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spacy
/
es_dep_news_trf

Token Classification
spaCy
Spanish
Eval Results
Model card Files Community
adrianeboyd commited on
Commit
287eea0
·
1 Parent(s): cbe7e92

Update spaCy pipeline

Browse files
Files changed (9) hide show
  1. README.md +19 -19
  2. accuracy.json +144 -144
  3. config.cfg +2 -1
  4. es_dep_news_trf-any-py3-none-any.whl +2 -2
  5. meta.json +148 -148
  6. morphologizer/cfg +1 -0
  7. morphologizer/model +1 -1
  8. parser/model +1 -1
  9. transformer/model +2 -2
README.md CHANGED
@@ -14,49 +14,49 @@ model-index:
14
  metrics:
15
  - name: TAG (XPOS) Accuracy
16
  type: accuracy
17
- value: 0.9676584487
18
  - task:
19
  name: POS
20
  type: token-classification
21
  metrics:
22
  - name: POS (UPOS) Accuracy
23
  type: accuracy
24
- value: 0.9915647406
25
  - task:
26
  name: MORPH
27
  type: token-classification
28
  metrics:
29
  - name: Morph (UFeats) Accuracy
30
  type: accuracy
31
- value: 0.9881421409
32
  - task:
33
  name: LEMMA
34
  type: token-classification
35
  metrics:
36
  - name: Lemma Accuracy
37
  type: accuracy
38
- value: 0.968172888
39
  - task:
40
  name: UNLABELED_DEPENDENCIES
41
  type: token-classification
42
  metrics:
43
  - name: Unlabeled Attachment Score (UAS)
44
  type: f_score
45
- value: 0.9474039771
46
  - task:
47
  name: LABELED_DEPENDENCIES
48
  type: token-classification
49
  metrics:
50
  - name: Labeled Attachment Score (LAS)
51
  type: f_score
52
- value: 0.9298190178
53
  - task:
54
  name: SENTS
55
  type: token-classification
56
  metrics:
57
  - name: Sentences F-Score
58
  type: f_score
59
- value: 0.96996997
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** | `3.5.0` |
69
- | **spaCy** | `>=3.5.0,<3.6.0` |
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` | 99.16 |
99
- | `MORPH_ACC` | 98.81 |
100
- | `MORPH_MICRO_P` | 99.68 |
101
  | `MORPH_MICRO_R` | 99.36 |
102
- | `MORPH_MICRO_F` | 99.52 |
103
- | `SENTS_P` | 96.36 |
104
- | `SENTS_R` | 97.64 |
105
  | `SENTS_F` | 97.00 |
106
- | `DEP_UAS` | 94.74 |
107
- | `DEP_LAS` | 92.98 |
108
- | `TAG_ACC` | 96.77 |
109
- | `LEMMA_ACC` | 96.82 |
 
14
  metrics:
15
  - name: TAG (XPOS) Accuracy
16
  type: accuracy
17
+ value: 0.9676386572
18
  - task:
19
  name: POS
20
  type: token-classification
21
  metrics:
22
  - name: POS (UPOS) Accuracy
23
  type: accuracy
24
+ value: 0.9914495504
25
  - task:
26
  name: MORPH
27
  type: token-classification
28
  metrics:
29
  - name: Morph (UFeats) Accuracy
30
  type: accuracy
31
+ value: 0.988017638
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: 0.9467628408
46
  - task:
47
  name: LABELED_DEPENDENCIES
48
  type: token-classification
49
  metrics:
50
  - name: Labeled Attachment Score (LAS)
51
  type: f_score
52
+ value: 0.9292321773
53
  - task:
54
  name: SENTS
55
  type: token-classification
56
  metrics:
57
  - name: Sentences F-Score
58
  type: f_score
59
+ value: 0.9700059988
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** | `3.6.1` |
69
+ | **spaCy** | `>=3.6.0,<3.7.0` |
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` | 99.14 |
99
+ | `MORPH_ACC` | 98.80 |
100
+ | `MORPH_MICRO_P` | 99.67 |
101
  | `MORPH_MICRO_R` | 99.36 |
102
+ | `MORPH_MICRO_F` | 99.51 |
103
+ | `SENTS_P` | 96.25 |
104
+ | `SENTS_R` | 97.76 |
105
  | `SENTS_F` | 97.00 |
106
+ | `DEP_UAS` | 94.68 |
107
+ | `DEP_LAS` | 92.92 |
108
+ | `TAG_ACC` | 96.76 |
109
+ | `LEMMA_ACC` | 96.79 |
accuracy.json CHANGED
@@ -3,66 +3,66 @@
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  "token_p": 0.9989078786,
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  "token_r": 0.9995398685,
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  "token_f": 0.9992237736,
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- "morph_acc": 0.9881421409,
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- "morph_micro_f": 0.9952039245,
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  "morph_per_feat": {
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  "Definite": {
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  "Gender": {
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  "Number": {
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- "r": 0.9944983072,
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  },
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  "PronType": {
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- "r": 0.9960840497,
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- "f": 0.9973223678
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  },
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  "PunctType": {
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- "p": 1.0,
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- "p": 0.9954652072,
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  "Mood": {
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  "r": 0.9910514541,
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  "Person": {
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- "p": 0.9958115183,
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  "r": 0.9932114883,
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- "f": 0.9945098039
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  },
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  "Tense": {
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  },
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  "NumForm": {
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  },
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  },
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  "Poss": {
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  "p": 1.0,
@@ -75,29 +75,29 @@
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  "f": 0.998998999
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  },
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  "Case": {
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- "r": 0.9653979239,
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- "f": 0.968329718
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  "PrepCase": {
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- "p": 0.9989594173,
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- "f": 0.9963674105
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  "AdvType": {
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  "p": 0.9414893617,
@@ -115,146 +115,146 @@
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  "f": 1.0
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  }
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  },
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- "sents_p": 0.9636038186,
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- "sents_r": 0.9764207981,
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- "sents_f": 0.96996997,
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- "dep_uas": 0.9474039771,
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- "dep_las": 0.9298190178,
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  "dep_las_per_type": {
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  "det": {
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  "case": {
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  "expl:pv": {
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  "cop": {
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  "expl:pass": {
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@@ -262,9 +262,9 @@
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  "f": 0.618705036
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  "orphan": {
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@@ -272,9 +272,9 @@
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  "dep": {
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  "p": 0.0,
@@ -292,7 +292,7 @@
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  }
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  },
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- "tag_acc": 0.9676584487,
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- "lemma_acc": 0.968172888,
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- "speed": 6244.6326917205
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  }
 
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