adrianeboyd
commited on
Commit
•
e2bbeeb
1
Parent(s):
6084989
Update spaCy pipeline
Browse files- README.md +20 -20
- accuracy.json +123 -128
- ja_core_news_md-any-py3-none-any.whl +2 -2
- meta.json +126 -131
- morphologizer/cfg +1 -0
- morphologizer/model +1 -1
- ner/model +1 -1
- parser/model +1 -1
- senter/model +1 -1
- tok2vec/model +1 -1
- vocab/strings.json +2 -2
README.md
CHANGED
@@ -14,27 +14,27 @@ model-index:
|
|
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metrics:
|
15 |
- name: NER Precision
|
16 |
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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36 |
type: accuracy
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37 |
-
value: 0.
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- task:
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name: MORPH
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type: token-classification
|
@@ -55,21 +55,21 @@ model-index:
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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/ja#ja_core_news_md
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|
@@ -78,8 +78,8 @@ Japanese pipeline optimized for CPU. Components: tok2vec, morphologizer, parser,
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| Feature | Description |
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| --- | --- |
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| **Name** | `ja_core_news_md` |
|
81 |
-
| **Version** | `3.
|
82 |
-
| **spaCy** | `>=3.
|
83 |
| **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `ner` |
|
84 |
| **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `ner` |
|
85 |
| **Vectors** | 480443 keys, 20000 unique vectors (300 dimensions) |
|
@@ -109,18 +109,18 @@ Japanese pipeline optimized for CPU. Components: tok2vec, morphologizer, parser,
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| `TOKEN_P` | 97.65 |
|
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| `TOKEN_R` | 97.90 |
|
111 |
| `TOKEN_F` | 97.77 |
|
112 |
-
| `POS_ACC` | 97.
|
113 |
| `MORPH_ACC` | 0.00 |
|
114 |
| `MORPH_MICRO_P` | 34.01 |
|
115 |
| `MORPH_MICRO_R` | 98.04 |
|
116 |
| `MORPH_MICRO_F` | 50.51 |
|
117 |
-
| `SENTS_P` |
|
118 |
-
| `SENTS_R` |
|
119 |
-
| `SENTS_F` |
|
120 |
-
| `DEP_UAS` | 92.
|
121 |
-
| `DEP_LAS` | 90.
|
122 |
-
| `TAG_ACC` | 97.
|
123 |
| `LEMMA_ACC` | 96.71 |
|
124 |
-
| `ENTS_P` |
|
125 |
-
| `ENTS_R` |
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-
| `ENTS_F` |
|
|
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metrics:
|
15 |
- name: NER Precision
|
16 |
type: precision
|
17 |
+
value: 0.7286295794
|
18 |
- name: NER Recall
|
19 |
type: recall
|
20 |
+
value: 0.6754716981
|
21 |
- name: NER F Score
|
22 |
type: f_score
|
23 |
+
value: 0.7010443864
|
24 |
- task:
|
25 |
name: TAG
|
26 |
type: token-classification
|
27 |
metrics:
|
28 |
- name: TAG (XPOS) Accuracy
|
29 |
type: accuracy
|
30 |
+
value: 0.9713305562
|
31 |
- task:
|
32 |
name: POS
|
33 |
type: token-classification
|
34 |
metrics:
|
35 |
- name: POS (UPOS) Accuracy
|
36 |
type: accuracy
|
37 |
+
value: 0.9729199051
|
38 |
- task:
|
39 |
name: MORPH
|
40 |
type: token-classification
|
|
|
55 |
metrics:
|
56 |
- name: Unlabeled Attachment Score (UAS)
|
57 |
type: f_score
|
58 |
+
value: 0.9206249156
|
59 |
- task:
|
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name: LABELED_DEPENDENCIES
|
61 |
type: token-classification
|
62 |
metrics:
|
63 |
- name: Labeled Attachment Score (LAS)
|
64 |
type: f_score
|
65 |
+
value: 0.9067758481
|
66 |
- task:
|
67 |
name: SENTS
|
68 |
type: token-classification
|
69 |
metrics:
|
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- name: Sentences F-Score
|
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type: f_score
|
72 |
+
value: 0.9901574803
|
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---
|
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### Details: https://spacy.io/models/ja#ja_core_news_md
|
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|
|
|
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| Feature | Description |
|
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| --- | --- |
|
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| **Name** | `ja_core_news_md` |
|
81 |
+
| **Version** | `3.6.0` |
|
82 |
+
| **spaCy** | `>=3.6.0,<3.7.0` |
|
83 |
| **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `ner` |
|
84 |
| **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `ner` |
|
85 |
| **Vectors** | 480443 keys, 20000 unique vectors (300 dimensions) |
|
|
|
109 |
| `TOKEN_P` | 97.65 |
|
110 |
| `TOKEN_R` | 97.90 |
|
111 |
| `TOKEN_F` | 97.77 |
|
112 |
+
| `POS_ACC` | 97.29 |
|
113 |
| `MORPH_ACC` | 0.00 |
|
114 |
| `MORPH_MICRO_P` | 34.01 |
|
115 |
| `MORPH_MICRO_R` | 98.04 |
|
116 |
| `MORPH_MICRO_F` | 50.51 |
|
117 |
+
| `SENTS_P` | 98.82 |
|
118 |
+
| `SENTS_R` | 99.21 |
|
119 |
+
| `SENTS_F` | 99.02 |
|
120 |
+
| `DEP_UAS` | 92.06 |
|
121 |
+
| `DEP_LAS` | 90.68 |
|
122 |
+
| `TAG_ACC` | 97.13 |
|
123 |
| `LEMMA_ACC` | 96.71 |
|
124 |
+
| `ENTS_P` | 72.86 |
|
125 |
+
| `ENTS_R` | 67.55 |
|
126 |
+
| `ENTS_F` | 70.10 |
|
accuracy.json
CHANGED
@@ -3,7 +3,7 @@
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|
3 |
"token_p": 0.9764591282,
|
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"token_r": 0.9790021974,
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"token_f": 0.9777290092,
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"morph_acc": 0.0,
|
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"morph_micro_p": 0.3401360544,
|
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"morph_micro_r": 0.9803921569,
|
@@ -25,31 +25,31 @@
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"f": 0.0
|
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}
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},
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@@ -57,74 +57,74 @@
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@@ -132,111 +132,111 @@
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@@ -244,15 +244,10 @@
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