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zh_lzh_sigtyp_trf

Token Classification
spaCy
Chinese
Eval Results (legacy)
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ljvmiranda921 commited on
Commit
a88137c
·
1 Parent(s): 0811cd4

zh_lzh_sigtyp_trf-0.1.0: Update SIGTYP pipeline

Browse files
Files changed (8) hide show
  1. README.md +20 -20
  2. meta.json +178 -178
  3. morphologizer/model +0 -0
  4. parser/model +1 -1
  5. tagger/model +0 -0
  6. trainable_lemmatizer/model +0 -0
  7. transformer/model +1 -1
  8. zh_lzh_sigtyp_trf-any-py3-none-any.whl +2 -2
README.md CHANGED
@@ -13,49 +13,49 @@ model-index:
13
  metrics:
14
  - name: TAG (XPOS) Accuracy
15
  type: accuracy
16
- value: 0.7418288567
17
  - task:
18
  name: POS
19
  type: token-classification
20
  metrics:
21
  - name: POS (UPOS) Accuracy
22
  type: accuracy
23
- value: 0.794490103
24
  - task:
25
  name: MORPH
26
  type: token-classification
27
  metrics:
28
  - name: Morph (UFeats) Accuracy
29
  type: accuracy
30
- value: 0.823496743
31
  - task:
32
  name: LEMMA
33
  type: token-classification
34
  metrics:
35
  - name: Lemma Accuracy
36
  type: accuracy
37
- value: 0.941164414
38
  - task:
39
  name: UNLABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Unlabeled Attachment Score (UAS)
43
  type: f_score
44
- value: 0.8227824679
45
  - task:
46
  name: LABELED_DEPENDENCIES
47
  type: token-classification
48
  metrics:
49
  - name: Labeled Attachment Score (LAS)
50
  type: f_score
51
- value: 0.7687085041
52
  - task:
53
  name: SENTS
54
  type: token-classification
55
  metrics:
56
  - name: Sentences F-Score
57
  type: f_score
58
- value: 0.9942116231
59
  ---
60
  | Feature | Description |
61
  | --- | --- |
@@ -88,16 +88,16 @@ model-index:
88
  | Type | Score |
89
  | --- | --- |
90
  | `DEP_UAS` | 82.28 |
91
- | `DEP_LAS` | 76.87 |
92
- | `SENTS_P` | 99.26 |
93
- | `SENTS_R` | 99.58 |
94
- | `SENTS_F` | 99.42 |
95
- | `LEMMA_ACC` | 94.12 |
96
- | `TAG_ACC` | 74.18 |
97
- | `POS_ACC` | 79.45 |
98
- | `MORPH_ACC` | 82.35 |
99
- | `TRANSFORMER_LOSS` | 3455711.53 |
100
- | `PARSER_LOSS` | 1091508.57 |
101
- | `TRAINABLE_LEMMATIZER_LOSS` | 103471.04 |
102
- | `TAGGER_LOSS` | 2743935.00 |
103
- | `MORPHOLOGIZER_LOSS` | 2387347.18 |
 
13
  metrics:
14
  - name: TAG (XPOS) Accuracy
15
  type: accuracy
16
+ value: 0.742052984
17
  - task:
18
  name: POS
19
  type: token-classification
20
  metrics:
21
  - name: POS (UPOS) Accuracy
22
  type: accuracy
23
+ value: 0.7949418685
24
  - task:
25
  name: MORPH
26
  type: token-classification
27
  metrics:
28
  - name: Morph (UFeats) Accuracy
29
  type: accuracy
30
+ value: 0.8236478744
31
  - task:
32
  name: LEMMA
33
  type: token-classification
34
  metrics:
35
  - name: Lemma Accuracy
36
  type: accuracy
37
+ value: 0.942007037
38
  - task:
39
  name: UNLABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Unlabeled Attachment Score (UAS)
43
  type: f_score
44
+ value: 0.8228271306
45
  - task:
46
  name: LABELED_DEPENDENCIES
47
  type: token-classification
48
  metrics:
49
  - name: Labeled Attachment Score (LAS)
50
  type: f_score
51
+ value: 0.7703219397
52
  - task:
53
  name: SENTS
54
  type: token-classification
55
  metrics:
56
  - name: Sentences F-Score
57
  type: f_score
58
+ value: 0.9851073655
59
  ---
60
  | Feature | Description |
61
  | --- | --- |
 
88
  | Type | Score |
89
  | --- | --- |
90
  | `DEP_UAS` | 82.28 |
91
+ | `DEP_LAS` | 77.03 |
92
+ | `SENTS_P` | 98.08 |
93
+ | `SENTS_R` | 98.94 |
94
+ | `SENTS_F` | 98.51 |
95
+ | `LEMMA_ACC` | 94.20 |
96
+ | `TAG_ACC` | 74.21 |
97
+ | `POS_ACC` | 79.49 |
98
+ | `MORPH_ACC` | 82.36 |
99
+ | `TRANSFORMER_LOSS` | 3733506.66 |
100
+ | `PARSER_LOSS` | 1170567.44 |
101
+ | `TRAINABLE_LEMMATIZER_LOSS` | 98325.33 |
102
+ | `TAGGER_LOSS` | 2806037.87 |
103
+ | `MORPHOLOGIZER_LOSS` | 2426650.00 |
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