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zh_core_web_trf

Token Classification spaCy Chinese Eval Results
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osanseviero HF staff commited on
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1 Parent(s): 3bf6c38

Update spaCy pipeline

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Files changed (17) hide show
  1. README.md +23 -20
  2. accuracy.json +195 -192
  3. attribute_ruler/patterns +0 -0
  4. config.cfg +20 -11
  5. meta.json +199 -196
  6. ner/model +0 -0
  7. parser/model +0 -0
  8. tagger/cfg +2 -1
  9. tagger/model +0 -0
  10. transformer/{model/pytorch_model.bin β†’ model} +2 -2
  11. transformer/model/config.json +0 -30
  12. transformer/model/special_tokens_map.json +0 -1
  13. transformer/model/tokenizer.json +0 -0
  14. transformer/model/tokenizer_config.json +0 -1
  15. transformer/model/vocab.txt +0 -0
  16. vocab/vectors.cfg +3 -0
  17. zh_core_web_trf-any-py3-none-any.whl +2 -2
README.md CHANGED
@@ -14,47 +14,47 @@ model-index:
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
- value: 0.6744976507
18
  - name: NER Recall
19
  type: recall
20
- value: 0.7414285714
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.7063811967
24
  - task:
25
  name: POS
26
  type: token-classification
27
  metrics:
28
  - name: POS Accuracy
29
  type: accuracy
30
- value: 0.92444533
31
  - task:
32
  name: SENTER
33
  type: token-classification
34
  metrics:
35
  - name: SENTER Precision
36
  type: precision
37
- value: 0.6917940608
38
  - name: SENTER Recall
39
  type: recall
40
- value: 0.655402031
41
  - name: SENTER F Score
42
  type: f_score
43
- value: 0.6731065139
44
  - task:
45
  name: UNLABELED_DEPENDENCIES
46
  type: token-classification
47
  metrics:
48
  - name: Unlabeled Dependencies Accuracy
49
  type: accuracy
50
- value: 0.7661671924
51
  - task:
52
  name: LABELED_DEPENDENCIES
53
  type: token-classification
54
  metrics:
55
  - name: Labeled Dependencies Accuracy
56
  type: accuracy
57
- value: 0.7661671924
58
  ---
59
  ### Details: https://spacy.io/models/zh#zh_core_web_trf
60
 
@@ -63,8 +63,8 @@ Chinese transformer pipeline (bert-base-chinese). Components: transformer, tagge
63
  | Feature | Description |
64
  | --- | --- |
65
  | **Name** | `zh_core_web_trf` |
66
- | **Version** | `3.1.0` |
67
- | **spaCy** | `>=3.1.0,<3.2.0` |
68
  | **Default Pipeline** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `ner` |
69
  | **Components** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `ner` |
70
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -91,12 +91,15 @@ Chinese transformer pipeline (bert-base-chinese). Components: transformer, tagge
91
  | Type | Score |
92
  | --- | --- |
93
  | `TOKEN_ACC` | 97.88 |
94
- | `TAG_ACC` | 92.44 |
95
- | `DEP_UAS` | 76.62 |
96
- | `DEP_LAS` | 72.80 |
97
- | `ENTS_P` | 67.45 |
98
- | `ENTS_R` | 74.14 |
99
- | `ENTS_F` | 70.64 |
100
- | `SENTS_P` | 69.18 |
101
- | `SENTS_R` | 65.54 |
102
- | `SENTS_F` | 67.31 |
 
 
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.746365105
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.7615384615
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.7538754419
24
  - task:
25
  name: POS
26
  type: token-classification
27
  metrics:
28
  - name: POS Accuracy
29
  type: accuracy
30
+ value: 0.9247167985
31
  - task:
32
  name: SENTER
33
  type: token-classification
34
  metrics:
35
  - name: SENTER Precision
36
  type: precision
37
+ value: 0.7110739502
38
  - name: SENTER Recall
39
  type: recall
40
+ value: 0.6370900616
41
  - name: SENTER F Score
42
  type: f_score
43
+ value: 0.67205198
44
  - task:
45
  name: UNLABELED_DEPENDENCIES
46
  type: token-classification
47
  metrics:
48
  - name: Unlabeled Dependencies Accuracy
49
  type: accuracy
50
+ value: 0.7683558244
51
  - task:
52
  name: LABELED_DEPENDENCIES
53
  type: token-classification
54
  metrics:
55
  - name: Labeled Dependencies Accuracy
56
  type: accuracy
57
+ value: 0.7683558244
58
  ---
59
  ### Details: https://spacy.io/models/zh#zh_core_web_trf
60
 
