |
+
value: 26.428
|
211 |
+
- type: map_at_1000
|
212 |
+
value: 28.002
|
213 |
+
- type: map_at_3
|
214 |
+
value: 13.502
|
215 |
+
- type: map_at_5
|
216 |
+
value: 15.577
|
217 |
+
- type: mrr_at_1
|
218 |
+
value: 63.0
|
219 |
+
- type: mrr_at_10
|
220 |
+
value: 72.714
|
221 |
+
- type: mrr_at_100
|
222 |
+
value: 73.021
|
223 |
+
- type: mrr_at_1000
|
224 |
+
value: 73.028
|
225 |
+
- type: mrr_at_3
|
226 |
+
value: 70.75
|
227 |
+
- type: mrr_at_5
|
228 |
+
value: 72.3
|
229 |
+
- type: ndcg_at_1
|
230 |
+
value: 52.75
|
231 |
+
- type: ndcg_at_10
|
232 |
+
value: 39.839999999999996
|
233 |
+
- type: ndcg_at_100
|
234 |
+
value: 44.989000000000004
|
235 |
+
- type: ndcg_at_1000
|
236 |
+
value: 52.532999999999994
|
237 |
+
- type: ndcg_at_3
|
238 |
+
value: 45.198
|
239 |
+
- type: ndcg_at_5
|
240 |
+
value: 42.015
|
241 |
+
- type: precision_at_1
|
242 |
+
value: 63.0
|
243 |
+
- type: precision_at_10
|
244 |
+
value: 31.05
|
245 |
+
- type: precision_at_100
|
246 |
+
value: 10.26
|
247 |
+
- type: precision_at_1000
|
248 |
+
value: 1.9879999999999998
|
249 |
+
- type: precision_at_3
|
250 |
+
value: 48.25
|
251 |
+
- type: precision_at_5
|
252 |
+
value: 40.45
|
253 |
+
- type: recall_at_1
|
254 |
+
value: 8.434
|
255 |
+
- type: recall_at_10
|
256 |
+
value: 24.004
|
257 |
+
- type: recall_at_100
|
258 |
+
value: 51.428
|
259 |
+
- type: recall_at_1000
|
260 |
+
value: 75.712
|
261 |
+
- type: recall_at_3
|
262 |
+
value: 15.015
|
263 |
+
- type: recall_at_5
|
264 |
+
value: 18.282999999999998
|
265 |
+
- task:
|
266 |
+
type: Retrieval
|
267 |
+
dataset:
|
268 |
+
type: fiqa-pl
|
269 |
+
name: MTEB FiQA-PL
|
270 |
+
config: default
|
271 |
+
split: test
|
272 |
+
revision: None
|
273 |
+
metrics:
|
274 |
+
- type: map_at_1
|
275 |
+
value: 19.088
|
276 |
+
- type: map_at_10
|
277 |
+
value: 31.818
|
278 |
+
- type: map_at_100
|
279 |
+
value: 33.689
|
280 |
+
- type: map_at_1000
|
281 |
+
value: 33.86
|
282 |
+
- type: map_at_3
|
283 |
+
value: 27.399
|
284 |
+
- type: map_at_5
|
285 |
+
value: 29.945
|
286 |
+
- type: mrr_at_1
|
287 |
+
value: 38.117000000000004
|
288 |
+
- type: mrr_at_10
|
289 |
+
value: 47.668
|
290 |
+
- type: mrr_at_100
|
291 |
+
value: 48.428
|
292 |
+
- type: mrr_at_1000
|
293 |
+
value: 48.475
|
294 |
+
- type: mrr_at_3
|
295 |
+
value: 45.242
|
296 |
+
- type: mrr_at_5
|
297 |
+
value: 46.716
|
298 |
+
- type: ndcg_at_1
|
299 |
+
value: 38.272
|
300 |
+
- type: ndcg_at_10
|
301 |
+
value: 39.903
|
302 |
+
- type: ndcg_at_100
|
303 |
+
value: 46.661
|
304 |
+
- type: ndcg_at_1000
|
305 |
+
value: 49.625
|
306 |
+
- type: ndcg_at_3
|
307 |
+
value: 35.921
|
308 |
+
- type: ndcg_at_5
|
309 |
+
value: 37.558
|
310 |
+
- type: precision_at_1
|
311 |
+
value: 38.272
|
312 |
+
- type: precision_at_10
|
313 |
+
value: 11.358
|
314 |
+
- type: precision_at_100
|
315 |
+
value: 1.8190000000000002
|
316 |
+
- type: precision_at_1000
|
317 |
+
value: 0.23500000000000001
|
318 |
+
- type: precision_at_3
|
319 |
+
value: 24.434
|
320 |
+
- type: precision_at_5
|
321 |
+
value: 18.395
|
322 |
+
- type: recall_at_1
|
323 |
+
value: 19.088
|
324 |
+
- type: recall_at_10
|
325 |
+
value: 47.355999999999995
|
326 |
+
- type: recall_at_100
|
327 |
+
value: 72.451
|
328 |
+
- type: recall_at_1000
|
329 |
+
value: 90.257
|
330 |
+
- type: recall_at_3
|
331 |
+
value: 32.931
|
332 |
+
- type: recall_at_5
|
333 |
+
value: 39.878
|
334 |
+
- task:
|
335 |
+
