denis-gordeev commited on
Commit
cdc4428
1 Parent(s): 0248880

End of training

Browse files
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,345 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ base_model: microsoft/mdeberta-v3-base
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: multilabel_ner
8
+ results: []
9
+ ---
10
+
11
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
+ should probably proofread and complete it, then remove this comment. -->
13
+
14
+ # multilabel_ner
15
+
16
+ This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
17
+ It achieves the following results on the evaluation set:
18
+ - Loss: 0.0096
19
+ - F1 Micro: 0.5837
20
+ - O F1 Micro: 0.6370
21
+ - O Recall Micro: 0.9242
22
+ - O Precision Micro: 0.4860
23
+ - B-person F1 Micro: 0.9639
24
+ - B-person Recall Micro: 0.9816
25
+ - B-person Precision Micro: 0.9468
26
+ - B-norp F1 Micro: 0.6190
27
+ - B-norp Recall Micro: 0.8667
28
+ - B-norp Precision Micro: 0.4815
29
+ - B-commodity F1 Micro: 0.7553
30
+ - B-commodity Recall Micro: 0.9470
31
+ - B-commodity Precision Micro: 0.6281
32
+ - B-date F1 Micro: 0.8386
33
+ - B-date Recall Micro: 0.8471
34
+ - B-date Precision Micro: 0.8304
35
+ - I-date F1 Micro: 0.6419
36
+ - I-date Recall Micro: 0.9492
37
+ - I-date Precision Micro: 0.4849
38
+ - B-country F1 Micro: 0.6152
39
+ - B-country Recall Micro: 0.9765
40
+ - B-country Precision Micro: 0.4490
41
+ - B-economic Sector F1 Micro: 0.5576
42
+ - B-economic Sector Recall Micro: 0.5897
43
+ - B-economic Sector Precision Micro: 0.5287
44
+ - I-economic Sector F1 Micro: 0.2517
45
+ - I-economic Sector Recall Micro: 0.6667
46
+ - I-economic Sector Precision Micro: 0.1551
47
+ - B-news Source F1 Micro: 0.7988
48
+ - B-news Source Recall Micro: 0.8327
49
+ - B-news Source Precision Micro: 0.7677
50
+ - B-profession F1 Micro: 0.8088
51
+ - B-profession Recall Micro: 0.9464
52
+ - B-profession Precision Micro: 0.7061
53
+ - I-news Source F1 Micro: 0.4808
54
+ - I-news Source Recall Micro: 0.8400
55
+ - I-news Source Precision Micro: 0.3368
56
+ - I-person F1 Micro: 0.3381
57
+ - I-person Recall Micro: 0.996
58
+ - I-person Precision Micro: 0.2036
59
+ - B-organization F1 Micro: 0.8350
60
+ - B-organization Recall Micro: 0.8993
61
+ - B-organization Precision Micro: 0.7794
62
+ - I-profession F1 Micro: 0.2462
63
+ - I-profession Recall Micro: 0.8030
64
+ - I-profession Precision Micro: 0.1454
65
+ - B-event F1 Micro: 0.5658
66
+ - B-event Recall Micro: 0.5436
67
+ - B-event Precision Micro: 0.5899
68
+ - B-city F1 Micro: 0.625
69
+ - B-city Recall Micro: 0.8904
70
+ - B-city Precision Micro: 0.4815
71
+ - B-gpe F1 Micro: 0.6760
72
+ - B-gpe Recall Micro: 0.9380
73
+ - B-gpe Precision Micro: 0.5284
74
+ - I-event F1 Micro: 0.2577
75
+ - I-event Recall Micro: 0.3776
76
+ - I-event Precision Micro: 0.1956
77
+ - B-group F1 Micro: 0.6667
78
+ - B-group Recall Micro: 0.75
79
+ - B-group Precision Micro: 0.6
80
+ - B-ordinal F1 Micro: 0.5306
81
+ - B-ordinal Recall Micro: 0.8125
82
+ - B-ordinal Precision Micro: 0.3939
83
+ - B-product F1 Micro: 0.6683
84
+ - B-product Recall Micro: 0.8232
85
+ - B-product Precision Micro: 0.5625
86
+ - I-organization F1 Micro: 0.3128
87
+ - I-organization Recall Micro: 0.8425
88
+ - I-organization Precision Micro: 0.1921
89
+ - B-money F1 Micro: 0.8530
90
+ - B-money Recall Micro: 0.8947
91
+ - B-money Precision Micro: 0.8151
92
+ - I-money F1 Micro: 0.6259
93
+ - I-money Recall Micro: 0.9644
94
+ - I-money Precision Micro: 0.4632
95
+ - B-currency F1 Micro: 0.7441
96
+ - B-currency Recall Micro: 0.9658
97
+ - B-currency Precision Micro: 0.6052
98
+ - B-percent F1 Micro: 0.8639
99
+ - B-percent Recall Micro: 0.8902
100
+ - B-percent Precision Micro: 0.8391
101
+ - I-percent F1 Micro: 0.6995
102
+ - I-percent Recall Micro: 0.9846
103
+ - I-percent Precision Micro: 0.5424
104
+ - I-group F1 Micro: 0.1844
105
+ - I-group Recall Micro: 0.4836
106
+ - I-group Precision Micro: 0.1139
107
+ - B-cardinal F1 Micro: 0.6903
108
+ - B-cardinal Recall Micro: 0.7358
109
+ - B-cardinal Precision Micro: 0.65
110
+ - B-law F1 Micro: 0.3704
111
+ - B-law Recall Micro: 0.3571
112
+ - B-law Precision Micro: 0.3846
113
+ - I-law F1 Micro: 0.3246
114
+ - I-law Recall Micro: 0.3936
115
+ - I-law Precision Micro: 0.2761
116
+ - B-fac F1 Micro: 0.6910
117
+ - B-fac Recall Micro: 0.6910
118
+ - B-fac Precision Micro: 0.6910
119
+ - I-fac F1 Micro: 0.3007
120
+ - I-fac Recall Micro: 0.7151
121
+ - I-fac Precision Micro: 0.1904
122
+ - B-age F1 Micro: 0.8649
123
+ - B-age Recall Micro: 0.7619
124
+ - B-age Precision Micro: 1.0
125
+ - I-city F1 Micro: 0.1047
126
+ - I-city Recall Micro: 0.6429
127
+ - I-city Precision Micro: 0.0570
128
+ - B-work Of Art F1 Micro: 0.3158
129
+ - B-work Of Art Recall Micro: 0.375
130
+ - B-work Of Art Precision Micro: 0.2727
131
+ - I-work Of Art F1 Micro: 0.3721
132
+ - I-work Of Art Recall Micro: 0.5
133
+ - I-work Of Art Precision Micro: 0.2963
134
+ - B-region F1 Micro: 0.8070
135
+ - B-region Recall Micro: 0.7731
136
+ - B-region Precision Micro: 0.8440
137
+ - I-region F1 Micro: 0.2817
138
+ - I-region Recall Micro: 0.8197
139
+ - I-region Precision Micro: 0.1701
140
+ - I-cardinal F1 Micro: 0.3851
141
+ - I-cardinal Recall Micro: 0.4831
142
+ - I-cardinal Precision Micro: 0.3202
143
+ - I-currency F1 Micro: 0.0
144
+ - I-currency Recall Micro: 0.0
145
+ - I-currency Precision Micro: 0.0
146
+ - B-quantity F1 Micro: 0.7311
147
+ - B-quantity Recall Micro: 0.7311
148
+ - B-quantity Precision Micro: 0.7311
149
+ - I-quantity F1 Micro: 0.4889
150
+ - I-quantity Recall Micro: 0.7989
151
+ - I-quantity Precision Micro: 0.3522