63
  | Feature | Description |
64
  | --- | --- |
65
  | **Name** | `zh_core_web_trf` |
66
+ | **Version** | `3.2.0` |
67
+ | **spaCy** | `>=3.2.0,<3.3.0` |
68
  | **Default Pipeline** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `ner` |
69
  | **Components** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `ner` |
70
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
91
  | Type | Score |
92
  | --- | --- |
93
  | `TOKEN_ACC` | 97.88 |
94
+ | `TOKEN_P` | 94.58 |
95
+ | `TOKEN_R` | 91.36 |
96
+ | `TOKEN_F` | 92.94 |
97
+ | `TAG_ACC` | 92.47 |
98
+ | `SENTS_P` | 71.11 |
99
+ | `SENTS_R` | 63.71 |
100
+ | `SENTS_F` | 67.21 |
101
+ | `DEP_UAS` | 76.84 |
102
+ | `DEP_LAS` | 73.07 |
103
+ | `ENTS_P` | 74.64 |
104
+ | `ENTS_R` | 76.15 |
105
+ | `ENTS_F` | 75.39 |
accuracy.json CHANGED
@@ -1,40 +1,39 @@
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  {
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@@ -42,189 +41,189 @@
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@@ -232,101 +231,105 @@
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  "NORP": {
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- "f": 0.6044340723
 
 
 
 
 
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  "PERSON": {
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  "LANGUAGE": {
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  }
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- }
 
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  }
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  "xcomp": {
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102
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103
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104
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105
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106
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107
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108
  "ccomp": {
109
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110
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111
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112
  },
113
  "advmod:rcomp": {
114
+ "p": 0.8541033435,
115
+ "r": 0.7783933518,
116
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117
  },
118
  "nmod:topic": {
119
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120
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121
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122
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123
  "cop": {
124
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125
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126
+ "f": 0.7290821968
127
  },
128
  "discourse": {
129
+ "p": 0.6257833483,
130
+ "r": 0.5767326733,
131
+ "f": 0.6002576213
132
  },
133
  "neg": {
134
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135
+ "r": 0.6706302021,
136
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137
  },
138
  "aux:modal": {
139
+ "p": 0.9086908691,
140
+ "r": 0.854188211,
141
+ "f": 0.8805970149
142
  },
143
  "nmod": {
144
+ "p": 0.8080808081,
145
+ "r": 0.7598371777,
146
+ "f": 0.7832167832
147
  },
148
  "aux:ba": {
149
+ "p": 0.9485714286,
150
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151
+ "f": 0.914600551
152
  },
153
  "advmod:loc": {
154
+ "p": 0.803030303,
155
+ "r": 0.6290801187,
156
+ "f": 0.7054908486
157
  },
158
  "aux:asp": {
159
+ "p": 0.9346349745,
160
+ "r": 0.8779904306,
161
+ "f": 0.9054276316
162
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163
  "conj": {
164
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165
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166
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167
  },
168
  "nsubjpass": {
169
+ "p": 0.9302325581,
170
+ "r": 0.8,
171
+ "f": 0.8602150538
172
  },
173
  "compound:vc": {
174
+ "p": 0.5380952381,
175
+ "r": 0.585492228,
176
+ "f": 0.5607940447
177
  },
178
  "advcl:loc": {
179
+ "p": 0.7894736842,
180
+ "r": 0.6428571429,
181
+ "f": 0.7086614173
182
  },
183
  "cc": {
184
+ "p": 0.8191287879,
185
+ "r": 0.7675244011,
186
+ "f": 0.7924874027
187
  },
188
  "advmod:dvp": {
189
+ "p": 0.8731343284,
190
+ "r": 0.7267080745,
191
+ "f": 0.793220339
192
  },
193
  "amod:ordmod": {
194
+ "p": 0.640625,
195
+ "r": 0.640625,
196
+ "f": 0.640625
197
  },
198
  "appos": {
199
+ "p": 0.9443099274,
200
+ "r": 0.8965517241,
201
+ "f": 0.9198113208
202
  },
203
  "nmod:poss": {
204
+ "p": 0.796460177,
205
+ "r": 0.6666666667,
206
+ "f": 0.7258064516
207
  },
208
  "name": {
209
+ "p": 0.6635514019,
210
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211
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212
  },
213
  "nsubj:xsubj": {
214
+ "p": 0.25,
215
  "r": 0.1,
216
+ "f": 0.1428571429
217
  },
218
  "nmod:range": {
219
+ "p": 0.8365019011,
220
+ "r": 0.7382550336,
221
+ "f": 0.7843137255
222
  },
223
  "parataxis:prnmod": {
224
+ "p": 0.3645833333,
225
+ "r": 0.2631578947,
226
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227
  },
228
  "erased": {
229
  "p": 0.0,
231
  "f": 0.0
232
  },
233
  "etc": {
234
+ "p": 0.8965517241,
235
  "r": 0.9285714286,
236
+ "f": 0.9122807018
237
  }
238
  },
239
+ "ents_p": 0.746365105,
240
+ "ents_r": 0.7615384615,
241
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242
  "ents_per_type": {
243
  "DATE": {
244
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245
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246
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247
  },
248
  "GPE": {
249
+ "p": 0.7898259705,
250
+ "r": 0.8651026393,
251
+ "f": 0.8257522743
 