type: Retrieval
|
336 |
+
dataset:
|
337 |
+
type: hotpotqa-pl
|
338 |
+
name: MTEB HotpotQA-PL
|
339 |
+
config: default
|
340 |
+
split: test
|
341 |
+
revision: None
|
342 |
+
metrics:
|
343 |
+
- type: map_at_1
|
344 |
+
value: 39.095
|
345 |
+
- type: map_at_10
|
346 |
+
value: 62.529
|
347 |
+
- type: map_at_100
|
348 |
+
value: 63.425
|
349 |
+
- type: map_at_1000
|
350 |
+
value: 63.483000000000004
|
351 |
+
- type: map_at_3
|
352 |
+
value: 58.887
|
353 |
+
- type: map_at_5
|
354 |
+
value: 61.18599999999999
|
355 |
+
- type: mrr_at_1
|
356 |
+
value: 78.123
|
357 |
+
- type: mrr_at_10
|
358 |
+
value: 84.231
|
359 |
+
- type: mrr_at_100
|
360 |
+
value: 84.408
|
361 |
+
- type: mrr_at_1000
|
362 |
+
value: 84.414
|
363 |
+
- type: mrr_at_3
|
364 |
+
value: 83.286
|
365 |
+
- type: mrr_at_5
|
366 |
+
value: 83.94
|
367 |
+
- type: ndcg_at_1
|
368 |
+
value: 78.19
|
369 |
+
- type: ndcg_at_10
|
370 |
+
value: 70.938
|
371 |
+
- type: ndcg_at_100
|
372 |
+
value: 73.992
|
373 |
+
- type: ndcg_at_1000
|
374 |
+
value: 75.1
|
375 |
+
- type: ndcg_at_3
|
376 |
+
value: 65.863
|
377 |
+
- type: ndcg_at_5
|
378 |
+
value: 68.755
|
379 |
+
- type: precision_at_1
|
380 |
+
value: 78.19
|
381 |
+
- type: precision_at_10
|
382 |
+
value: 14.949000000000002
|
383 |
+
- type: precision_at_100
|
384 |
+
value: 1.733
|
385 |
+
- type: precision_at_1000
|
386 |
+
value: 0.188
|
387 |
+
- type: precision_at_3
|
388 |
+
value: 42.381
|
389 |
+
- type: precision_at_5
|
390 |
+
value: 27.711000000000002
|
391 |
+
- type: recall_at_1
|
392 |
+
value: 39.095
|
393 |
+
- type: recall_at_10
|
394 |
+
value: 74.747
|
395 |
+
- type: recall_at_100
|
396 |
+
value: 86.631
|
397 |
+
- type: recall_at_1000
|
398 |
+
value: 93.923
|
399 |
+
- type: recall_at_3
|
400 |
+
value: 63.571999999999996
|
401 |
+
- type: recall_at_5
|
402 |
+
value: 69.27799999999999
|
403 |
+
- task:
|
404 |
+
type: Retrieval
|
405 |
+
dataset:
|
406 |
+
type: msmarco-pl
|
407 |
+
name: MTEB MSMARCO-PL
|
408 |
+
config: default
|
409 |
+
split: validation
|
410 |
+
revision: None
|
411 |
+
metrics:
|
412 |
+
- type: map_at_1
|
413 |
+
value: 19.439999999999998
|
414 |
+
- type: map_at_10
|
415 |
+
value: 30.264000000000003
|
416 |
+
- type: map_at_100
|
417 |
+
value: 31.438
|
418 |
+
- type: map_at_1000
|
419 |
+
value: 31.495
|
420 |
+
- type: map_at_3
|
421 |
+
value: 26.735
|
422 |
+
- type: map_at_5
|
423 |
+
value: 28.716
|
424 |
+
- type: mrr_at_1
|
425 |
+
value: 19.914
|
426 |
+
- type: mrr_at_10
|
427 |
+
value: 30.753999999999998
|
428 |
+
- type: mrr_at_100
|
429 |
+
value: 31.877
|
430 |
+
- type: mrr_at_1000
|
431 |
+
value: 31.929000000000002
|
432 |
+
- type: mrr_at_3
|
433 |
+
value: 27.299
|
434 |
+
- type: mrr_at_5
|
435 |
+
value: 29.254
|
436 |
+
- type: ndcg_at_1
|
437 |
+
value: 20.014000000000003
|
438 |
+
- type: ndcg_at_10
|
439 |
+
value: 36.472
|
440 |
+
- type: ndcg_at_100
|
441 |
+
value: 42.231
|
442 |
+
- type: ndcg_at_1000
|
443 |
+
value: 43.744
|
444 |
+
- type: ndcg_at_3
|
445 |
+
value: 29.268
|
446 |
+
- type: ndcg_at_5
|
447 |
+
value: 32.79
|
448 |
+
- type: precision_at_1
|
449 |
+
value: 20.014000000000003
|
450 |
+
- type: precision_at_10
|
451 |
+
value: 5.814
|
452 |
+
- type: precision_at_100
|
453 |
+
value: 0.8710000000000001
|
454 |
+
- type: precision_at_1000
|
455 |
+
value: 0.1
|
456 |
+
- type: precision_at_3
|
457 |
+
value: 12.426
|
458 |
+
- type: precision_at_5
|
