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reneknaebel
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de_dep_hdt_dist

Token Classification
spaCy
German
Eval Results
Model card Files Community
rknaebel commited on
Commit
240012f
·
1 Parent(s): b27a285

Update spaCy pipeline

Browse files
Files changed (9) hide show
  1. README.md +21 -21
  2. de_dep_hdt_dist-any-py3-none-any.whl +2 -2
  3. meta.json +166 -166
  4. morphologizer/model +1 -1
  5. parser/model +1 -1
  6. tagger/model +1 -1
  7. trainable_lemmatizer/model +1 -1
  8. transformer/model +1 -1
  9. vocab/strings.json +2 -2
README.md CHANGED
@@ -13,49 +13,49 @@ model-index:
13
  metrics:
14
  - name: TAG (XPOS) Accuracy
15
  type: accuracy
16
- value: 0.9820812758
17
  - task:
18
  name: POS
19
  type: token-classification
20
  metrics:
21
  - name: POS (UPOS) Accuracy
22
  type: accuracy
23
- value: 0.9826540575
24
  - task:
25
  name: MORPH
26
  type: token-classification
27
  metrics:
28
  - name: Morph (UFeats) Accuracy
29
  type: accuracy
30
- value: 0.8748718992
31
  - task:
32
  name: LEMMA
33
  type: token-classification
34
  metrics:
35
  - name: Lemma Accuracy
36
  type: accuracy
37
- value: 0.9377750766
38
  - task:
39
  name: UNLABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Unlabeled Attachment Score (UAS)
43
  type: f_score
44
- value: 0.9649132786
45
  - task:
46
  name: LABELED_DEPENDENCIES
47
  type: token-classification
48
  metrics:
49
  - name: Labeled Attachment Score (LAS)
50
  type: f_score
51
- value: 0.9505498411
52
  - task:
53
  name: SENTS
54
  type: token-classification
55
  metrics:
56
  - name: Sentences F-Score
57
  type: f_score
58
- value: 0.98269539
59
  ---
60
  | Feature | Description |
61
  | --- | --- |
@@ -87,17 +87,17 @@ model-index:
87
 
88
  | Type | Score |
89
  | --- | --- |
90
- | `TAG_ACC` | 2.60 |
91
- | `POS_ACC` | 21.41 |
92
- | `MORPH_ACC` | 1.29 |
93
- | `LEMMA_ACC` | 67.01 |
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- | `DEP_UAS` | 8.79 |
95
- | `DEP_LAS` | 0.95 |
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- | `SENTS_P` | 0.01 |
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- | `SENTS_R` | 0.01 |
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- | `SENTS_F` | 0.01 |
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- | `TRANSFORMER_LOSS` | 277625.79 |
100
- | `TAGGER_LOSS` | 118955.58 |
101
- | `MORPHOLOGIZER_LOSS` | 121005.44 |
102
- | `TRAINABLE_LEMMATIZER_LOSS` | 121191.12 |
103
- | `PARSER_LOSS` | 211127.24 |
 
13
  metrics:
14
  - name: TAG (XPOS) Accuracy
15
  type: accuracy
16
+ value: 0.9820096945
17
  - task:
18
  name: POS
19
  type: token-classification
20
  metrics:
21
  - name: POS (UPOS) Accuracy
22
  type: accuracy
23
+ value: 0.9826215529
24
  - task:
25
  name: MORPH
26
  type: token-classification
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  metrics:
28
  - name: Morph (UFeats) Accuracy
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  type: accuracy
30
+ value: 0.8750692321
31
  - task:
32
  name: LEMMA
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  type: token-classification
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  metrics:
35
  - name: Lemma Accuracy
36
  type: accuracy
37
+ value: 0.9402498871
38
  - task:
39
  name: UNLABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Unlabeled Attachment Score (UAS)
43
  type: f_score
44
+ value: 0.9658369416
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  - task:
46
  name: LABELED_DEPENDENCIES
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  type: token-classification
48
  metrics:
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  - name: Labeled Attachment Score (LAS)
50
  type: f_score
51
+ value: 0.9518845257
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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: 0.9825772607
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  ---
60
  | Feature | Description |
61
  | --- | --- |
 
87
 
88
  | Type | Score |
89
  | --- | --- |
90
+ | `TAG_ACC` | 98.20 |
91
+ | `POS_ACC` | 98.26 |
92
+ | `MORPH_ACC` | 87.51 |
93
+ | `LEMMA_ACC` | 94.02 |
94
+ | `DEP_UAS` | 96.58 |
95
+ | `DEP_LAS` | 95.19 |
96
+ | `SENTS_P` | 98.46 |
97
+ | `SENTS_R` | 98.05 |
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+ | `SENTS_F` | 98.26 |
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+ | `TRANSFORMER_LOSS` | 6737451.05 |
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+ | `TAGGER_LOSS` | 371214.67 |
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+ | `MORPHOLOGIZER_LOSS` | 1534248.79 |
102
+ | `TRAINABLE_LEMMATIZER_LOSS` | 1361668.67 |
103
+ | `PARSER_LOSS` | 3465429.74 |
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