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pengql
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checkpoint-9000

Feature Extraction
Transformers
PyTorch
mistral
mteb
Eval Results
text-generation-inference
text-embeddings-inference
Inference Endpoints
Model card Files Community
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- license: mit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3
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  ---
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+ tags:
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+ - mteb
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+ model-index:
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+ - name: checkpoint-9000
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+ results:
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+ - task:
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+ type: Retrieval
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+ dataset:
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+ type: C-MTEB/CmedqaRetrieval
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+ name: MTEB CmedqaRetrieval
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+ config: default
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+ split: dev
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+ revision: None
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+ metrics:
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+ - type: map_at_1
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+ value: 23.191
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+ - type: map_at_10
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+ value: 34.272999999999996
20
+ - type: map_at_100
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+ value: 36.101
22
+ - type: map_at_1000
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+ value: 36.231
24
+ - type: map_at_3
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+ value: 30.495
26
+ - type: map_at_5
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+ value: 32.54
28
+ - type: mrr_at_1
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+ value: 35.434
30
+ - type: mrr_at_10
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+ value: 43.15
32
+ - type: mrr_at_100
33
+ value: 44.155
34
+ - type: mrr_at_1000
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+ value: 44.211
36
+ - type: mrr_at_3
37
+ value: 40.735
38
+ - type: mrr_at_5
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+ value: 42.052
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+ - type: ndcg_at_1
41
+ value: 35.434
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+ - type: ndcg_at_10
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+ value: 40.572
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+ - type: ndcg_at_100
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+ value: 47.921
46
+ - type: ndcg_at_1000
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+ value: 50.314
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+ - type: ndcg_at_3
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+ value: 35.671
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+ - type: ndcg_at_5
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+ value: 37.635000000000005
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+ - type: precision_at_1
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+ value: 35.434
54
+ - type: precision_at_10
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+ value: 9.067
56
+ - type: precision_at_100
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+ value: 1.506
58
+ - type: precision_at_1000
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+ value: 0.181
60
+ - type: precision_at_3
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+ value: 20.163
62
+ - type: precision_at_5
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+ value: 14.624
64
+ - type: recall_at_1
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+ value: 23.191
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+ - type: recall_at_10
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+ value: 50.318
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+ - type: recall_at_100
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+ value: 80.958
70
+ - type: recall_at_1000
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+ value: 97.16799999999999
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+ - type: recall_at_3
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+ value: 35.57
74
+ - type: recall_at_5
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+ value: 41.776
76
+ - task:
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+ type: Retrieval
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+ dataset:
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+ type: C-MTEB/CovidRetrieval