152
+ - B-crime F1 Micro: 0.3736
153
+ - B-crime Recall Micro: 0.4048
154
+ - B-crime Precision Micro: 0.3469
155
+ - I-crime F1 Micro: 0.3245
156
+ - I-crime Recall Micro: 0.5648
157
+ - I-crime Precision Micro: 0.2276
158
+ - B-trade Agreement F1 Micro: 0.7170
159
+ - B-trade Agreement Recall Micro: 0.7037
160
+ - B-trade Agreement Precision Micro: 0.7308
161
+ - B-nationality F1 Micro: 0.0
162
+ - B-nationality Recall Micro: 0.0
163
+ - B-nationality Precision Micro: 0.0
164
+ - B-family F1 Micro: 0.5
165
+ - B-family Recall Micro: 0.8889
166
+ - B-family Precision Micro: 0.3478
167
+ - I-family F1 Micro: 0.0
168
+ - I-family Recall Micro: 0.0
169
+ - I-family Precision Micro: 0.0
170
+ - I-product F1 Micro: 0.2021
171
+ - I-product Recall Micro: 0.6824
172
+ - I-product Precision Micro: 0.1186
173
+ - B-time F1 Micro: 0.6538
174
+ - B-time Recall Micro: 0.6296
175
+ - B-time Precision Micro: 0.68
176
+ - I-time F1 Micro: 0.6118
177
+ - I-time Recall Micro: 0.9811
178
+ - I-time Precision Micro: 0.4444
179
+ - I-commodity F1 Micro: 0.0444
180
+ - I-commodity Recall Micro: 0.1667
181
+ - I-commodity Precision Micro: 0.0256
182
+ - B-application F1 Micro: 0.0
183
+ - B-application Recall Micro: 0.0
184
+ - B-application Precision Micro: 0.0
185
+ - I-application F1 Micro: 0.0
186
+ - I-application Recall Micro: 0.0
187
+ - I-application Precision Micro: 0.0
188
+ - I-country F1 Micro: 0.1695
189
+ - I-country Recall Micro: 0.7895
190
+ - I-country Precision Micro: 0.0949
191
+ - B-award F1 Micro: 0.5455
192
+ - B-award Recall Micro: 0.4615
193
+ - B-award Precision Micro: 0.6667
194
+ - I-award F1 Micro: 0.4459
195
+ - I-award Recall Micro: 0.8049
196
+ - I-award Precision Micro: 0.3084
197
+ - I-gpe F1 Micro: 0.3284
198
+ - I-gpe Recall Micro: 0.9167
199
+ - I-gpe Precision Micro: 0.2
200
+ - B-location F1 Micro: 0.4885
201
+ - B-location Recall Micro: 0.5161
202
+ - B-location Precision Micro: 0.4638
203
+ - I-location F1 Micro: 0.3189
204
+ - I-location Recall Micro: 0.6316
205
+ - I-location Precision Micro: 0.2133
206
+ - I-ordinal F1 Micro: 0.5
207
+ - I-ordinal Recall Micro: 0.4
208
+ - I-ordinal Precision Micro: 0.6667
209
+ - I-trade Agreement F1 Micro: 0.1163
210
+ - I-trade Agreement Recall Micro: 0.3846
211
+ - I-trade Agreement Precision Micro: 0.0685
212
+ - B-religion F1 Micro: 0.0
213
+ - B-religion Recall Micro: 0.0
214
+ - B-religion Precision Micro: 0.0
215
+ - I-age F1 Micro: 0.4324
216
+ - I-age Recall Micro: 0.5714
217
+ - I-age Precision Micro: 0.3478
218
+ - B-investment Program F1 Micro: 0.0
219
+ - B-investment Program Recall Micro: 0.0
220
+ - B-investment Program Precision Micro: 0.0
221
+ - I-investment Program F1 Micro: 0.0
222
+ - I-investment Program Recall Micro: 0.0
223
+ - I-investment Program Precision Micro: 0.0
224
+ - B-borough F1 Micro: 0.7059
225
+ - B-borough Recall Micro: 0.6667
226
+ - B-borough Precision Micro: 0.75
227
+ - B-price F1 Micro: 0.0
228
+ - B-price Recall Micro: 0.0
229
+ - B-price Precision Micro: 0.0
230
+ - I-price F1 Micro: 0.0
231
+ - I-price Recall Micro: 0.0
232
+ - I-price Precision Micro: 0.0
233
+ - B-character F1 Micro: 0.0
234
+ - B-character Recall Micro: 0.0
235
+ - B-character Precision Micro: 0.0
236
+ - I-character F1 Micro: 0.0
237
+ - I-character Recall Micro: 0.0
238
+ - I-character Precision Micro: 0.0
239
+ - B-website F1 Micro: 0.0
240
+ - B-website Recall Micro: 0.0
241
+ - B-website Precision Micro: 0.0
242
+ - B-street F1 Micro: 0.4000
243
+ - B-street Recall Micro: 0.4286
244
+ - B-street Precision Micro: 0.375
245
+ - I-street F1 Micro: 0.3256
246
+ - I-street Recall Micro: 1.0
247
+ - I-street Precision Micro: 0.1944
248
+ - B-village F1 Micro: 0.6667
249
+ - B-village Recall Micro: 0.7
250
+ - B-village Precision Micro: 0.6364
251
+ - I-village F1 Micro: 0.2222
252
+ - I-village Recall Micro: 0.875
253
+ - I-village Precision Micro: 0.1273
254
+ - B-disease F1 Micro: 0.5965
255
+ - B-disease Recall Micro: 0.7083
256
+ - B-disease Precision Micro: 0.5152
257
+ - I-disease F1 Micro: 0.3704
258
+ - I-disease Recall Micro: 0.7812
259
+ - I-disease Precision Micro: 0.2427
260
+ - B-penalty F1 Micro: 0.1579
261
+ - B-penalty Recall Micro: 0.1579
262
+ - B-penalty Precision Micro: 0.1579
263
+ - I-penalty F1 Micro: 0.1674
264
+ - I-penalty Recall Micro: 0.3175
265
+ - I-penalty Precision Micro: 0.1136
266
+ - B-weapon F1 Micro: 0.6715
267
+ - B-weapon Recall Micro: 0.7302
268
+ - B-weapon Precision Micro: 0.6216
269
+ - I-weapon F1 Micro: 0.2455
270
+ - I-weapon Recall Micro: 0.5965
271
+ - I-weapon Precision Micro: 0.1545
272
+ - I-borough F1 Micro: 0.4091
273
+ - I-borough Recall Micro: 0.6923
274
+ - I-borough Precision Micro: 0.2903
275
+ - B-vehicle F1 Micro: 0.6349
276
+ - B-vehicle Recall Micro: 0.5882
277
+ - B-vehicle Precision Micro: 0.6897
278
+ - I-vehicle F1 Micro: 0.4174
279
+ - I-vehicle Recall Micro: 0.7273
280
+ - I-vehicle Precision Micro: 0.2927
281
+ - B-language F1 Micro: 0.0
282
+ - B-language Recall Micro: 0.0
283
+ - B-language Precision Micro: 0.0
284
+ - I-language F1 Micro: 0.0
285
+ - I-language Recall Micro: 0.0
286
+ - I-language Precision Micro: 0.0
287
+ - B-house F1 Micro: 0.0
288
+ - B-house Recall Micro: 0.0
289
+ - B-house Precision Micro: 0.0
290
+ - I-norp F1 Micro: 0.0
291
+ - I-norp Recall Micro: 0.0
292
+ - I-norp Precision Micro: 0.0
293
+ - I-house F1 Micro: 0.0
294
+ - I-house Recall Micro: 0.0
295
+ - I-house Precision Micro: 0.0
296
+ - I-website F1 Micro: 0.0
297
+ - I-website Recall Micro: 0.0
298
+ - I-website Precision Micro: 0.0
299
+ - F1 Macro: 0.3969
300
+ - Recall Macro: 0.5603
301
+ - Precision Macro: 0.3447