 
 
 
 
252
  },
253
  "ORDINAL": {
254
+ "p": 0.8720930233,
255
  "r": 0.7894736842,
256
+ "f": 0.8287292818
257
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258
  "FAC": {
259
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260
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261
+ "f": 0.4936386768
262
  },
263
  "ORG": {
264
+ "p": 0.749034749,
265
+ "r": 0.7382039574,
266
+ "f": 0.7435799157
 
 
 
 
 
267
  },
268
  "NORP": {
269
+ "p": 0.6806930693,
270
+ "r": 0.5777310924,
271
+ "f": 0.625
272
+ },
273
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274
+ "p": 0.5765765766,
275
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276
+ "f": 0.5446808511
277
  },
278
  "QUANTITY": {
279
+ "p": 0.6742424242,
280
+ "r": 0.6592592593,
281
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282
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283
  "PERSON": {
284
+ "p": 0.8638871858,
285
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286
+ "f": 0.8853283066
287
+ },
288
+ "CARDINAL": {
289
+ "p": 0.6205821206,
290
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291
+ "f": 0.6110542477
292
  },
293
  "TIME": {
294
+ "p": 0.7630331754,
295
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  },
298
  "WORK_OF_ART": {
299
+ "p": 0.4724409449,
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+ "r": 0.4,
301
+ "f": 0.4332129964
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  },
303
  "MONEY": {
304
+ "p": 0.8615384615,
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  "r": 0.8296296296,
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+ "f": 0.8452830189
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  },
308
  "EVENT": {
309
+ "p": 0.5757575758,
310
+ "r": 0.6985294118,
311
+ "f": 0.6312292359
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  },
313
  "PERCENT": {
314
+ "p": 0.7865168539,
315
+ "r": 0.843373494,
316
+ "f": 0.8139534884
317
  },
318
  "PRODUCT": {
319
+ "p": 0.4814814815,
320
+ "r": 0.2653061224,
321
+ "f": 0.3421052632
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  },
323
  "LAW": {
324
+ "p": 0.3921568627,
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+ "r": 0.3333333333,
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  },
328
  "LANGUAGE": {
329
+ "p": 0.75,
330
  "r": 1.0,
331
+ "f": 0.8571428571
332
  }
333
+ },
334
+ "speed": 4253.4050367787
335
  }
attribute_ruler/patterns CHANGED
Binary files a/attribute_ruler/patterns and b/attribute_ruler/patterns differ
config.cfg CHANGED
@@ -1,10 +1,8 @@
1
  [paths]
2
- train = "corpus/zh-core-news/train.spacy"
3
- dev = "corpus/zh-core-news/dev.spacy"
4
  vectors = null
5
- raw = null
6
  init_tok2vec = null
7
- vocab_data = null
8
 
9
  [system]
10
  gpu_allocator = "pytorch"
@@ -27,12 +25,14 @@ segmenter = "pkuseg"
27
 
