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spacy
/
es_dep_news_trf

Token Classification
spaCy
Spanish
Eval Results
Model card Files Community
Adriane Boyd commited on
Commit
0d2edc9
·
1 Parent(s): 5d18e87

Update spaCy pipeline

Browse files
Files changed (8) hide show
  1. README.md +20 -20
  2. accuracy.json +147 -147
  3. es_dep_news_trf-any-py3-none-any.whl +2 -2
  4. meta.json +150 -150
  5. morphologizer/model +1 -1
  6. parser/model +1 -1
  7. transformer/model +2 -2
  8. vocab/strings.json +2 -2
README.md CHANGED
@@ -14,49 +14,49 @@ model-index:
14
  metrics:
15
  - name: TAG (XPOS) Accuracy
16
  type: accuracy
17
- value: 0.9672676386
18
  - task:
19
  name: POS
20
  type: token-classification
21
  metrics:
22
  - name: POS (UPOS) Accuracy
23
  type: accuracy
24
- value: 0.991133987
25
  - task:
26
  name: MORPH
27
  type: token-classification
28
  metrics:
29
  - name: Morph (UFeats) Accuracy
30
  type: accuracy
31
- value: 0.9882476994
32
  - task:
33
  name: LEMMA
34
  type: token-classification
35
  metrics:
36
  - name: Lemma Accuracy
37
  type: accuracy
38
- value: 0.9678853802
39
  - task:
40
  name: UNLABELED_DEPENDENCIES
41
  type: token-classification
42
  metrics:
43
  - name: Unlabeled Attachment Score (UAS)
44
  type: f_score
45
- value: 0.9473191035
46
  - task:
47
  name: LABELED_DEPENDENCIES
48
  type: token-classification
49
  metrics:
50
  - name: Labeled Attachment Score (LAS)
51
  type: f_score
52
- value: 0.9285130585
53
  - task:
54
  name: SENTS
55
  type: token-classification
56
  metrics:
57
  - name: Sentences F-Score
58
  type: f_score
59
- value: 0.9688436189
60
  ---
61
  ### Details: https://spacy.io/models/es#es_dep_news_trf
62
 
@@ -65,8 +65,8 @@ Spanish transformer pipeline (dccuchile/bert-base-spanish-wwm-cased). Components
65
  | Feature | Description |
66
  | --- | --- |
67
  | **Name** | `es_dep_news_trf` |
68
- | **Version** | `3.3.0` |
69
- | **spaCy** | `>=3.3.0.dev0,<3.4.0` |
70
  | **Default Pipeline** | `transformer`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer` |
71
  | **Components** | `transformer`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer` |
72
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -95,15 +95,15 @@ Spanish transformer pipeline (dccuchile/bert-base-spanish-wwm-cased). Components
95
  | `TOKEN_P` | 99.89 |
96
  | `TOKEN_R` | 99.95 |
97
  | `TOKEN_F` | 99.92 |
98
- | `POS_ACC` | 99.11 |
99
- | `MORPH_ACC` | 98.82 |
100
- | `MORPH_MICRO_P` | 99.67 |
101
- | `MORPH_MICRO_R` | 99.37 |
102
- | `MORPH_MICRO_F` | 99.52 |
103
- | `SENTS_P` | 96.02 |
104
- | `SENTS_R` | 97.76 |
105
- | `SENTS_F` | 96.88 |
106
- | `DEP_UAS` | 94.73 |
107
  | `DEP_LAS` | 92.85 |
108
- | `TAG_ACC` | 96.73 |
109
- | `LEMMA_ACC` | 96.79 |
 
14
  metrics:
15
  - name: TAG (XPOS) Accuracy
16
  type: accuracy
17
+ value: 0.9668829737
18
  - task:
19
  name: POS
20
  type: token-classification
21
  metrics:
22
  - name: POS (UPOS) Accuracy
23
  type: accuracy
24
+ value: 0.9907118962
25
  - task:
26
  name: MORPH
27
  type: token-classification
28
  metrics:
29
  - name: Morph (UFeats) Accuracy
30
  type: accuracy
31
+ value: 0.9876533742
32
  - task:
33
  name: LEMMA
34
  type: token-classification
35
  metrics:
36
  - name: Lemma Accuracy
37
  type: accuracy
38
+ value: 0.9676745412
39
  - task:
40
  name: UNLABELED_DEPENDENCIES
41
  type: token-classification
42
  metrics:
43
  - name: Unlabeled Attachment Score (UAS)
44
  type: f_score
45
+ value: 0.9473948005
46
  - task:
47
  name: LABELED_DEPENDENCIES
48
  type: token-classification
49
  metrics:
50
  - name: Labeled Attachment Score (LAS)
51
  type: f_score
52
+ value: 0.9284912671
53
  - task:
54
  name: SENTS
55
  type: token-classification
56
  metrics:
57
  - name: Sentences F-Score
58
  type: f_score
59
+ value: 0.9738817172
60
  ---
61
  ### Details: https://spacy.io/models/es#es_dep_news_trf
62
 
 
65
  | Feature | Description |
66
  | --- | --- |
67
  | **Name** | `es_dep_news_trf` |
68
+ | **Version** | `3.4.0` |
69
+ | **spaCy** | `>=3.4.0,<3.5.0` |
70
  | **Default Pipeline** | `transformer`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer` |
71
  | **Components** | `transformer`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer` |
72
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
 
95
  | `TOKEN_P` | 99.89 |
96
  | `TOKEN_R` | 99.95 |
97
  | `TOKEN_F` | 99.92 |
98
+ | `POS_ACC` | 99.07 |
99
+ | `MORPH_ACC` | 98.77 |
100
+ | `MORPH_MICRO_P` | 99.68 |
101
+ | `MORPH_MICRO_R` | 99.34 |
102
+ | `MORPH_MICRO_F` | 99.51 |
103
+ | `SENTS_P` | 96.72 |
104
+ | `SENTS_R` | 98.07 |
105
+ | `SENTS_F` | 97.39 |
106
+ | `DEP_UAS` | 94.74 |
107
  | `DEP_LAS` | 92.85 |
108
+ | `TAG_ACC` | 96.69 |
109
+ | `LEMMA_ACC` | 96.77 |
accuracy.json CHANGED
@@ -3,66 +3,66 @@
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  "token_p": 0.9989078786,
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  "token_f": 0.9992237736,
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  "morph_per_feat": {
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  },
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  "Tense": {
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- "p": 0.9836065574,
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- "r": 0.9671993272,
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- "f": 0.9745762712
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  "Poss": {
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  "p": 1.0,
@@ -70,14 +70,14 @@
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  "f": 0.9990850869
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  },
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  "PunctSide": {
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- "f": 0.994994995
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  "Case": {
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- "p": 0.9713292789,
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  "PrepCase": {
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  "p": 1.0,
@@ -85,24 +85,24 @@
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  "f": 0.9968847352
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  },
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  "Reflex": {
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  "Number[psor]": {
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  "p": 1.0,
@@ -115,156 +115,156 @@
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  "f": 1.0
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  }
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  },
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- "sents_p": 0.9602137767,
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- "sents_r": 0.9776299879,
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- "sents_f": 0.9688436189,
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- "dep_uas": 0.9473191035,
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- "dep_las": 0.9285130585,
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  "dep_las_per_type": {
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  "det": {
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@@ -272,9 +272,9 @@
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@@ -292,7 +292,7 @@
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- "tag_acc": 0.9672676386,
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  }
 
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