302
+
303
+ ## Model description
304
+
305
+ More information needed
306
+
307
+ ## Intended uses & limitations
308
+
309
+ More information needed
310
+
311
+ ## Training and evaluation data
312
+
313
+ More information needed
314
+
315
+ ## Training procedure
316
+
317
+ ### Training hyperparameters
318
+
319
+ The following hyperparameters were used during training:
320
+ - learning_rate: 1e-05
321
+ - train_batch_size: 4
322
+ - eval_batch_size: 4
323
+ - seed: 42
324
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
325
+ - lr_scheduler_type: linear
326
+ - num_epochs: 10000
327
+ - mixed_precision_training: Native AMP
328
+
329
+ ### Training results
330
+
331
+ | Training Loss | Epoch | Step | Validation Loss | F1 Micro | O F1 Micro | O Recall Micro | O Precision Micro | B-person F1 Micro | B-person Recall Micro | B-person Precision Micro | B-norp F1 Micro | B-norp Recall Micro | B-norp Precision Micro | B-commodity F1 Micro | B-commodity Recall Micro | B-commodity Precision Micro | B-date F1 Micro | B-date Recall Micro | B-date Precision Micro | I-date F1 Micro | I-date Recall Micro | I-date Precision Micro | B-country F1 Micro | B-country Recall Micro | B-country Precision Micro | B-economic Sector F1 Micro | B-economic Sector Recall Micro | B-economic Sector Precision Micro | I-economic Sector F1 Micro | I-economic Sector Recall Micro | I-economic Sector Precision Micro | B-news Source F1 Micro | B-news Source Recall Micro | B-news Source Precision Micro | B-profession F1 Micro | B-profession Recall Micro | B-profession Precision Micro | I-news Source F1 Micro | I-news Source Recall Micro | I-news Source Precision Micro | I-person F1 Micro | I-person Recall Micro | I-person Precision Micro | B-organization F1 Micro | B-organization Recall Micro | B-organization Precision Micro | I-profession F1 Micro | I-profession Recall Micro | I-profession Precision Micro | B-event F1 Micro | B-event Recall Micro | B-event Precision Micro | B-city F1 Micro | B-city Recall Micro | B-city Precision Micro | B-gpe F1 Micro | B-gpe Recall Micro | B-gpe Precision Micro | I-event F1 Micro | I-event Recall Micro | I-event Precision Micro | B-group F1 Micro | B-group Recall Micro | B-group Precision Micro | B-ordinal F1 Micro | B-ordinal Recall Micro | B-ordinal Precision Micro | B-product F1 Micro | B-product Recall Micro | B-product Precision Micro | I-organization F1 Micro | I-organization Recall Micro | I-organization Precision Micro | B-money F1 Micro | B-money Recall Micro | B-money Precision Micro | I-money F1 Micro | I-money Recall Micro | I-money Precision Micro | B-currency F1 Micro | B-currency Recall Micro | B-currency Precision Micro | B-percent F1 Micro | B-percent Recall Micro | B-percent Precision Micro | I-percent F1 Micro | I-percent Recall Micro | I-percent Precision Micro | I-group F1 Micro | I-group Recall Micro | I-group Precision Micro | B-cardinal F1 Micro | B-cardinal Recall Micro | B-cardinal Precision Micro | B-law F1 Micro | B-law Recall Micro | B-law Precision Micro | I-law F1 Micro | I-law Recall Micro | I-law Precision Micro | B-fac F1 Micro | B-fac Recall Micro | B-fac Precision Micro | I-fac F1 Micro | I-fac Recall Micro | I-fac Precision Micro | B-age F1 Micro | B-age Recall Micro | B-age Precision Micro | I-city F1 Micro | I-city Recall Micro | I-city Precision Micro | B-work Of Art F1 Micro | B-work Of Art Recall Micro | B-work Of Art Precision Micro | I-work Of Art F1 Micro | I-work Of Art Recall Micro | I-work Of Art Precision Micro | B-region F1 Micro | B-region Recall Micro | B-region Precision Micro | I-region F1 Micro | I-region Recall Micro | I-region Precision Micro | I-cardinal F1 Micro | I-cardinal Recall Micro | I-cardinal Precision Micro | I-currency F1 Micro | I-currency Recall Micro | I-currency Precision Micro | B-quantity F1 Micro | B-quantity Recall Micro | B-quantity Precision Micro | I-quantity F1 Micro | I-quantity Recall Micro | I-quantity Precision Micro | B-crime F1 Micro | B-crime Recall Micro | B-crime Precision Micro | I-crime F1 Micro | I-crime Recall Micro | I-crime Precision Micro | B-trade Agreement F1 Micro | B-trade Agreement Recall Micro | B-trade Agreement Precision Micro | B-nationality F1 Micro | B-nationality Recall Micro | B-nationality Precision Micro | B-family F1 Micro | B-family Recall Micro | B-family Precision Micro | I-family F1 Micro | I-family Recall Micro | I-family Precision Micro | I-product F1 Micro | I-product Recall Micro | I-product Precision Micro | B-time F1 Micro | B-time Recall Micro | B-time Precision Micro | I-time F1 Micro | I-time Recall Micro | I-time Precision Micro | I-commodity F1 Micro | I-commodity Recall Micro | I-commodity Precision Micro | B-application F1 Micro | B-application Recall Micro | B-application Precision Micro | I-application F1 Micro | I-application Recall Micro | I-application Precision Micro | I-country F1 Micro | I-country Recall Micro | I-country Precision Micro | B-award F1 Micro | B-award Recall Micro | B-award Precision Micro | I-award F1 Micro | I-award Recall Micro | I-award Precision Micro | I-gpe F1 Micro | I-gpe Recall Micro | I-gpe Precision Micro | B-location F1 Micro | B-location Recall Micro | B-location Precision Micro | I-location F1 Micro | I-location Recall Micro | I-location Precision Micro | I-ordinal F1 Micro | I-ordinal Recall Micro | I-ordinal Precision Micro | I-trade Agreement F1 Micro | I-trade Agreement Recall Micro | I-trade Agreement Precision Micro | B-religion F1 Micro | B-religion Recall Micro | B-religion Precision Micro | I-age F1 Micro | I-age Recall Micro | I-age Precision Micro | B-investment