28
  [components.attribute_ruler]
29
  factory = "attribute_ruler"
 
30
  validate = false
31
 
32
  [components.ner]
33
  factory = "ner"
34
  incorrect_spans_key = null
35
  moves = null
 
36
  update_with_oracle_cut_size = 100
37
 
38
  [components.ner.model]
@@ -55,6 +55,7 @@ factory = "parser"
55
  learn_tokens = false
56
  min_action_freq = 30
57
  moves = null
 
58
  update_with_oracle_cut_size = 100
59
 
60
  [components.parser.model]
@@ -74,6 +75,8 @@ pooling = {"@layers":"reduce_mean.v1"}
74
 
75
  [components.tagger]
76
  factory = "tagger"
 
 
77
 
78
  [components.tagger.model]
79
  @architectures = "spacy.Tagger.v1"
@@ -91,32 +94,37 @@ max_batch_items = 4096
91
  set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
92
 
93
  [components.transformer.model]
94
- @architectures = "spacy-transformers.TransformerModel.v1"
95
  name = "bert-base-chinese"
 
96
 
97
  [components.transformer.model.get_spans]
98
  @span_getters = "spacy-transformers.strided_spans.v1"
99
  window = 128
100
  stride = 96
101
 
 
 
102
  [components.transformer.model.tokenizer_config]
103
  use_fast = true
104
 
 
 
105
  [corpora]
106
 
107
  [corpora.dev]
108
  @readers = "spacy.Corpus.v1"
109
- limit = 0
110
- max_length = 0
111
- path = ${paths:dev}
112
  gold_preproc = false
 
 
113
  augmenter = null
114
 
115
  [corpora.train]
116
  @readers = "spacy.Corpus.v1"
117
- path = ${paths:train}
118
- max_length = 500
119
  gold_preproc = false
 
120
  limit = 0
121
  augmenter = null
122
 
@@ -174,11 +182,12 @@ ents_f = 0.32
174
  ents_p = 0.0
175
  ents_r = 0.0
176
  ents_per_type = null
 
177
 
178
  [pretraining]
179
 
180
  [initialize]
181
- vocab_data = ${paths.vocab_data}
182
  vectors = ${paths.vectors}
183
  init_tok2vec = ${paths.init_tok2vec}
184
  before_init = null
1
  [paths]
2
+ train = null
3
+ dev = null
4
  vectors = null
 
5
  init_tok2vec = null
 
6
 
7
  [system]
8
  gpu_allocator = "pytorch"
25
 
26
  [components.attribute_ruler]
27
  factory = "attribute_ruler"
28
+ scorer = {"@scorers":"spacy.attribute_ruler_scorer.v1"}
29
  validate = false
30
 
31
  [components.ner]
32
  factory = "ner"
33
  incorrect_spans_key = null
34
  moves = null
35
+ scorer = {"@scorers":"spacy.ner_scorer.v1"}
36
  update_with_oracle_cut_size = 100
37
 
38
  [components.ner.model]
55
  learn_tokens = false
56
  min_action_freq = 30
57
  moves = null
58
+ scorer = {"@scorers":"spacy.parser_scorer.v1"}
59
  update_with_oracle_cut_size = 100
60
 
61
  [components.parser.model]
75
 
76
  [components.tagger]
77
  factory = "tagger"
78
+ overwrite = false
79
+ scorer = {"@scorers":"spacy.tagger_scorer.v1"}
80
 
81
  [components.tagger.model]
82
  @architectures = "spacy.Tagger.v1"
94
  set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
95
 
96
  [components.transformer.model]
97
+ @architectures = "spacy-transformers.TransformerModel.v3"
98
  name = "bert-base-chinese"
99
+ mixed_precision = false
100
 
101
  [components.transformer.model.get_spans]
102
  @span_getters = "spacy-transformers.strided_spans.v1"
103
  window = 128
104
  stride = 96
105
 
106
+ [components.transformer.model.grad_scaler_config]
107
+
108
  [components.transformer.model.tokenizer_config]
109
  use_fast = true
110
 
111
+ [components.transformer.model.transformer_config]
112
+
113
  [corpora]
114
 
115
  [corpora.dev]
116
  @readers = "spacy.Corpus.v1"
117
+ path = ${paths.dev}
 
 
118
  gold_preproc = false
119
+ max_length = 0
120
+ limit = 0
121
  augmenter = null
122
 
