adrianeboyd
commited on
Commit
•
5daa22f
1
Parent(s):
a56a017
Update spaCy pipeline
Browse files- README.md +28 -28
- accuracy.json +164 -164
- config.cfg +5 -4
- lemmatizer/model +1 -1
- meta.json +167 -167
- morphologizer/model +1 -1
- ner/model +2 -2
- nl_core_news_lg-any-py3-none-any.whl +2 -2
- parser/model +1 -1
- senter/model +1 -1
- tagger/model +1 -1
- tok2vec/model +2 -2
- tokenizer +0 -0
- vocab/strings.json +2 -2
README.md
CHANGED
@@ -14,62 +14,62 @@ model-index:
|
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metrics:
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- name: NER Precision
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type: precision
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-
value: 0.
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- name: NER Recall
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type: recall
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-
value: 0.
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- name: NER F Score
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type: f_score
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-
value: 0.
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- task:
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name: TAG
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type: token-classification
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metrics:
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- name: TAG (XPOS) Accuracy
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type: accuracy
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-
value: 0.
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- task:
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name: POS
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type: token-classification
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metrics:
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- name: POS (UPOS) Accuracy
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type: accuracy
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-
value: 0.
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- task:
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name: MORPH
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type: token-classification
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metrics:
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- name: Morph (UFeats) Accuracy
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type: accuracy
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-
value: 0.
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- task:
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name: LEMMA
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type: token-classification
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metrics:
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- name: Lemma Accuracy
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type: accuracy
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-
value: 0.
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- task:
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name: UNLABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Unlabeled Attachment Score (UAS)
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type: f_score
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-
value: 0.
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- task:
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name: LABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Labeled Attachment Score (LAS)
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type: f_score
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-
value: 0.
|
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- task:
|
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name: SENTS
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type: token-classification
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metrics:
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- name: Sentences F-Score
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type: f_score
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-
value: 0.
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---
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### Details: https://spacy.io/models/nl#nl_core_news_lg
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|
@@ -78,8 +78,8 @@ Dutch pipeline optimized for CPU. Components: tok2vec, morphologizer, tagger, pa
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| Feature | Description |
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| --- | --- |
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| **Name** | `nl_core_news_lg` |
|
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-
| **Version** | `3.
|
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-
| **spaCy** | `>=3.
|
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| **Default Pipeline** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
|
84 |
| **Components** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
|
85 |
| **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
|
@@ -106,22 +106,22 @@ Dutch pipeline optimized for CPU. Components: tok2vec, morphologizer, tagger, pa
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| Type | Score |
|
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| --- | --- |
|
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-
| `TAG_ACC` | 95.
|
110 |
-
| `SENTS_P` |
|
111 |
-
| `SENTS_R` |
|
112 |
-
| `SENTS_F` | 87.
|
113 |
-
| `DEP_UAS` |
|
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-
| `DEP_LAS` | 82.
|
115 |
-
| `ENTS_P` | 78.
|
116 |
-
| `ENTS_R` |
|
117 |
-
| `ENTS_F` |
|
118 |
-
| `TOKEN_ACC` | 99.
|
119 |
| `TOKEN_P` | 99.74 |
|
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| `TOKEN_R` | 99.76 |
|
121 |
| `TOKEN_F` | 99.75 |
|
122 |
-
| `POS_ACC` | 96.
|
123 |
-
| `MORPH_ACC` | 96.
|
124 |
-
| `MORPH_MICRO_P` | 97.
|
125 |
-
| `MORPH_MICRO_R` | 95.
|
126 |
-
| `MORPH_MICRO_F` | 96.
|
127 |
-
| `LEMMA_ACC` | 95.