459 |
+
value: 9.238
|
460 |
+
- type: recall_at_1
|
461 |
+
value: 19.439999999999998
|
462 |
+
- type: recall_at_10
|
463 |
+
value: 55.535000000000004
|
464 |
+
- type: recall_at_100
|
465 |
+
value: 82.44399999999999
|
466 |
+
- type: recall_at_1000
|
467 |
+
value: 94.217
|
468 |
+
- type: recall_at_3
|
469 |
+
value: 35.963
|
470 |
+
- type: recall_at_5
|
471 |
+
value: 44.367000000000004
|
472 |
+
- task:
|
473 |
+
type: Classification
|
474 |
+
dataset:
|
475 |
+
type: mteb/amazon_massive_intent
|
476 |
+
name: MTEB MassiveIntentClassification (pl)
|
477 |
+
config: pl
|
478 |
+
split: test
|
479 |
+
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
480 |
+
metrics:
|
481 |
+
- type: accuracy
|
482 |
+
value: 72.01412239408205
|
483 |
+
- type: f1
|
484 |
+
value: 70.04544187503352
|
485 |
+
- task:
|
486 |
+
type: Classification
|
487 |
+
dataset:
|
488 |
+
type: mteb/amazon_massive_scenario
|
489 |
+
name: MTEB MassiveScenarioClassification (pl)
|
490 |
+
config: pl
|
491 |
+
split: test
|
492 |
+
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
493 |
+
metrics:
|
494 |
+
- type: accuracy
|
495 |
+
value: 75.26899798251513
|
496 |
+
- type: f1
|
497 |
+
value: 75.55876166863844
|
498 |
+
- task:
|
499 |
+
type: Retrieval
|
500 |
+
dataset:
|
501 |
+
type: nfcorpus-pl
|
502 |
+
name: MTEB NFCorpus-PL
|
503 |
+
config: default
|
504 |
+
split: test
|
505 |
+
revision: None
|
506 |
+
metrics:
|
507 |
+
- type: map_at_1
|
508 |
+
value: 5.772
|
509 |
+
- type: map_at_10
|
510 |
+
value: 12.708
|
511 |
+
- type: map_at_100
|
512 |
+
value: 16.194
|
513 |
+
- type: map_at_1000
|
514 |
+
value: 17.630000000000003
|
515 |
+
- type: map_at_3
|
516 |
+
value: 9.34
|
517 |
+
- type: map_at_5
|
518 |
+
value: 10.741
|
519 |
+
- type: mrr_at_1
|
520 |
+
value: 43.344
|
521 |
+
- type: mrr_at_10
|
522 |
+
value: 53.429
|
523 |
+
- type: mrr_at_100
|
524 |
+
value: 53.88699999999999
|
525 |
+
- type: mrr_at_1000
|
526 |
+
value: 53.925
|
527 |
+
- type: mrr_at_3
|
528 |
+
value: 51.342
|
529 |
+
- type: mrr_at_5
|
530 |
+
value: 52.456
|
531 |
+
- type: ndcg_at_1
|
532 |
+
value: 41.641
|
533 |
+
- type: ndcg_at_10
|
534 |
+
value: 34.028000000000006
|
535 |
+
- type: ndcg_at_100
|
536 |
+
value: 31.613000000000003
|
537 |
+
- type: ndcg_at_1000
|
538 |
+
value: 40.428
|
539 |
+
- type: ndcg_at_3
|
540 |
+
value: 38.991
|
541 |
+
- type: ndcg_at_5
|
542 |
+
value: 36.704
|
543 |
+
- type: precision_at_1
|
544 |
+
value: 43.034
|
545 |
+
- type: precision_at_10
|
546 |
+
value: 25.324999999999996
|
547 |
+
- type: precision_at_100
|
548 |
+
value: 7.889
|
549 |
+
- type: precision_at_1000
|
550 |
+
value: 2.069
|
551 |
+
- type: precision_at_3
|
552 |
+
value: 36.739
|
553 |
+
- type: precision_at_5
|
554 |
+
value: 32.074000000000005
|
555 |
+
- type: recall_at_1
|
556 |
+
value: 5.772
|
557 |
+
- type: recall_at_10
|
558 |
+
value: 16.827
|
559 |
+
- type: recall_at_100
|
560 |
+
value: 32.346000000000004
|
561 |
+
- type: recall_at_1000
|
562 |
+
value: 62.739
|
563 |
+
- type: recall_at_3
|
564 |
+
value: 10.56
|
565 |
+
- type: recall_at_5
|
566 |
+
value: 12.655
|
567 |
+
- task:
|
568 |
+
type: Retrieval
|
569 |
+
dataset:
|
570 |
+
type: nq-pl
|
571 |
+
name: MTEB NQ-PL
|
572 |
+
config: default
|
573 |
+
split: test
|
574 |
+
revision: None
|
575 |
+
metrics:
|
576 |
+
- type: map_at_1
|
577 |
+
value: 26.101000000000003
|
578 |
+
- type: map_at_10
|
579 |
+