Program F1 Micro | B-investment Program Recall Micro | B-investment Program Precision Micro | I-investment Program F1 Micro | I-investment Program Recall Micro | I-investment Program Precision Micro | B-borough F1 Micro | B-borough Recall Micro | B-borough Precision Micro | B-price F1 Micro | B-price Recall Micro | B-price Precision Micro | I-price F1 Micro | I-price Recall Micro | I-price Precision Micro | B-character F1 Micro | B-character Recall Micro | B-character Precision Micro | I-character F1 Micro | I-character Recall Micro | I-character Precision Micro | B-website F1 Micro | B-website Recall Micro | B-website Precision Micro | B-street F1 Micro | B-street Recall Micro | B-street Precision Micro | I-street F1 Micro | I-street Recall Micro | I-street Precision Micro | B-village F1 Micro | B-village Recall Micro | B-village Precision Micro | I-village F1 Micro | I-village Recall Micro | I-village Precision Micro | B-disease F1 Micro | B-disease Recall Micro | B-disease Precision Micro | I-disease F1 Micro | I-disease Recall Micro | I-disease Precision Micro | B-penalty F1 Micro | B-penalty Recall Micro | B-penalty Precision Micro | I-penalty F1 Micro | I-penalty Recall Micro | I-penalty Precision Micro | B-weapon F1 Micro | B-weapon Recall Micro | B-weapon Precision Micro | I-weapon F1 Micro | I-weapon Recall Micro | I-weapon Precision Micro | I-borough F1 Micro | I-borough Recall Micro | I-borough Precision Micro | B-vehicle F1 Micro | B-vehicle Recall Micro | B-vehicle Precision Micro | I-vehicle F1 Micro | I-vehicle Recall Micro | I-vehicle Precision Micro | B-language F1 Micro | B-language Recall Micro | B-language Precision Micro | I-language F1 Micro | I-language Recall Micro | I-language Precision Micro | B-house F1 Micro | B-house Recall Micro | B-house Precision Micro | I-norp F1 Micro | I-norp Recall Micro | I-norp Precision Micro | I-house F1 Micro | I-house Recall Micro | I-house Precision Micro | I-website F1 Micro | I-website Recall Micro | I-website Precision Micro | F1 Macro | Recall Macro | Precision Macro |
332
+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------:|:--------------:|:-----------------:|:-----------------:|:---------------------:|:------------------------:|:---------------:|:-------------------:|:----------------------:|:--------------------:|:------------------------:|:---------------------------:|:---------------:|:-------------------:|:----------------------:|:---------------:|:-------------------:|:----------------------:|:------------------:|:----------------------:|:-------------------------:|:--------------------------:|:------------------------------:|:---------------------------------:|:--------------------------:|:------------------------------:|:---------------------------------:|:----------------------:|:--------------------------:|:-----------------------------:|:---------------------:|:-------------------------:|:----------------------------:|:----------------------:|:--------------------------:|:-----------------------------:|:-----------------:|:---------------------:|:------------------------:|:-----------------------:|:---------------------------:|:------------------------------:|:---------------------:|:-------------------------:|:----------------------------:|:----------------:|:--------------------:|:-----------------------:|:---------------:|:-------------------:|:----------------------:|:--------------:|:------------------:|:---------------------:|:----------------:|:--------------------:|:-----------------------:|:----------------:|:--------------------:|:-----------------------:|:------------------:|:----------------------:|:-------------------------:|:------------------:|:----------------------:|:-------------------------:|:-----------------------:|:---------------------------:|:------------------------------:|:----------------:|:--------------------:|:-----------------------:|:----------------:|:--------------------:|:-----------------------:|:-------------------:|:-----------------------:|:--------------------------:|:------------------:|:----------------------:|:-------------------------:|:------------------:|:----------------------:|:-------------------------:|:----------------:|:--------------------:|:-----------------------:|:-------------------:|:-----------------------:|:--------------------------:|:--------------:|:------------------:|:---------------------:|:--------------:|:------------------:|:---------------------:|:--------------:|:------------------:|:---------------------:|:--------------:|:------------------:|:---------------------:|:--------------:|:------------------:|:---------------------:|:---------------:|:-------------------:|:----------------------:|:----------------------:|:--------------------------:|:-----------------------------:|:----------------------:|:--------------------------:|:-----------------------------:|:-----------------:|:---------------------:|:------------------------:|:-----------------:|:---------------------:|:------------------------:|:-------------------:|:-----------------------:|:--------------------------:|:-------------------:|:-----------------------:|:--------------------------:|:-------------------:|:-----------------------:|:--------------------------:|:-------------------:|:-----------------------:|:--------------------------:|:----------------:|:--------------------:|:-----------------------:|:----------------:|:--------------------:|:-----------------------:|:--------------------------:|:------------------------------:|:---------------------------------:|:----------------------:|:--------------------------:|:-----