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+ name: MTEB CovidRetrieval
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+ config: default
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+ split: dev
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+ revision: None
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+ metrics:
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+ - type: map_at_1
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+ value: 64.015
87
+ - type: map_at_10
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+ value: 71.983
89
+ - type: map_at_100
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+ value: 72.432
91
+ - type: map_at_1000
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+ value: 72.441
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+ - type: map_at_3
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+ value: 69.92399999999999
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+ - type: map_at_5
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+ value: 71.177
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+ - type: mrr_at_1
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+ value: 64.173
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+ - type: mrr_at_10
100
+ value: 71.985
101
+ - type: mrr_at_100
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+ value: 72.425
103
+ - type: mrr_at_1000
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+ value: 72.434
105
+ - type: mrr_at_3
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+ value: 69.968
107
+ - type: mrr_at_5
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+ value: 71.222
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+ - type: ndcg_at_1
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+ value: 64.173
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+ - type: ndcg_at_10
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+ value: 75.929
113
+ - type: ndcg_at_100
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+ value: 77.961
115
+ - type: ndcg_at_1000
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+ value: 78.223
117
+ - type: ndcg_at_3
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+ value: 71.828
119
+ - type: ndcg_at_5
120
+ value: 74.066
121
+ - type: precision_at_1
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+ value: 64.173
123
+ - type: precision_at_10
124
+ value: 8.924999999999999
125
+ - type: precision_at_100
126
+ value: 0.985
127
+ - type: precision_at_1000
128
+ value: 0.101
129
+ - type: precision_at_3
130
+ value: 25.887
131
+ - type: precision_at_5
132
+ value: 16.669999999999998
133
+ - type: recall_at_1
134
+ value: 64.015
135
+ - type: recall_at_10
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+ value: 88.251
137
+ - type: recall_at_100
138
+ value: 97.471
139
+ - type: recall_at_1000
140
+ value: 99.579
141
+ - type: recall_at_3
142
+ value: 77.292
143
+ - type: recall_at_5
144
+ value: 82.666
145
+ - task:
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+ type: Retrieval
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+ dataset:
148
+ type: C-MTEB/DuRetrieval
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+ name: MTEB DuRetrieval
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+ config: default
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+ split: dev
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+ revision: None
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+ metrics:
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+ - type: map_at_1
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+ value: 23.983999999999998
156
+ - type: map_at_10
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+ value: 75.175
158
+ - type: map_at_100
159
+ value: 78.27300000000001
160
+ - type: map_at_1000
161
+ value: 78.322
162
+ - type: map_at_3
163
+ value: 51.214999999999996
164
+ - type: map_at_5
165
+ value: 64.89200000000001
166
+ - type: mrr_at_1
167
+ value: 83.89999999999999
168
+ - type: mrr_at_10
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+ value: 89.563
170
+ - type: mrr_at_100
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+ value: 89.64999999999999
172
+ - type: mrr_at_1000
173
+ value: 89.654
174
+ - type: mrr_at_3
175
+ value: 89.167
176
+ - type: mrr_at_5
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+ value: 89.492
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+ - type: ndcg_at_1
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+ value: 83.89999999999999
180
+ - type: ndcg_at_10
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+ value: 83.72800000000001
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+ - type: ndcg_at_100
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+ value: 87.064
184
+ - type: ndcg_at_1000
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+ value: 87.504
186