value: 39.912
|
580 |
+
- type: map_at_100
|
581 |
+
value: 41.037
|
582 |
+
- type: map_at_1000
|
583 |
+
value: 41.077000000000005
|
584 |
+
- type: map_at_3
|
585 |
+
value: 35.691
|
586 |
+
- type: map_at_5
|
587 |
+
value: 38.155
|
588 |
+
- type: mrr_at_1
|
589 |
+
value: 29.403000000000002
|
590 |
+
- type: mrr_at_10
|
591 |
+
value: 42.376999999999995
|
592 |
+
- type: mrr_at_100
|
593 |
+
value: 43.248999999999995
|
594 |
+
- type: mrr_at_1000
|
595 |
+
value: 43.277
|
596 |
+
- type: mrr_at_3
|
597 |
+
value: 38.794000000000004
|
598 |
+
- type: mrr_at_5
|
599 |
+
value: 40.933
|
600 |
+
- type: ndcg_at_1
|
601 |
+
value: 29.519000000000002
|
602 |
+
- type: ndcg_at_10
|
603 |
+
value: 47.33
|
604 |
+
- type: ndcg_at_100
|
605 |
+
value: 52.171
|
606 |
+
- type: ndcg_at_1000
|
607 |
+
value: 53.125
|
608 |
+
- type: ndcg_at_3
|
609 |
+
value: 39.316
|
610 |
+
- type: ndcg_at_5
|
611 |
+
value: 43.457
|
612 |
+
- type: precision_at_1
|
613 |
+
value: 29.519000000000002
|
614 |
+
- type: precision_at_10
|
615 |
+
value: 8.03
|
616 |
+
- type: precision_at_100
|
617 |
+
value: 1.075
|
618 |
+
- type: precision_at_1000
|
619 |
+
value: 0.117
|
620 |
+
- type: precision_at_3
|
621 |
+
value: 18.009
|
622 |
+
- type: precision_at_5
|
623 |
+
value: 13.221
|
624 |
+
- type: recall_at_1
|
625 |
+
value: 26.101000000000003
|
626 |
+
- type: recall_at_10
|
627 |
+
value: 67.50399999999999
|
628 |
+
- type: recall_at_100
|
629 |
+
value: 88.64699999999999
|
630 |
+
- type: recall_at_1000
|
631 |
+
value: 95.771
|
632 |
+
- type: recall_at_3
|
633 |
+
value: 46.669
|
634 |
+
- type: recall_at_5
|
635 |
+
value: 56.24
|
636 |
+
- task:
|
637 |
+
type: Classification
|
638 |
+
dataset:
|
639 |
+
type: laugustyniak/abusive-clauses-pl
|
640 |
+
name: MTEB PAC
|
641 |
+
config: default
|
642 |
+
split: test
|
643 |
+
revision: None
|
644 |
+
metrics:
|
645 |
+
- type: accuracy
|
646 |
+
value: 63.76773819866782
|
647 |
+
- type: ap
|
648 |
+
value: 74.87896817642536
|
649 |
+
- type: f1
|
650 |
+
value: 61.420506092721425
|
651 |
+
- task:
|
652 |
+
type: PairClassification
|
653 |
+
dataset:
|
654 |
+
type: PL-MTEB/ppc-pairclassification
|
655 |
+
name: MTEB PPC
|
656 |
+
config: default
|
657 |
+
split: test
|
658 |
+
revision: None
|
659 |
+
metrics:
|
660 |
+
- type: cos_sim_accuracy
|
661 |
+
value: 82.1
|
662 |
+
- type: cos_sim_ap
|
663 |
+
value: 91.09417013497443
|
664 |
+
- type: cos_sim_f1
|
665 |
+
value: 84.78437754271766
|
666 |
+
- type: cos_sim_precision
|
667 |
+
value: 83.36
|
668 |
+
- type: cos_sim_recall
|
669 |
+
value: 86.25827814569537
|
670 |
+
- type: dot_accuracy
|
671 |
+
value: 75.9
|
672 |
+
- type: dot_ap
|
673 |
+
value: 86.82680649789796
|
674 |
+
- type: dot_f1
|
675 |
+
value: 80.5379746835443
|
676 |
+
- type: dot_precision
|
677 |
+
value: 77.12121212121212
|
678 |
+
- type: dot_recall
|
679 |
+
value: 84.27152317880795
|
680 |
+
- type: euclidean_accuracy
|
681 |
+
value: 81.6
|
682 |
+
- type: euclidean_ap
|
683 |
+
value: 90.81248760600693
|
684 |
+
- type: euclidean_f1
|
685 |
+
value: 84.35374149659863
|
686 |
+
- type: euclidean_precision
|
687 |
+
value: 86.7132867132867
|
688 |
+
- type: euclidean_recall
|
689 |
+
value: 82.11920529801324
|
690 |
+
- type: manhattan_accuracy
|
691 |
+
value: 81.6
|
692 |
+
- type: manhattan_ap
|
693 |
+
value: 90.81272803548767
|
694 |
+
- type: manhattan_f1
|
695 |
+
value: 84.33530906011855
|
696 |
+