------------------------:|:-----------------:|:---------------------:|:------------------------:|:-----------------:|:---------------------:|:------------------------:|:------------------:|:----------------------:|:-------------------------:|:---------------:|:-------------------:|:----------------------:|:---------------:|:-------------------:|:----------------------:|:--------------------:|:------------------------:|:---------------------------:|:----------------------:|:--------------------------:|:-----------------------------:|:----------------------:|:--------------------------:|:-----------------------------:|:------------------:|:----------------------:|:-------------------------:|:----------------:|:--------------------:|:-----------------------:|:----------------:|:--------------------:|:-----------------------:|:--------------:|:------------------:|:---------------------:|:-------------------:|:-----------------------:|:--------------------------:|:-------------------:|:-----------------------:|:--------------------------:|:------------------:|:----------------------:|:-------------------------:|:--------------------------:|:------------------------------:|:---------------------------------:|:-------------------:|:-----------------------:|:--------------------------:|:--------------:|:------------------:|:---------------------:|:-----------------------------:|:---------------------------------:|:------------------------------------:|:-----------------------------:|:---------------------------------:|:------------------------------------:|:------------------:|:----------------------:|:-------------------------:|:----------------:|:--------------------:|:-----------------------:|:----------------:|:--------------------:|:-----------------------:|:--------------------:|:------------------------:|:---------------------------:|:--------------------:|:------------------------:|:---------------------------:|:------------------:|:----------------------:|:-------------------------:|:-----------------:|:---------------------:|:------------------------:|:-----------------:|:---------------------:|:------------------------:|:------------------:|:----------------------:|:-------------------------:|:------------------:|:----------------------:|:-------------------------:|:------------------:|:----------------------:|:-------------------------:|:------------------:|:----------------------:|:-------------------------:|:------------------:|:----------------------:|:-------------------------:|:------------------:|:----------------------:|:-------------------------:|:-----------------:|:---------------------:|:------------------------:|:-----------------:|:---------------------:|:------------------------:|:------------------:|:----------------------:|:-------------------------:|:------------------:|:----------------------:|:-------------------------:|:------------------:|:----------------------:|:-------------------------:|:-------------------:|:-----------------------:|:--------------------------:|:-------------------:|:-----------------------:|:--------------------------:|:----------------:|:--------------------:|:-----------------------:|:---------------:|:-------------------:|:----------------------:|:----------------:|:--------------------:|:-----------------------:|:------------------:|:----------------------:|:-------------------------:|:--------:|:------------:|:---------------:|
333
+ | 0.0033 | 1.0 | 3014 | 0.0092 | 0.5876 | 0.6385 | 0.9365 | 0.4844 | 0.9705 | 0.9816 | 0.9596 | 0.6118 | 0.8667 | 0.4727 | 0.7873 | 0.9394 | 0.6776 | 0.8436 | 0.8571 | 0.8304 | 0.6416 | 0.9669 | 0.4801 | 0.6229 | 0.9831 | 0.4559 | 0.6024 | 0.6410 | 0.5682 | 0.2491 | 0.5965 | 0.1574 | 0.7954 | 0.8306 | 0.7630 | 0.8659 | 0.9184 | 0.8191 | 0.4757 | 0.8461 | 0.3309 | 0.3331 | 0.996 | 0.2 | 0.8277 | 0.9038 | 0.7633 | 0.2675 | 0.7652 | 0.1621 | 0.5617 | 0.5291 | 0.5987 | 0.7347 | 0.8630 | 0.6396 | 0.6989 | 0.9535 | 0.5516 | 0.2461 | 0.3922 | 0.1793 | 0.7073 | 0.7143 | 0.7004 | 0.592 | 0.7708 | 0.4805 | 0.7213 | 0.8049 | 0.6535 | 0.3127 | 0.8040 | 0.1941 | 0.88 | 0.9098 | 0.8521 | 0.6312 | 0.9502 | 0.4726 | 0.7622 | 0.9658 | 0.6295 | 0.8824 | 0.9146 | 0.8523 | 0.6952 | 1.0 | 0.5328 | 0.1762 | 0.4426 | 0.1100 | 0.6688 | 0.6604 | 0.6774 | 0.3846 | 0.3571 | 0.4167 | 0.2473 | 0.3617 | 0.1878 | 0.7348 | 0.7253 | 0.7445 | 0.3085 | 0.6977 | 0.1980 | 0.8333 | 0.7143 | 1.0 | 0.1010 | 0.7143 | 0.0543 | 0.3333 | 0.25 | 0.5 | 0.4242 | 0.4375 | 0.4118 | 0.7729 | 0.8151 | 0.7348 | 0.2865 | 0.8033 | 0.1744 | 0.4196 | 0.5085 | 0.3571 | 0.0 | 0.0 | 0.0 | 0.7177 | 0.7479 | 0.6899 | 0.4931 | 0.7933 | 0.3577 | 0.3789 | 0.4286 | 0.3396 | 0.3341 | 0.6574 | 0.2240 | 0.6415 | 0.6296 | 0.6538 | 0.0 | 0.0 | 0.0 | 0.4737 | 1.0 | 0.3103 | 0.0 | 0.0 | 0.0 | 0.2270 | 0.5647 | 0.1420 | 0.6667 | 0.6667 | 0.6667 | 0.5854 | 0.9057 | 0.4324 | 0.0741 | 0.1667 | 0.0476 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1867 | 0.7368 | 0.1069 | 0.4444 | 0.3077 | 0.8 | 0.4706 | 0.7805 | 0.3368 | 0.2619 | 0.9167 | 0.1528 | 0.4878 | 0.4839 | 0.4918 | 0.2997 | 0.6053 | 0.1991 | 0.25 | 0.2 | 0.3333 | 0.1154 | 0.2308 | 0.0769 | 0.0 | 0.0 | 0.0 | 0.3750 | 0.6429 | 0.2647 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6667 | 0.6667 | 0.6667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5 | 0.5714 | 0.4444 | 0.3333 | 1.0 | 0.2 | 0.6222 | 0.7 | 0.56 | 0.2424 | 1.0 | 0.1379 | 0.5778 | 0.5417 | 0.6190 | 0.3425 | 0.7812 | 0.2193 | 0.1212 | 0.1053 | 0.1429 | 0.1847 | 0.3651 | 0.1237 | 0.7015 | 0.7460 | 0.6620 | 0.2256 | 0.5263 | 0.1435 | 0.4045 | 0.6923 | 0.2857 | 0.7143 | 0.7353 | 0.6944 | 0.3826 | 0.6667 | 0.2683 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3969 | 0.5513 | 0.3515 |