123
  [corpora.train]
124
  @readers = "spacy.Corpus.v1"
125
+ path = ${paths.train}
 
126
  gold_preproc = false
127
+ max_length = 0
128
  limit = 0
129
  augmenter = null
130
 
182
  ents_p = 0.0
183
  ents_r = 0.0
184
  ents_per_type = null
185
+ speed = 0.0
186
 
187
  [pretraining]
188
 
189
  [initialize]
190
+ vocab_data = null
191
  vectors = ${paths.vectors}
192
  init_tok2vec = ${paths.init_tok2vec}
193
  before_init = null
meta.json CHANGED
@@ -1,14 +1,14 @@
1
  {
2
  "lang":"zh",
3
  "name":"core_web_trf",
4
- "version":"3.1.0",
5
  "description":"Chinese transformer pipeline (bert-base-chinese). Components: transformer, tagger, parser, ner, attribute_ruler.",
6
  "author":"Explosion",
7
  "email":"contact@explosion.ai",
8
  "url":"https://explosion.ai",
9
  "license":"MIT",
10
- "spacy_version":">=3.1.0,<3.2.0",
11
- "spacy_git_version":"caba63b74",
12
  "vectors":{
13
  "width":0,
14
  "vectors":0,
@@ -147,41 +147,40 @@
147
  ],
148
  "performance":{
149
  "token_acc":0.9788303388,
150
- "tag_acc":0.92444533,
151
- "dep_uas":0.7661671924,
152
- "dep_las":0.727981345,
153
- "ents_p":0.6744976507,
154
- "ents_r":0.7414285714,
155
- "ents_f":0.7063811967,
156
- "sents_p":0.6917940608,
157
- "sents_r":0.655402031,
158
- "sents_f":0.6731065139,
159
- "speed":4304.7686585922,
160
  "dep_las_per_type":{
161
  "dep":{
162
- "p":0.5611908839,
163
- "r":0.4304334647,
164
- "f":0.4871912168
165
  },
166
  "case":{
167
- "p":0.9069435432,
168
- "r":0.8472356935,
169
- "f":0.8760734658
170
  },
171
  "nmod:tmod":{
172
- "p":0.8046448087,
173
- "r":0.8013605442,
174
- "f":0.8029993183
175
  },
176
  "nummod":{
177
- "p":0.9012345679,
178
- "r":0.583610926,
179
- "f":0.7084512738
180
  },
181
  "mark:clf":{
182
- "p":0.9517326733,
183
  "r":0.5736665423,
184
- "f":0.7158482662
185
  },
186
  "auxpass":{
187
  "p":0.9293478261,
@@ -189,189 +188,189 @@
189
  "f":0.9268292683
190
  },
191
  "nsubj":{
192
- "p":0.8733342307,
193
- "r":0.7969536912,
194
- "f":0.8333975594
195
  },
196
  "acl":{
197
- "p":0.8216805645,
198
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199
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200
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201
  "advmod":{
202
- "p":0.8829383266,
203
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204
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205
  },
206
  "mark":{
207
- "p":0.865225391,
208
- "r":0.82427695,
209
- "f":0.8442549372
210
  },
211
  "xcomp":{
212
- "p":0.8221343874,
213
- "r":0.67752443,
214
- "f":0.7428571429
215
  },
216
  "nmod:assmod":{
217
- "p":0.8709787817,
218
- "r":0.7920946156,
219
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220
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221
  "det":{
222
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223
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224
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225
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226
  "amod":{
227
- "p":0.8509749304,
228
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229
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230
  },
231
  "nmod:prep":{
232
- "p":0.8192449048,
233
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234
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235
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236
  "root":{
237
- "p":0.7726093403,
238
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239
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240
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241
  "aux:prtmod":{
242
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243
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245
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246
  "compound:nn":{
247
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248
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251
  "dobj":{
252
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253
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254
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255
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256
  "ccomp":{
257
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258
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260
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261
  "advmod:rcomp":{
262
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263
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264
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265
  },
266
  "nmod:topic":{
267
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271
  "cop":{
272
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273
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276
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277
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278
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279
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280
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281
  "neg":{
282
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283
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284
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285
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286
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291
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326
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