- type: manhattan_precision
|
697 |
+
value: 86.30849220103987
|
698 |
+
- type: manhattan_recall
|
699 |
+
value: 82.45033112582782
|
700 |
+
- type: max_accuracy
|
701 |
+
value: 82.1
|
702 |
+
- type: max_ap
|
703 |
+
value: 91.09417013497443
|
704 |
+
- type: max_f1
|
705 |
+
value: 84.78437754271766
|
706 |
+
- task:
|
707 |
+
type: PairClassification
|
708 |
+
dataset:
|
709 |
+
type: PL-MTEB/psc-pairclassification
|
710 |
+
name: MTEB PSC
|
711 |
+
config: default
|
712 |
+
split: test
|
713 |
+
revision: None
|
714 |
+
metrics:
|
715 |
+
- type: cos_sim_accuracy
|
716 |
+
value: 98.05194805194806
|
717 |
+
- type: cos_sim_ap
|
718 |
+
value: 99.52709687103496
|
719 |
+
- type: cos_sim_f1
|
720 |
+
value: 96.83257918552036
|
721 |
+
- type: cos_sim_precision
|
722 |
+
value: 95.82089552238806
|
723 |
+
- type: cos_sim_recall
|
724 |
+
value: 97.86585365853658
|
725 |
+
- type: dot_accuracy
|
726 |
+
value: 92.30055658627087
|
727 |
+
- type: dot_ap
|
728 |
+
value: 94.12759311032353
|
729 |
+
- type: dot_f1
|
730 |
+
value: 87.00906344410878
|
731 |
+
- type: dot_precision
|
732 |
+
value: 86.22754491017965
|
733 |
+
- type: dot_recall
|
734 |
+
value: 87.8048780487805
|
735 |
+
- type: euclidean_accuracy
|
736 |
+
value: 98.05194805194806
|
737 |
+
- type: euclidean_ap
|
738 |
+
value: 99.49402675624125
|
739 |
+
- type: euclidean_f1
|
740 |
+
value: 96.8133535660091
|
741 |
+
- type: euclidean_precision
|
742 |
+
value: 96.37462235649546
|
743 |
+
- type: euclidean_recall
|
744 |
+
value: 97.2560975609756
|
745 |
+
- type: manhattan_accuracy
|
746 |
+
value: 98.05194805194806
|
747 |
+
- type: manhattan_ap
|
748 |
+
value: 99.50120505935962
|
749 |
+
- type: manhattan_f1
|
750 |
+
value: 96.8133535660091
|
751 |
+
- type: manhattan_precision
|
752 |
+
value: 96.37462235649546
|
753 |
+
- type: manhattan_recall
|
754 |
+
value: 97.2560975609756
|
755 |
+
- type: max_accuracy
|
756 |
+
value: 98.05194805194806
|
757 |
+
- type: max_ap
|
758 |
+
value: 99.52709687103496
|
759 |
+
- type: max_f1
|
760 |
+
value: 96.83257918552036
|
761 |
+
- task:
|
762 |
+
type: Classification
|
763 |
+
dataset:
|
764 |
+
type: PL-MTEB/polemo2_in
|
765 |
+
name: MTEB PolEmo2.0-IN
|
766 |
+
config: default
|
767 |
+
split: test
|
768 |
+
revision: None
|
769 |
+
metrics:
|
770 |
+
- type: accuracy
|
771 |
+
value: 69.45983379501385
|
772 |
+
- type: f1
|
773 |
+
value: 68.60917948426784
|
774 |
+
- task:
|
775 |
+
type: Classification
|
776 |
+
dataset:
|
777 |
+
type: PL-MTEB/polemo2_out
|
778 |
+
name: MTEB PolEmo2.0-OUT
|
779 |
+
config: default
|
780 |
+
split: test
|
781 |
+
revision: None
|
782 |
+
metrics:
|
783 |
+
- type: accuracy
|
784 |
+
value: 43.13765182186235
|
785 |
+
- type: f1
|
786 |
+
value: 36.15557441785656
|
787 |
+
- task:
|
788 |
+
type: Retrieval
|
789 |
+
dataset:
|
790 |
+
type: quora-pl
|
791 |
+
name: MTEB Quora-PL
|
792 |
+
config: default
|
793 |
+
split: test
|
794 |
+
revision: None
|
795 |
+
metrics:
|
796 |
+
- type: map_at_1
|
797 |
+
value: 67.448
|
798 |
+
- type: map_at_10
|
799 |
+
value: 81.566
|
800 |
+
- type: map_at_100
|
801 |
+
value: 82.284
|
802 |
+
- type: map_at_1000
|
803 |
+
value: 82.301
|
804 |
+
- type: map_at_3
|
805 |
+
value: 78.425
|
806 |
+
- type: map_at_5
|
807 |
+
value: 80.43400000000001
|
808 |
+
- type: mrr_at_1
|
809 |
+
value: 77.61
|
810 |
+
- type: mrr_at_10
|
811 |
+
value: 84.467
|
812 |
+
- type: mrr_at_100
|
813 |
+