334
+ | 0.0032 | 2.0 | 6028 | 0.0096 | 0.5837 | 0.6370 | 0.9242 | 0.4860 | 0.9639 | 0.9816 | 0.9468 | 0.6190 | 0.8667 | 0.4815 | 0.7553 | 0.9470 | 0.6281 | 0.8386 | 0.8471 | 0.8304 | 0.6419 | 0.9492 | 0.4849 | 0.6152 | 0.9765 | 0.4490 | 0.5576 | 0.5897 | 0.5287 | 0.2517 | 0.6667 | 0.1551 | 0.7988 | 0.8327 | 0.7677 | 0.8088 | 0.9464 | 0.7061 | 0.4808 | 0.8400 | 0.3368 | 0.3381 | 0.996 | 0.2036 | 0.8350 | 0.8993 | 0.7794 | 0.2462 | 0.8030 | 0.1454 | 0.5658 | 0.5436 | 0.5899 | 0.625 | 0.8904 | 0.4815 | 0.6760 | 0.9380 | 0.5284 | 0.2577 | 0.3776 | 0.1956 | 0.6667 | 0.75 | 0.6 | 0.5306 | 0.8125 | 0.3939 | 0.6683 | 0.8232 | 0.5625 | 0.3128 | 0.8425 | 0.1921 | 0.8530 | 0.8947 | 0.8151 | 0.6259 | 0.9644 | 0.4632 | 0.7441 | 0.9658 | 0.6052 | 0.8639 | 0.8902 | 0.8391 | 0.6995 | 0.9846 | 0.5424 | 0.1844 | 0.4836 | 0.1139 | 0.6903 | 0.7358 | 0.65 | 0.3704 | 0.3571 | 0.3846 | 0.3246 | 0.3936 | 0.2761 | 0.6910 | 0.6910 | 0.6910 | 0.3007 | 0.7151 | 0.1904 | 0.8649 | 0.7619 | 1.0 | 0.1047 | 0.6429 | 0.0570 | 0.3158 | 0.375 | 0.2727 | 0.3721 | 0.5 | 0.2963 | 0.8070 | 0.7731 | 0.8440 | 0.2817 | 0.8197 | 0.1701 | 0.3851 | 0.4831 | 0.3202 | 0.0 | 0.0 | 0.0 | 0.7311 | 0.7311 | 0.7311 | 0.4889 | 0.7989 | 0.3522 | 0.3736 | 0.4048 | 0.3469 | 0.3245 | 0.5648 | 0.2276 | 0.7170 | 0.7037 | 0.7308 | 0.0 | 0.0 | 0.0 | 0.5 | 0.8889 | 0.3478 | 0.0 | 0.0 | 0.0 | 0.2021 | 0.6824 | 0.1186 | 0.6538 | 0.6296 | 0.68 | 0.6118 | 0.9811 | 0.4444 | 0.0444 | 0.1667 | 0.0256 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1695 | 0.7895 | 0.0949 | 0.5455 | 0.4615 | 0.6667 | 0.4459 | 0.8049 | 0.3084 | 0.3284 | 0.9167 | 0.2 | 0.4885 | 0.5161 | 0.4638 | 0.3189 | 0.6316 | 0.2133 | 0.5 | 0.4 | 0.6667 | 0.1163 | 0.3846 | 0.0685 | 0.0 | 0.0 | 0.0 | 0.4324 | 0.5714 | 0.3478 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7059 | 0.6667 | 0.75 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4000 | 0.4286 | 0.375 | 0.3256 | 1.0 | 0.1944 | 0.6667 | 0.7 | 0.6364 | 0.2222 | 0.875 | 0.1273 | 0.5965 | 0.7083 | 0.5152 | 0.3704 | 0.7812 | 0.2427 | 0.1579 | 0.1579 | 0.1579 | 0.1674 | 0.3175 | 0.1136 | 0.6715 | 0.7302 | 0.6216 | 0.2455 | 0.5965 | 0.1545 | 0.4091 | 0.6923 | 0.2903 | 0.6349 | 0.5882 | 0.6897 | 0.4174 | 0.7273 | 0.2927 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3969 | 0.5603 | 0.3447 |
335
+ | 0.0029 | 3.0 | 9042 | 0.0102 | 0.5857 | 0.6369 | 0.9367 | 0.4824 | 0.9555 | 0.9862 | 0.9266 | 0.5909 | 0.8667 | 0.4483 | 0.7590 | 0.9545 | 0.63 | 0.8374 | 0.8551 | 0.8205 | 0.6347 | 0.9752 | 0.4704 | 0.6097 | 0.9817 | 0.4422 | 0.6286 | 0.7051 | 0.5670 | 0.2581 | 0.6316 | 0.1622 | 0.7871 | 0.8347 | 0.7446 | 0.8664 | 0.9371 | 0.8056 | 0.4789 | 0.8564 | 0.3324 | 0.3383 | 0.996 | 0.2038 | 0.8071 | 0.8929 | 0.7364 | 0.2440 | 0.8106 | 0.1436 | 0.5397 | 0.4738 | 0.6269 | 0.7014 | 0.8767 | 0.5845 | 0.6503 | 0.9225 | 0.5021 | 0.2354 | 0.3306 | 0.1828 | 0.6799 | 0.75 | 0.6217 | 0.592 | 0.7708 | 0.4805 | 0.7163 | 0.7622 | 0.6757 | 0.3133 | 0.8077 | 0.1944 | 0.8278 | 0.8496 | 0.8071 | 0.6187 | 0.9644 | 0.4555 | 0.7749 | 0.9315 | 0.6634 | 0.8606 | 0.8659 | 0.8554 | 0.688 | 0.9923 | 0.5265 | 0.1872 | 0.4918 | 0.1156 | 0.6826 | 0.7170 | 0.6514 | 0.4286 | 0.4286 | 0.4286 | 0.2900 | 0.4149 | 0.2229 | 0.7124 | 0.6910 | 0.7352 | 0.3132 | 0.7093 | 0.2010 | 0.8649 | 0.7619 | 1.0 | 0.0988 | 0.5714 | 0.0541 | 0.1429 | 0.125 | 0.1667 | 0.3889 | 0.4375 | 0.35 | 0.7317 | 0.7563 | 0.7087 | 0.2889 | 0.8525 | 0.1739 | 0.4224 | 0.5763 | 0.3333 | 0.0 | 0.0 | 0.0 | 0.7265 | 0.7143 | 0.7391 | 0.4936 | 0.7598 | 0.3656 | 0.3564 | 0.4286 | 0.3051 | 0.2857 | 0.6944 | 0.1799 | 0.6471 | 0.8148 | 0.5366 | 0.0 | 0.0 | 0.0 | 0.5455 | 1.0 | 0.375 | 0.0 | 0.0 | 0.0 | 0.2392 | 0.5529 | 0.1526 | 0.6415 | 0.6296 | 0.6538 | 0.6 | 0.9057 | 0.4486 | 0.1176 | 0.6667 | 0.0645 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1436 | 0.7368 | 0.0795 | 0.4286 | 0.4615 | 0.4 | 0.4595 | 0.8293 | 0.3178 | 0.3548 | 0.9167 | 0.22 | 0.5197 | 0.5323 | 0.5077 | 0.3300 | 0.6447 | 0.2217 | 0.4444 | 0.4 | 0.5 | 0.0870 | 0.2308 | 0.0536 | 0.0 | 0.0 | 0.0 | 0.3902 | 0.5714 | 0.2963 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6471 | 0.6111 | 0.6875 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4000 | 0.4286 | 0.375 | 0.3256 | 1.0 | 0.1944 | 0.6829 | 0.7 | 0.6667 | 0.2258 | 0.875 | 0.1296 | 0.4928 | 0.7083 | 0.3778 | 0.3521 | 0.7812 | 0.2273 | 0.15 | 0.1579 | 0.1429 | 0.2128 | 0.3175 | 0.16 | 0.7059 | 0.7619 | 0.6575 | 0.2581 | 0.7018 | 0.1581 | 0.3956 | 0.6923 | 0.2769 | 0.7143 | 0.7353 | 0.6944 | 0.4915 | 0.8788 | 0.3412 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3958 | 0.5647 | 0.3398 |
336
+ | 0.0026 | 4.0 | 12056 | 0.0105 | 0.5820 | 0.6363 | 0.9236 | 0.4854 | 0.9661 | 0.9839 | 0.9490 | 0.6118 | 0.8667 | 0.4727 | 0.7568 | 0.9545 | 0.6269 | 0.8481 | 0.8370 | 0.8595 | 0.6525 | 0.9587 | 0.4945 | 0.6156 | 0.9844 | 0.4478 | 0.6125 | 0.6282 | 0.5976 | 0.2618 | 0.6316 | 0.1651 | 0.8011 | 0.8448 | 0.7618 | 0.8447 | 0.9254 | 0.7769 | 0.4769 | 0.8303 | 0.3346 | 0.3379 | 0.996 | 0.2034 | 0.8171 | 0.8938 | 0.7525 | 0.2480 | 0.8182 | 0.1461 | 0.5205 | 0.5174 | 0.5235 | 0.6432 | 0.8767 | 0.5079 | 0.6821 | 0.9147 | 0.5438 | 0.2270 | 0.4441 | 0.1525 | 0.6405 | 0.7460 | 0.5612 | 0.6016 | 0.7708 | 0.4933 | 0.7299 | 0.7744 | 0.6902 | 0.3177 | 0.8059 | 0.1978 | 0.8699 | 0.8797 | 0.8603 | 0.6308 | 0.9395 | 0.4748 | 0.7637 | 0.9521 | 0.6376 | 0.8571 | 0.8780 | 0.8372 | 0.688 | 0.9923 | 0.5265 | 0.1887 | 0.4918 | 0.1167 | 0.6879 | 0.7484 | 0.6364 | 0.3333 | 0.3571 | 0.3125 | 0.2439 | 0.3723 | 0.1813 | 0.6925 | 0.6910 | 0.6940 | 0.3186 | 0.7326 | 0.2036 | 0.8333 | 0.7143 | 1.0 | 0.1046 | 0.5714 | 0.0576 | 0.2857 | 0.25 | 0.3333 | 0.3333 | 0.4375 | 0.2692 | 0.7583 | 0.7647 | 0.7521 | 0.2985 | 0.8197 | 0.1825 | 0.3416 | 0.4661 | 0.2696 | 0.0 | 0.0 | 0.0 | 0.7113 | 0.7143 | 0.7083 | 0.4965 | 0.7877 | 0.3625 | 0.3800 | 0.4524 | 0.3276 | 0.3125 | 0.6944 | 0.2016 | 0.6545 | 0.6667 | 0.6429 | 0.0 | 0.0 | 0.0 | 0.5143 | 1.0 | 0.3462 | 0.0 | 0.0 | 0.0 | 0.2338 | 0.5294 | 0.15 | 0.6429 | 0.6667 | 0.6207 | 0.5561 | 0.9811 | 0.3881 | 0.1481 | 0.6667 | 0.0833 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1172 | 0.7368 | 0.0636 | 0.4762 | 0.3846 | 0.625 | 0.4648 | 0.8049 | 0.3267 | 0.2299 | 0.8333 | 0.1333 | 0.4429 | 0.5 | 0.3974 | 0.3009 | 0.6711 | 0.1939 | 0.4444 | 0.4 | 0.5 | 0.0714 | 0.1538 | 0.0465 | 0.0 | 0.0 | 0.0 | 0.4118 | 0.5 | 0.35 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7568 | 0.7778 | 0.7368 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3077 | 0.2857 | 0.3333 | 0.3333 | 1.0 | 0.2 | 0.6667 | 0.75 | 0.6 | 0.2222 | 0.875 | 0.1273 | 0.5246 | 0.6667 | 0.4324 | 0.3145 | 0.7812 | 0.1969 | 0.1818 | 0.2105 | 0.16 | 0.1910 | 0.3016 | 0.1397 | 0.6341 | 0.8254 | 0.5149 | 0.2434 | 0.6491 | 0.1498 | 0.3925 | 0.8077 | 0.2593 | 0.7042 | 0.7353 | 0.6757 | 0.4265 | 0.8788 | 0.2816 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3908 | 0.5625 | 0.3356 |
337
+ | 0.0024 | 5.0 | 15070 | 0.0106 | 0.5861 | 0.6371 | 0.9416 | 0.4815 | 0.9805 | 0.9839 | 0.9772 | 0.5909 | 0.8667 | 0.4483 | 0.8039 | 0.9470 | 0.6983 | 0.7907 | 0.7827 | 0.7988 | 0.6354 | 0.9126 | 0.4874 | 0.6076 | 0.9791 | 0.4405 | 0.5590 | 0.5769 | 0.5422 | 0.2528 | 0.5965 | 0.1604 | 0.7992 | 0.8508 | 0.7536 | 0.8109 | 0.9347 | 0.7161 | 0.4823 | 0.8485 | 0.3369 | 0.3381 | 0.996 | 0.2036 | 0.8518 | 0.9103 | 0.8003 | 0.2566 | 0.8106 | 0.1524 | 0.5482 | 0.5203 | 0.5793 | 0.6995 | 0.8767 | 0.5818 | 0.6629 | 0.8992 | 0.5249 | 0.2411 | 0.3355 | 0.1882 | 0.6858 | 0.7103 | 0.6630 | 0.5455 | 0.8125 | 0.4105 | 0.6468 | 0.7927 | 0.5462 | 0.3140 | 0.8498 | 0.1926 | 0.8722 | 0.8722 | 0.8722 | 0.6272 | 0.9431 | 0.4699 | 0.7363 | 0.9658 | 0.5949 | 0.8690 | 0.8902 | 0.8488 | 0.6904 | 0.9692 | 0.5362 | 0.1986 | 0.4590 | 0.1267 | 0.7049 | 0.7736 | 0.6474 | 0.3125 | 0.3571 | 0.2778 | 0.2397 | 0.4043 | 0.1704 | 0.6680 | 0.6953 | 0.6429 | 0.3102 | 0.7267 | 0.1972 | 0.8649 | 0.7619 | 1.0 | 0.0859 | 0.5 | 0.0470 | 0.2667 | 0.25 | 0.2857 | 0.3333 | 0.4375 | 0.2692 | 0.7819 | 0.7983 | 0.7661 | 0.2779 | 0.8361 | 0.1667 | 0.4099 | 0.5593 | 0.3235 | 0.0 | 0.0 | 0.0 | 0.7378 | 0.6975 | 0.7830 | 0.4953 | 0.7318 | 0.3743 | 0.3191 | 0.3571 | 0.2885 | 0.3052 | 0.5185 | 0.2162 | 0.6667 | 0.8519 | 0.5476 | 0.0 | 0.0 | 0.0 | 0.5625 | 1.0 | 0.3913 | 0.0 | 0.0 | 0.0 | 0.25 | 0.5765 | 0.1596 | 0.5926 | 0.5926 | 0.5926 | 0.56 | 0.9245 | 0.4016 | 0.1067 | 0.6667 | 0.0580 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1266 | 0.7895 | 0.0688 | 0.3478 | 0.3077 | 0.4 | 0.4828 | 0.6829 | 0.3733 | 0.2933 | 0.9167 | 0.1746 | 0.4885 | 0.5161 | 0.4638 | 0.3055 | 0.5526 | 0.2111 | 0.4615 | 0.6 | 0.375 | 0.1034 | 0.2308 | 0.0667 | 0.0 | 0.0 | 0.0 | 0.4091 | 0.6429 | 0.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7647 | 0.7222 | 0.8125 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4000 | 0.4286 | 0.375 | 0.3333 | 1.0 | 0.2 | 0.6341 | 0.65 | 0.6190 | 0.2034 | 0.75 | 0.1176 | 0.3404 | 0.6667 | 0.2286 | 0.3356 | 0.7812 | 0.2137 | 0.2041 | 0.2632 | 0.1667 | 0.3077 | 0.4444 | 0.2353 | 0.6483 | 0.7460 | 0.5732 | 0.2628 | 0.6316 | 0.1659 | 0.4368 | 0.7308 | 0.3115 | 0.7385 | 0.7059 | 0.7742 | 0.448 | 0.8485 | 0.3043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3916 | 0.5600 | 0.3347 |
338
+
339
+
340
+ ### Framework versions
341
+
342
+ - Transformers 4.35.0
343
+ - Pytorch 2.1.0+cu121
344
+ - Datasets 2.2.2
345
+ - Tokenizers 0.14.1
added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "[MASK]": 250101
3
+ }
config.json ADDED
@@ -0,0 +1,225 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "microsoft/mdeberta-v3-base",
3
+ "architectures": [
4
+ "DebertaV2ForTokenClassification"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "hidden_act": "gelu",
8
+ "hidden_dropout_prob": 0.1,
9
+ "hidden_size": 768,
10
+ "id2label": {
11
+ "0": "O",
12
+ "1": "B-PERSON",
13
+ "2": "B-NORP",
14
+ "3": "B-COMMODITY",
15
+ "4": "B-DATE",
16
+ "5": "I-DATE",
17
+ "6": "B-COUNTRY",
18
+ "7": "B-ECONOMIC_SECTOR",
19
+ "8": "I-ECONOMIC_SECTOR",
20
+ "9": "B-NEWS_SOURCE",
21
+ "10": "B-PROFESSION",
22
+ "11": "I-NEWS_SOURCE",
23
+ "12": "I-PERSON",
24
+ "13": "B-ORGANIZATION",
25
+ "14": "I-PROFESSION",
26
+ "15": "B-EVENT",
27
+ "16": "B-CITY",
28
+ "17": "B-GPE",
29
+ "18": "I-EVENT",
30
+ "19": "B-GROUP",
31
+ "20": "B-ORDINAL",
32
+ "21": "B-PRODUCT",
33
+ "22": "I-ORGANIZATION",
34
+ "23": "B-MONEY",
35
+ "24": "I-MONEY",
36
+ "25": "B-CURRENCY",
37
+ "26": "B-PERCENT",
38
+ "27": "I-PERCENT",
39
+ "28": "I-GROUP",
40
+ "29": "B-CARDINAL",
41
+ "30": "B-LAW",
42
+ "31": "I-LAW",
43
+ "32": "B-FAC",
44
+ "33": "I-FAC",
45
+ "34": "B-AGE",
46
+ "35": "I-CITY",
47
+ "36": "B-WORK_OF_ART",
48
+ "37": "I-WORK_OF_ART",
49
+ "38": "B-REGION",
50
+ "39": "I-REGION",
51
+ "40": "I-CARDINAL",
52
+ "41": "I-CURRENCY",
53
+ "42": "B-QUANTITY",
54
+ "43": "I-QUANTITY",
55
+ "44": "B-CRIME",
56
+ "45": "I-CRIME",
57
+ "46": "B-TRADE_AGREEMENT",
58
+ "47": "B-NATIONALITY",
59
+ "48": "B-FAMILY",
60
+ "49": "I-FAMILY",
61
+ "50": "I-PRODUCT",
62
+ "51": "B-TIME",
63
+ "52": "I-TIME",
64
+ "53": "I-COMMODITY",
65
+ "54": "B-APPLICATION",
66
+ "55": "I-APPLICATION",
67
+ "56": "I-COUNTRY",
68
+ "57": "B-AWARD",
69
+ "58": "I-AWARD",
70
+ "59": "I-GPE",
71
+ "60": "B-LOCATION",
72