|
|
|
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metrics:
|
15 |
- name: NER Precision
|
16 |
type: precision
|
17 |
+
value: 0.7850940666
|
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- name: NER Recall
|
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type: recall
|
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+
value: 0.7503457815
|
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- name: NER F Score
|
22 |
type: f_score
|
23 |
+
value: 0.7673267327
|
24 |
- task:
|
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name: TAG
|
26 |
type: token-classification
|
27 |
metrics:
|
28 |
- name: TAG (XPOS) Accuracy
|
29 |
type: accuracy
|
30 |
+
value: 0.9514067612
|
31 |
- task:
|
32 |
name: POS
|
33 |
type: token-classification
|
34 |
metrics:
|
35 |
- name: POS (UPOS) Accuracy
|
36 |
type: accuracy
|
37 |
+
value: 0.9638822246
|
38 |
- task:
|
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name: MORPH
|
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type: token-classification
|
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metrics:
|
42 |
- name: Morph (UFeats) Accuracy
|
43 |
type: accuracy
|
44 |
+
value: 0.9628967172
|
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- task:
|
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name: LEMMA
|
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type: token-classification
|
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metrics:
|
49 |
- name: Lemma Accuracy
|
50 |
type: accuracy
|
51 |
+
value: 0.9556229147
|
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- task:
|
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name: UNLABELED_DEPENDENCIES
|
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type: token-classification
|
55 |
metrics:
|
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- name: Unlabeled Attachment Score (UAS)
|
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type: f_score
|
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+
value: 0.8702417761
|
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- task:
|
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name: LABELED_DEPENDENCIES
|
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type: token-classification
|
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metrics:
|
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- name: Labeled Attachment Score (LAS)
|
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type: f_score
|
65 |
+
value: 0.8253421186
|
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- task:
|
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name: SENTS
|
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type: token-classification
|
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metrics:
|
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- name: Sentences F-Score
|
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type: f_score
|
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+
value: 0.8731501057
|
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---
|
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### Details: https://spacy.io/models/nl#nl_core_news_lg
|
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|
|
|
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| Feature | Description |
|
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| --- | --- |
|
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| **Name** | `nl_core_news_lg` |
|
81 |
+
| **Version** | `3.5.0` |
|
82 |
+
| **spaCy** | `>=3.5.0,<3.6.0` |
|
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| **Default Pipeline** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
|
84 |
| **Components** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
|
85 |
| **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
|
|
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|
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| Type | Score |
|
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| --- | --- |
|
109 |
+
| `TAG_ACC` | 95.14 |
|
110 |
+
| `SENTS_P` | 85.80 |
|
111 |
+
| `SENTS_R` | 88.88 |
|
112 |
+
| `SENTS_F` | 87.32 |
|
113 |
+
| `DEP_UAS` | 87.02 |
|
114 |
+
| `DEP_LAS` | 82.53 |
|
115 |
+
| `ENTS_P` | 78.51 |
|
116 |
+
| `ENTS_R` | 75.03 |
|
117 |
+
| `ENTS_F` | 76.73 |
|
118 |
+
| `TOKEN_ACC` | 99.94 |
|
119 |
| `TOKEN_P` | 99.74 |
|
120 |
| `TOKEN_R` | 99.76 |
|
121 |
| `TOKEN_F` | 99.75 |
|
122 |
+
| `POS_ACC` | 96.39 |
|
123 |
+
| `MORPH_ACC` | 96.29 |
|
124 |
+
| `MORPH_MICRO_P` | 97.12 |
|
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+
| `MORPH_MICRO_R` | 95.47 |
|
126 |
+
| `MORPH_MICRO_F` | 96.29 |
|
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+
| `LEMMA_ACC` | 95.56 |
|
accuracy.json
CHANGED
@@ -1,191 +1,196 @@
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config.cfg
CHANGED
@@ -81,8 +81,8 @@ nO = null
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|
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[components.ner.model.tok2vec.embed]
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[components.ner.model.tok2vec.encode]
|
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172 |
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[components.tok2vec.model.encode]
|
@@ -209,6 +209,7 @@ eval_frequency = 1000
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212 |
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213 |
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214 |
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81 |
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lemmatizer/model
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