value: 84.63199999999999
|
814 |
+
- type: mrr_at_1000
|
815 |
+
value: 84.634
|
816 |
+
- type: mrr_at_3
|
817 |
+
value: 83.288
|
818 |
+
- type: mrr_at_5
|
819 |
+
value: 84.095
|
820 |
+
- type: ndcg_at_1
|
821 |
+
value: 77.66
|
822 |
+
- type: ndcg_at_10
|
823 |
+
value: 85.63199999999999
|
824 |
+
- type: ndcg_at_100
|
825 |
+
value: 87.166
|
826 |
+
- type: ndcg_at_1000
|
827 |
+
value: 87.306
|
828 |
+
- type: ndcg_at_3
|
829 |
+
value: 82.32300000000001
|
830 |
+
- type: ndcg_at_5
|
831 |
+
value: 84.22
|
832 |
+
- type: precision_at_1
|
833 |
+
value: 77.66
|
834 |
+
- type: precision_at_10
|
835 |
+
value: 13.136000000000001
|
836 |
+
- type: precision_at_100
|
837 |
+
value: 1.522
|
838 |
+
- type: precision_at_1000
|
839 |
+
value: 0.156
|
840 |
+
- type: precision_at_3
|
841 |
+
value: 36.153
|
842 |
+
- type: precision_at_5
|
843 |
+
value: 23.982
|
844 |
+
- type: recall_at_1
|
845 |
+
value: 67.448
|
846 |
+
- type: recall_at_10
|
847 |
+
value: 93.83200000000001
|
848 |
+
- type: recall_at_100
|
849 |
+
value: 99.212
|
850 |
+
- type: recall_at_1000
|
851 |
+
value: 99.94
|
852 |
+
- type: recall_at_3
|
853 |
+
value: 84.539
|
854 |
+
- type: recall_at_5
|
855 |
+
value: 89.71000000000001
|
856 |
+
- task:
|
857 |
+
type: Retrieval
|
858 |
+
dataset:
|
859 |
+
type: scidocs-pl
|
860 |
+
name: MTEB SCIDOCS-PL
|
861 |
+
config: default
|
862 |
+
split: test
|
863 |
+
revision: None
|
864 |
+
metrics:
|
865 |
+
- type: map_at_1
|
866 |
+
value: 4.393
|
867 |
+
- type: map_at_10
|
868 |
+
value: 11.472
|
869 |
+
- type: map_at_100
|
870 |
+
value: 13.584999999999999
|
871 |
+
- type: map_at_1000
|
872 |
+
value: 13.918
|
873 |
+
- type: map_at_3
|
874 |
+
value: 8.212
|
875 |
+
- type: map_at_5
|
876 |
+
value: 9.864
|
877 |
+
- type: mrr_at_1
|
878 |
+
value: 21.7
|
879 |
+
- type: mrr_at_10
|
880 |
+
value: 32.268
|
881 |
+
- type: mrr_at_100
|
882 |
+
value: 33.495000000000005
|
883 |
+
- type: mrr_at_1000
|
884 |
+
value: 33.548
|
885 |
+
- type: mrr_at_3
|
886 |
+
value: 29.15
|
887 |
+
- type: mrr_at_5
|
888 |
+
value: 30.91
|
889 |
+
- type: ndcg_at_1
|
890 |
+
value: 21.6
|
891 |
+
- type: ndcg_at_10
|
892 |
+
value: 19.126
|
893 |
+
- type: ndcg_at_100
|
894 |
+
value: 27.496
|
895 |
+
- type: ndcg_at_1000
|
896 |
+
value: 33.274
|
897 |
+
- type: ndcg_at_3
|
898 |
+
value: 18.196
|
899 |
+
- type: ndcg_at_5
|
900 |
+
value: 15.945
|
901 |
+
- type: precision_at_1
|
902 |
+
value: 21.6
|
903 |
+
- type: precision_at_10
|
904 |
+
value: 9.94
|
905 |
+
- type: precision_at_100
|
906 |
+
value: 2.1999999999999997
|
907 |
+
- type: precision_at_1000
|
908 |
+
value: 0.359
|
909 |
+
- type: precision_at_3
|
910 |
+
value: 17.2
|
911 |
+
- type: precision_at_5
|
912 |
+
value: 14.12
|
913 |
+
- type: recall_at_1
|
914 |
+
value: 4.393
|
915 |
+
- type: recall_at_10
|
916 |
+
value: 20.166999999999998
|
917 |
+
- type: recall_at_100
|
918 |
+
value: 44.678000000000004
|
919 |
+
- type: recall_at_1000
|
920 |
+
value: 72.868
|
921 |
+
- type: recall_at_3
|
922 |
+
value: 10.473
|
923 |
+
- type: recall_at_5
|
924 |
+
value: 14.313
|
925 |
+
- task:
|
926 |
+
type: PairClassification
|
927 |
+
dataset:
|
928 |
+
type: PL-MTEB/sicke-pl-pairclassification
|
929 |
+
name: MTEB SICK-E-PL
|
930 |
+
config: default
|
931 |
+
split: test
|
932 |
+
revision: None
|
933 |
+
metrics:
|
934 |
+
- type: cos_sim_accuracy
|
935 |
+
value: 82.65389319200979
|
936 |
+