+ "61": "I-LOCATION",
73
+ "62": "I-ORDINAL",
74
+ "63": "I-TRADE_AGREEMENT",
75
+ "64": "B-RELIGION",
76
+ "65": "I-AGE",
77
+ "66": "B-INVESTMENT_PROGRAM",
78
+ "67": "I-INVESTMENT_PROGRAM",
79
+ "68": "B-BOROUGH",
80
+ "69": "B-PRICE",
81
+ "70": "I-PRICE",
82
+ "71": "B-CHARACTER",
83
+ "72": "I-CHARACTER",
84
+ "73": "B-WEBSITE",
85
+ "74": "B-STREET",
86
+ "75": "I-STREET",
87
+ "76": "B-VILLAGE",
88
+ "77": "I-VILLAGE",
89
+ "78": "B-DISEASE",
90
+ "79": "I-DISEASE",
91
+ "80": "B-PENALTY",
92
+ "81": "I-PENALTY",
93
+ "82": "B-WEAPON",
94
+ "83": "I-WEAPON",
95
+ "84": "I-BOROUGH",
96
+ "85": "B-VEHICLE",
97
+ "86": "I-VEHICLE",
98
+ "87": "B-LANGUAGE",
99
+ "88": "I-LANGUAGE",
100
+ "89": "B-HOUSE",
101
+ "90": "I-NORP",
102
+ "91": "I-HOUSE",
103
+ "92": "I-WEBSITE"
104
+ },
105
+ "initializer_range": 0.02,
106
+ "intermediate_size": 3072,
107
+ "label2id": {
108
+ "B-AGE": 34,
109
+ "B-APPLICATION": 54,
110
+ "B-AWARD": 57,
111
+ "B-BOROUGH": 68,
112
+ "B-CARDINAL": 29,
113
+ "B-CHARACTER": 71,
114
+ "B-CITY": 16,
115
+ "B-COMMODITY": 3,
116
+ "B-COUNTRY": 6,
117
+ "B-CRIME": 44,
118
+ "B-CURRENCY": 25,
119
+ "B-DATE": 4,
120
+ "B-DISEASE": 78,
121
+ "B-ECONOMIC_SECTOR": 7,
122
+ "B-EVENT": 15,
123
+ "B-FAC": 32,
124
+ "B-FAMILY": 48,
125
+ "B-GPE": 17,
126
+ "B-GROUP": 19,
127
+ "B-HOUSE": 89,
128
+ "B-INVESTMENT_PROGRAM": 66,
129
+ "B-LANGUAGE": 87,
130
+ "B-LAW": 30,
131
+ "B-LOCATION": 60,
132
+ "B-MONEY": 23,
133
+ "B-NATIONALITY": 47,
134
+ "B-NEWS_SOURCE": 9,
135
+ "B-NORP": 2,
136
+ "B-ORDINAL": 20,
137
+ "B-ORGANIZATION": 13,
138
+ "B-PENALTY": 80,
139
+ "B-PERCENT": 26,
140
+ "B-PERSON": 1,
141
+ "B-PRICE": 69,
142
+ "B-PRODUCT": 21,
143
+ "B-PROFESSION": 10,
144
+ "B-QUANTITY": 42,
145
+ "B-REGION": 38,
146
+ "B-RELIGION": 64,
147
+ "B-STREET": 74,
148
+ "B-TIME": 51,
149
+ "B-TRADE_AGREEMENT": 46,
150
+ "B-VEHICLE": 85,
151
+ "B-VILLAGE": 76,
152
+ "B-WEAPON": 82,
153
+ "B-WEBSITE": 73,
154
+ "B-WORK_OF_ART": 36,
155
+ "I-AGE": 65,
156
+ "I-APPLICATION": 55,
157
+ "I-AWARD": 58,
158
+ "I-BOROUGH": 84,
159
+ "I-CARDINAL": 40,
160
+ "I-CHARACTER": 72,
161
+ "I-CITY": 35,
162
+ "I-COMMODITY": 53,
163
+ "I-COUNTRY": 56,
164
+ "I-CRIME": 45,
165
+ "I-CURRENCY": 41,
166
+ "I-DATE": 5,
167
+ "I-DISEASE": 79,
168
+ "I-ECONOMIC_SECTOR": 8,
169
+ "I-EVENT": 18,
170
+ "I-FAC": 33,
171
+ "I-FAMILY": 49,
172
+ "I-GPE": 59,
173
+ "I-GROUP": 28,
174
+ "I-HOUSE": 91,
175
+ "I-INVESTMENT_PROGRAM": 67,
176
+ "I-LANGUAGE": 88,
177
+ "I-LAW": 31,
178
+ "I-LOCATION": 61,
179
+ "I-MONEY": 24,
180
+ "I-NEWS_SOURCE": 11,
181
+ "I-NORP": 90,
182
+ "I-ORDINAL": 62,
183
+ "I-ORGANIZATION": 22,
184
+ "I-PENALTY": 81,
185
+ "I-PERCENT": 27,
186
+ "I-PERSON": 12,
187
+ "I-PRICE": 70,
188
+ "I-PRODUCT": 50,
189
+ "I-PROFESSION": 14,
190
+ "I-QUANTITY": 43,
191
+ "I-REGION": 39,
192
+ "I-STREET": 75,
193
+ "I-TIME": 52,
194
+ "I-TRADE_AGREEMENT": 63,
195
+ "I-VEHICLE": 86,
196
+ "I-VILLAGE": 77,
197
+ "I-WEAPON": 83,
198
+ "I-WEBSITE": 92,
199
+ "I-WORK_OF_ART": 37,
200
+ "O": 0
201
+ },
202
+ "layer_norm_eps": 1e-07,
203
+ "max_position_embeddings": 512,
204
+ "max_relative_positions": -1,
205
+ "model_type": "deberta-v2",
206
+ "norm_rel_ebd": "layer_norm",
207
+ "num_attention_heads": 12,
208
+ "num_hidden_layers": 12,
209
+ "pad_token_id": 0,
210
+ "pooler_dropout": 0,
211
+ "pooler_hidden_act": "gelu",
212
+ "pooler_hidden_size": 768,
213
+ "pos_att_type": [
214
+ "p2c",
215
+ "c2p"
216
+ ],
217
+ "position_biased_input": false,
218
+ "position_buckets": 256,
219
+ "relative_attention": true,
220
+ "share_att_key": true,
221
+ "torch_dtype": "float32",
222
+ "transformers_version": "4.35.0",
223
+ "type_vocab_size": 0,
224
+ "vocab_size": 251000
225
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5835fbcbbdb58b868f0474e0e742b61c0d2be6d811241a5c2a4e439543c408a6
3
+ size 1113185580
special_tokens_map.json ADDED
@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": "[CLS]",
3
+ "cls_token": "[CLS]",
4
+ "eos_token": "[SEP]",
5
+ "mask_token": "[MASK]",
6
+ "pad_token": "[PAD]",
7
+ "sep_token": "[SEP]",
8
+ "unk_token": {
9
+ "content": "[UNK]",
10
+ "lstrip": false,
11
+ "normalized": true,
12
+ "rstrip": false,
13
+ "single_word": false
14
+ }
15
+ }
spm.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:13c8d666d62a7bc4ac8f040aab68e942c861f93303156cc28f5c7e885d86d6e3
3
+ size 4305025
tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b8526679586383c62039cf0a3fde1398f047c9f2927186be57eb14e2c229279a
3
+ size 16331328
tokenizer_config.json ADDED
@@ -0,0 +1,58 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "[PAD]",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "1": {
12
+ "content": "[CLS]",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "2": {
20
+ "content": "[SEP]",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "3": {
28
+ "content": "[UNK]",
29
+ "lstrip": false,
30
+ "normalized": true,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "250101": {
36
+ "content": "[MASK]",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ }
43
+ },
44
+ "bos_token": "[CLS]",
45
+ "clean_up_tokenization_spaces": true,
46
+ "cls_token": "[CLS]",
47
+ "do_lower_case": false,
48
+ "eos_token": "[SEP]",
49
+ "mask_token": "[MASK]",
50
+ "model_max_length": 1000000000000000019884624838656,
51
+ "pad_token": "[PAD]",
52
+ "sep_token": "[SEP]",
53
+ "sp_model_kwargs": {},
54
+ "split_by_punct": false,
55
+ "tokenizer_class": "DebertaV2Tokenizer",
56
+ "unk_token": "[UNK]",
57
+ "vocab_type": "spm"
58
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d8b5d5b79e7ec03ce40af3680fcdbbc9a21bdb37aa8a3e32d45bf86c9a8f73f5
3
+ size 4536