+ - type: ndcg_at_3
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+ value: 81.318
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+ - type: ndcg_at_5
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+ value: 80.667
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+ - type: precision_at_1
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+ value: 83.89999999999999
192
+ - type: precision_at_10
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+ value: 40.699999999999996
194
+ - type: precision_at_100
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+ value: 4.7780000000000005
196
+ - type: precision_at_1000
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+ value: 0.488
198
+ - type: precision_at_3
199
+ value: 73.317
200
+ - type: precision_at_5
201
+ value: 62.129999999999995
202
+ - type: recall_at_1
203
+ value: 23.983999999999998
204
+ - type: recall_at_10
205
+ value: 86.412
206
+ - type: recall_at_100
207
+ value: 96.882
208
+ - type: recall_at_1000
209
+ value: 99.22
210
+ - type: recall_at_3
211
+ value: 54.769999999999996
212
+ - type: recall_at_5
213
+ value: 71.663
214
+ - task:
215
+ type: Retrieval
216
+ dataset:
217
+ type: C-MTEB/EcomRetrieval
218
+ name: MTEB EcomRetrieval
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+ config: default
220
+ split: dev
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+ revision: None
222
+ metrics:
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+ - type: map_at_1
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+ value: 51.6
225
+ - type: map_at_10
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+ value: 61.209
227
+ - type: map_at_100
228
+ value: 61.734
229
+ - type: map_at_1000
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+ value: 61.75000000000001
231
+ - type: map_at_3
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+ value: 58.8
233
+ - type: map_at_5
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+ value: 60.165
235
+ - type: mrr_at_1
236
+ value: 51.6
237
+ - type: mrr_at_10
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+ value: 61.209
239
+ - type: mrr_at_100
240
+ value: 61.734
241
+ - type: mrr_at_1000
242
+ value: 61.75000000000001
243
+ - type: mrr_at_3
244
+ value: 58.8
245
+ - type: mrr_at_5
246
+ value: 60.165
247
+ - type: ndcg_at_1
248
+ value: 51.6
249
+ - type: ndcg_at_10
250
+ value: 66.13900000000001
251
+ - type: ndcg_at_100
252
+ value: 68.65400000000001
253
+ - type: ndcg_at_1000
254
+ value: 69.057
255
+ - type: ndcg_at_3
256
+ value: 61.185
257
+ - type: ndcg_at_5
258
+ value: 63.651
259
+ - type: precision_at_1
260
+ value: 51.6
261
+ - type: precision_at_10
262
+ value: 8.17
263
+ - type: precision_at_100
264
+ value: 0.9339999999999999
265
+ - type: precision_at_1000
266
+ value: 0.097
267
+ - type: precision_at_3
268
+ value: 22.7
269
+ - type: precision_at_5
270
+ value: 14.82
271
+ - type: recall_at_1
272
+ value: 51.6
273
+ - type: recall_at_10
274
+ value: 81.69999999999999
275
+ - type: recall_at_100
276
+ value: 93.4
277
+ - type: recall_at_1000
278
+ value: 96.6
279
+ - type: recall_at_3
280
+ value: 68.10000000000001
281
+ - type: recall_at_5
282
+ value: 74.1
283
+ - task:
284
+ type: Retrieval
285
+ dataset:
286
+ type: C-MTEB/MMarcoRetrieval
287
+ name: MTEB MMarcoRetrieval
288
+ config: default
289
+ split: dev
290
+ revision: None
291
+ metrics:
292
+ - type: map_at_1
293
+ value: 69.54599999999999
294
+ - type: map_at_10
295
+ value: 78.477
296
+ - type: map_at_100
297
+ value: 78.743
298
+ - type: map_at_1000
299
+ value: 78.751
300
+ - type: map_at_3
301
+ value: 76.769
302
+ - type: map_at_5
303
+ value: 77.854
304
+ - type: mrr_at_1
305
+ value: 71.819
306
+ - type: mrr_at_10
307
+ value: 79.008
308
+ - type: mrr_at_100
309
+ value: 79.24
310
+ - type: mrr_at_1000
311
+ value: 79.247
312
+ - type: mrr_at_3
313
+ value: 77.55300000000001
314
+ - type: mrr_at_5
315
+ value: 78.477
316
+ - type: ndcg_at_1
317
+ value: 71.819
318
+ - type: ndcg_at_10
319
+ value: 81.947
320
+ - type: ndcg_at_100
321
+ value: 83.112
322
+ - type: ndcg_at_1000
323
+ value: 83.325
324
+ - type: ndcg_at_3
325
+ value: 78.758
326
+ - type: ndcg_at_5
327
+ value: 80.563
328
+ - type: precision_at_1
329
+ value: 71.819
330
+ - type: precision_at_10
331
+ value: 9.792
332
+ - type: precision_at_100
333
+ value: 1.0370000000000001
334
+ - type: precision_at_1000
335
+ value: 0.105
336
+ - type: precision_at_3
337
+ value: 29.479
338
+ - type: precision_at_5
339
+ value: 18.659
340
+ - type: recall_at_1
341
+ value: 69.54599999999999
342
+ - type: recall_at_10
343
+ value: 92.053
344
+ - type: recall_at_100
345
+ value: 97.25399999999999
346
+ - type: recall_at_1000
347
+ value: 98.926
348
+ - type: recall_at_3
349
+ value: 83.682
350
+ - type: recall_at_5
351
+ value: 87.944
352
+ - task:
353
+ type: Retrieval
354
+ dataset:
355
+ type: C-MTEB/MedicalRetrieval
356