- type: cos_sim_ap
|
937 |
+
value: 76.13749398520014
|
938 |
+
- type: cos_sim_f1
|
939 |
+
value: 66.64355062413314
|
940 |
+
- type: cos_sim_precision
|
941 |
+
value: 64.93243243243244
|
942 |
+
- type: cos_sim_recall
|
943 |
+
value: 68.44729344729345
|
944 |
+
- type: dot_accuracy
|
945 |
+
value: 76.0905014268243
|
946 |
+
- type: dot_ap
|
947 |
+
value: 58.058968583382494
|
948 |
+
- type: dot_f1
|
949 |
+
value: 61.181080324657145
|
950 |
+
- type: dot_precision
|
951 |
+
value: 50.391885661595204
|
952 |
+
- type: dot_recall
|
953 |
+
value: 77.84900284900284
|
954 |
+
- type: euclidean_accuracy
|
955 |
+
value: 82.61312678353036
|
956 |
+
- type: euclidean_ap
|
957 |
+
value: 76.10290283033221
|
958 |
+
- type: euclidean_f1
|
959 |
+
value: 66.50782845473111
|
960 |
+
- type: euclidean_precision
|
961 |
+
value: 63.6897001303781
|
962 |
+
- type: euclidean_recall
|
963 |
+
value: 69.58689458689459
|
964 |
+
- type: manhattan_accuracy
|
965 |
+
value: 82.6742763962495
|
966 |
+
- type: manhattan_ap
|
967 |
+
value: 76.12712309700966
|
968 |
+
- type: manhattan_f1
|
969 |
+
value: 66.59700452803902
|
970 |
+
- type: manhattan_precision
|
971 |
+
value: 65.16700749829583
|
972 |
+
- type: manhattan_recall
|
973 |
+
value: 68.09116809116809
|
974 |
+
- type: max_accuracy
|
975 |
+
value: 82.6742763962495
|
976 |
+
- type: max_ap
|
977 |
+
value: 76.13749398520014
|
978 |
+
- type: max_f1
|
979 |
+
value: 66.64355062413314
|
980 |
+
- task:
|
981 |
+
type: STS
|
982 |
+
dataset:
|
983 |
+
type: PL-MTEB/sickr-pl-sts
|
984 |
+
name: MTEB SICK-R-PL
|
985 |
+
config: default
|
986 |
+
split: test
|
987 |
+
revision: None
|
988 |
+
metrics:
|
989 |
+
- type: cos_sim_pearson
|
990 |
+
value: 81.23898481255246
|
991 |
+
- type: cos_sim_spearman
|
992 |
+
value: 76.0416957474899
|
993 |
+
- type: euclidean_pearson
|
994 |
+
value: 78.96475496102107
|
995 |
+
- type: euclidean_spearman
|
996 |
+
value: 76.07208683063504
|
997 |
+
- type: manhattan_pearson
|
998 |
+
value: 78.92666424673251
|
999 |
+
- type: manhattan_spearman
|
1000 |
+
value: 76.04968227583831
|
1001 |
+
- task:
|
1002 |
+
type: STS
|
1003 |
+
dataset:
|
1004 |
+
type: mteb/sts22-crosslingual-sts
|
1005 |
+
name: MTEB STS22 (pl)
|
1006 |
+
config: pl
|
1007 |
+
split: test
|
1008 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
1009 |
+
metrics:
|
1010 |
+
- type: cos_sim_pearson
|
1011 |
+
value: 39.13987124398541
|
1012 |
+
- type: cos_sim_spearman
|
1013 |
+
value: 40.40194528288759
|
1014 |
+
- type: euclidean_pearson
|
1015 |
+
value: 29.14566247168167
|
1016 |
+
- type: euclidean_spearman
|
1017 |
+
value: 39.97389932591777
|
1018 |
+
- type: manhattan_pearson
|
1019 |
+
value: 29.172993134388935
|
1020 |
+
- type: manhattan_spearman
|
1021 |
+
value: 39.85681935287037
|
1022 |
+
- task:
|
1023 |
+
type: Retrieval
|
1024 |
+
dataset:
|
1025 |
+
type: scifact-pl
|
1026 |
+
name: MTEB SciFact-PL
|
1027 |
+
config: default
|
1028 |
+
split: test
|
1029 |
+
revision: None
|
1030 |
+
metrics:
|
1031 |
+
- type: map_at_1
|
1032 |
+
value: 57.260999999999996
|
1033 |
+
- type: map_at_10
|
1034 |
+
value: 66.92399999999999
|
1035 |
+
- type: map_at_100
|
1036 |
+
value: 67.443
|
1037 |
+
- type: map_at_1000
|
1038 |
+
value: 67.47800000000001
|
1039 |
+
- type: map_at_3
|
1040 |
+
value: 64.859
|
1041 |
+
- type: map_at_5
|
1042 |
+
value: 65.71900000000001
|
1043 |
+
- type: mrr_at_1
|
1044 |
+
value: 60.333000000000006
|
1045 |
+
- type: mrr_at_10
|
1046 |
+
value: 67.95400000000001
|
1047 |
+
- type: mrr_at_100
|
1048 |
+
value: 68.42
|
1049 |
+
- type: mrr_at_1000
|
1050 |
+
value: 68.45
|
1051 |
+
- type: mrr_at_3
|
1052 |
+
value: 66.444
|
1053 |
+
- type: mrr_at_5
|
1054 |
+
value: 67.128
|
1055 |
+
- type: ndcg_at_1
|
1056 |
+
value: 60.333000000000006
|
1057 |
+
- type: ndcg_at_10
|
1058 |
+
value: 71.209
|
1059 |
+
- type: ndcg_at_100
|
1060 |
+
value: 73.37
|
1061 |
+
- type: ndcg_at_1000
|
1062 |
+
value: 74.287
|
1063 |
+
- type: ndcg_at_3
|
1064 |
+
value: 67.66799999999999
|
1065 |
+
- type: ndcg_at_5
|
1066 |
+
value: 68.644
|
1067 |
+
- type: precision_at_1
|
1068 |
+
value: 60.333000000000006
|
1069 |
+
- type: precision_at_10
|
1070 |
+
value: 9.467
|
1071 |
+
- type: precision_at_100
|
1072 |
+
value: 1.053
|
1073 |
+
- type: precision_at_1000
|
1074 |
+
value: 0.11299999999999999
|
1075 |
+
- type: precision_at_3
|
1076 |
+
value: 26.778000000000002
|
1077 |
+
- type: precision_at_5
|
1078 |
+
value: 16.933
|
1079 |
+
- type: recall_at_1
|
1080 |
+
value: 57.260999999999996
|
1081 |
+
- type: recall_at_10
|
1082 |
+
value: 83.256
|
1083 |
+
- type: recall_at_100
|
1084 |
+
value: 92.767
|
1085 |
+
- type: recall_at_1000
|
1086 |
+
value: 100.0
|
1087 |
+
- type: recall_at_3
|
1088 |
+
value: 72.933
|
1089 |
+
- type: recall_at_5
|
1090 |
+
value: 75.744
|
1091 |
+
- task:
|
1092 |
+
type: Retrieval
|
1093 |
+
dataset:
|
1094 |
+
type: trec-covid-pl
|
1095 |
+
name: MTEB TRECCOVID-PL
|
1096 |
+
config: default
|
1097 |
+
split: test
|
1098 |
+
revision: None
|
1099 |
+
metrics:
|
1100 |
+
- type: map_at_1
|
1101 |
+
value: 0.22
|
1102 |
+
- type: map_at_10
|
1103 |
+
value: 1.693
|
1104 |
+
- type: map_at_100
|
1105 |
+
value: 9.281
|
1106 |
+
- type: map_at_1000
|
1107 |
+
value: 21.462999999999997
|
1108 |
+
- type: map_at_3
|
1109 |
+
value: 0.609
|
1110 |
+
- type: map_at_5
|
1111 |
+
value: 0.9570000000000001
|
1112 |
+
- type: mrr_at_1
|
1113 |
+
value: 80.0
|
1114 |
+
- type: mrr_at_10
|
1115 |
+
value: 88.73299999999999
|
1116 |
+
- type: mrr_at_100
|
1117 |
+
value: 88.73299999999999
|
1118 |
+
- type: mrr_at_1000
|
1119 |
+
value: 88.73299999999999
|
1120 |
+
- type: mrr_at_3
|
1121 |
+
value: 88.333
|
1122 |
+
- type: mrr_at_5
|
1123 |
+
value: 88.73299999999999
|
1124 |
+
- type: ndcg_at_1
|
1125 |
+
value: 79.0
|
1126 |
+
- type: ndcg_at_10
|
1127 |
+
value: 71.177
|
1128 |
+
- type: ndcg_at_100
|
1129 |
+
value: 52.479
|
1130 |
+
- type: ndcg_at_1000
|
1131 |
+
value: 45.333
|
1132 |
+
- type: ndcg_at_3
|
1133 |
+
value: 77.48
|
1134 |
+
- type: ndcg_at_5
|
1135 |
+
value: 76.137
|
1136 |
+
- type: precision_at_1
|
1137 |
+
value: 82.0
|
1138 |
+
- type: precision_at_10
|
1139 |
+
value: 74.0
|
1140 |
+
- type: precision_at_100
|
1141 |
+
value: 53.68000000000001
|
1142 |
+
- type: precision_at_1000
|
1143 |
+
value: 19.954
|
1144 |
+
- type: precision_at_3
|
1145 |
+
value: 80.667
|
1146 |
+
- type: precision_at_5
|
1147 |
+
value: 80.80000000000001
|
1148 |
+
- type: recall_at_1
|
1149 |
+
value: 0.22
|
1150 |
+
- type: recall_at_10
|
1151 |
+
value: 1.934
|
1152 |
+
- type: recall_at_100
|
1153 |
+
value: 12.728
|
1154 |
+
- type: recall_at_1000
|
1155 |
+
value: 41.869
|
1156 |
+
- type: recall_at_3
|
1157 |
+
value: 0.637
|
1158 |
+
- type: recall_at_5
|
1159 |
+
value: 1.042
|
1160 |
language: pl
|
1161 |
license: apache-2.0
|
1162 |
widget:
|