+ name: MTEB MedicalRetrieval
357
+ config: default
358
+ split: dev
359
+ revision: None
360
+ metrics:
361
+ - type: map_at_1
362
+ value: 50.3
363
+ - type: map_at_10
364
+ value: 55.824
365
+ - type: map_at_100
366
+ value: 56.379999999999995
367
+ - type: map_at_1000
368
+ value: 56.440999999999995
369
+ - type: map_at_3
370
+ value: 54.400000000000006
371
+ - type: map_at_5
372
+ value: 55.235
373
+ - type: mrr_at_1
374
+ value: 50.4
375
+ - type: mrr_at_10
376
+ value: 55.88999999999999
377
+ - type: mrr_at_100
378
+ value: 56.447
379
+ - type: mrr_at_1000
380
+ value: 56.508
381
+ - type: mrr_at_3
382
+ value: 54.467
383
+ - type: mrr_at_5
384
+ value: 55.30199999999999
385
+ - type: ndcg_at_1
386
+ value: 50.3
387
+ - type: ndcg_at_10
388
+ value: 58.577999999999996
389
+ - type: ndcg_at_100
390
+ value: 61.49099999999999
391
+ - type: ndcg_at_1000
392
+ value: 63.161
393
+ - type: ndcg_at_3
394
+ value: 55.64
395
+ - type: ndcg_at_5
396
+ value: 57.13399999999999
397
+ - type: precision_at_1
398
+ value: 50.3
399
+ - type: precision_at_10
400
+ value: 6.7299999999999995
401
+ - type: precision_at_100
402
+ value: 0.814
403
+ - type: precision_at_1000
404
+ value: 0.095
405
+ - type: precision_at_3
406
+ value: 19.733
407
+ - type: precision_at_5
408
+ value: 12.559999999999999
409
+ - type: recall_at_1
410
+ value: 50.3
411
+ - type: recall_at_10
412
+ value: 67.30000000000001
413
+ - type: recall_at_100
414
+ value: 81.39999999999999
415
+ - type: recall_at_1000
416
+ value: 94.69999999999999
417
+ - type: recall_at_3
418
+ value: 59.199999999999996
419
+ - type: recall_at_5
420
+ value: 62.8
421
+ - task:
422
+ type: Retrieval
423
+ dataset:
424
+ type: C-MTEB/T2Retrieval
425
+ name: MTEB T2Retrieval
426
+ config: default
427
+ split: dev
428
+ revision: None
429
+ metrics:
430
+ - type: map_at_1
431
+ value: 27.293
432
+ - type: map_at_10
433
+ value: 76.618
434
+ - type: map_at_100
435
+ value: 80.22500000000001
436
+ - type: map_at_1000
437
+ value: 80.292
438
+ - type: map_at_3
439
+ value: 53.856
440
+ - type: map_at_5
441
+ value: 66.158
442
+ - type: mrr_at_1
443
+ value: 89.659
444
+ - type: mrr_at_10
445
+ value: 92.121
446
+ - type: mrr_at_100
447
+ value: 92.214
448
+ - type: mrr_at_1000
449
+ value: 92.218
450
+ - type: mrr_at_3
451
+ value: 91.67
452
+ - type: mrr_at_5
453
+ value: 91.955
454
+ - type: ndcg_at_1
455
+ value: 89.659
456
+ - type: ndcg_at_10
457
+ value: 84.172
458
+ - type: ndcg_at_100
459
+ value: 87.767
460
+ - type: ndcg_at_1000
461
+ value: 88.419
462
+ - type: ndcg_at_3
463
+ value: 85.628
464
+ - type: ndcg_at_5
465
+ value: 84.155
466
+ - type: precision_at_1
467
+ value: 89.659
468
+ - type: precision_at_10
469
+ value: 41.914
470
+ - type: precision_at_100
471
+ value: 4.9959999999999996
472
+ - type: precision_at_1000
473
+ value: 0.515
474
+ - type: precision_at_3
475
+ value: 74.955
476
+ - type: precision_at_5
477
+ value: 62.771
478
+ - type: recall_at_1
479
+ value: 27.293
480
+ - type: recall_at_10
481
+ value: 83.004
482
+ - type: recall_at_100
483
+ value: 94.82300000000001
484
+ - type: recall_at_1000
485
+ value: 98.15
486
+ - type: recall_at_3
487
+ value: 55.455
488
+ - type: recall_at_5
489
+ value: 69.422
490
+ - task:
491
+ type: Retrieval
492
+ dataset:
493
+ type: C-MTEB/VideoRetrieval
494
+ name: MTEB VideoRetrieval
495
+ config: default
496
+ split: dev
497
+ revision: None
498
+ metrics:
499
+ - type: map_at_1
500
+ value: 59.599999999999994
501
+ - type: map_at_10
502
+ value: 69.44399999999999
503
+ - type: map_at_100
504
+ value: 69.798
505
+ - type: map_at_1000
506
+ value: 69.81
507
+ - type: map_at_3
508
+ value: 67.467
509
+ - type: map_at_5
510
+ value: 68.692
511
+ - type: mrr_at_1
512
+ value: 59.599999999999994
513
+ - type: mrr_at_10
514
+ value: 69.44399999999999
515
+ - type: mrr_at_100
516
+ value: 69.798
517
+ - type: mrr_at_1000
518
+ value: 69.81
519
+ - type: mrr_at_3
520
+ value: 67.467
521
+ - type: mrr_at_5
522
+ value: 68.692
523
+ - type: ndcg_at_1
524
+ value: 59.599999999999994
525
+ - type: ndcg_at_10
526
+ value: 73.936
527
+ - type: ndcg_at_100
528
+ value: 75.688
529
+ - type: ndcg_at_1000
530
+ value: 75.942
531
+ - type: ndcg_at_3
532
+ value: 69.92399999999999
533
+ - type: ndcg_at_5
534
+ value: 72.14
535
+ - type: precision_at_1
536
+ value: 59.599999999999994
537
+ - type: precision_at_10
538
+ value: 8.790000000000001
539
+ - type: precision_at_100
540
+ value: 0.9610000000000001
541
+ - type: precision_at_1000
542
+ value: 0.098
543
+ - type: precision_at_3
544
+ value: 25.667
545
+ - type: precision_at_5
546
+ value: 16.48
547
+ - type: recall_at_1
548
+ value: 59.599999999999994
549
+ - type: recall_at_10
550
+ value: 87.9
551
+ - type: recall_at_100
552
+ value: 96.1
553
+ - type: recall_at_1000
554
+ value: 98
555
+ - type: recall_at_3
556
+ value: 77
557
+ - type: recall_at_5
558
+ value: 82.39999999999999
559
+
560
  ---
561
+