osanseviero
commited on
Commit
Β·
c4017fc
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Parent(s):
e35ed0c
Update spaCy pipeline
Browse files- .gitattributes +4 -0
- LICENSE +19 -0
- LICENSES_SOURCES +36 -0
- README.md +102 -0
- accuracy.json +332 -0
- attribute_ruler/patterns +0 -0
- config.cfg +217 -0
- meta.json +504 -0
- ner/cfg +13 -0
- ner/model +0 -0
- ner/moves +1 -0
- parser/cfg +13 -0
- parser/model +0 -0
- parser/moves +1 -0
- tagger/cfg +40 -0
- tagger/model +0 -0
- tokenizer/cfg +3 -0
- tokenizer/pkuseg_model/features.msgpack +3 -0
- tokenizer/pkuseg_model/weights.npz +3 -0
- tokenizer/pkuseg_processors +0 -0
- transformer/cfg +3 -0
- transformer/model/config.json +30 -0
- transformer/model/pytorch_model.bin +3 -0
- transformer/model/special_tokens_map.json +1 -0
- transformer/model/tokenizer.json +0 -0
- transformer/model/tokenizer_config.json +1 -0
- transformer/model/vocab.txt +0 -0
- vocab/key2row +1 -0
- vocab/lookups.bin +3 -0
- vocab/strings.json +3 -0
- vocab/vectors +3 -0
- zh_core_web_trf-any-py3-none-any.whl +3 -0
.gitattributes
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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*.whl filter=lfs diff=lfs merge=lfs -text
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*.npz filter=lfs diff=lfs merge=lfs -text
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*strings.json filter=lfs diff=lfs merge=lfs -text
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vectors filter=lfs diff=lfs merge=lfs -text
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LICENSE
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Copyright 2021 ExplosionAI GmbH
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Permission is hereby granted, free of charge, to any person obtaining a copy of
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this software and associated documentation files (the "Software"), to deal in
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the Software without restriction, including without limitation the rights to
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use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
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of the Software, and to permit persons to whom the Software is furnished to do
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so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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LICENSES_SOURCES
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# OntoNotes 5
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* Author: Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston
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* URL: https://catalog.ldc.upenn.edu/LDC2013T19
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* License: commercial (licensed by Explosion)
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```
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```
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# CoreNLP Universal Dependencies Converter
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* Author: Stanford NLP Group
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* URL: https://nlp.stanford.edu/software/stanford-dependencies.html
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* License: Citation provided for reference, no code packaged with model
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```
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```
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# bert-base-chinese
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* Author: Hugging Face
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* URL: https://huggingface.co/bert-base-chinese
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* License:
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```
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```
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README.md
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---
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tags:
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- spacy
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- token-classification
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language:
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- zh
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license: MIT
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model-index:
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- name: zh_core_web_trf
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results:
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- tasks:
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name: NER
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type: token-classification
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metrics:
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- name: Precision
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type: precision
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value: 0.6744976507
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- name: Recall
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type: recall
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value: 0.7414285714
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- name: F Score
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type: f_score
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value: 0.7063811967
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- tasks:
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name: POS
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type: token-classification
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.92444533
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- tasks:
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name: SENTER
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type: token-classification
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metrics:
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- name: Precision
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type: precision
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value: 0.6917940608
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- name: Recall
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type: recall
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value: 0.655402031
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- name: F Score
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type: f_score
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value: 0.6731065139
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- tasks:
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name: UNLABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7661671924
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- tasks:
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name: LABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7661671924
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---
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### Details: https://spacy.io/models/zh#zh_core_web_trf
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Chinese transformer pipeline (bert-base-chinese). Components: transformer, tagger, parser, ner, attribute_ruler.
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| Feature | Description |
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| --- | --- |
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| **Name** | `zh_core_web_trf` |
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| **Version** | `3.1.0` |
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| **spaCy** | `>=3.1.0,<3.2.0` |
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| **Default Pipeline** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `ner` |
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| **Components** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `ner` |
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| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
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| **Sources** | [OntoNotes 5](https://catalog.ldc.upenn.edu/LDC2013T19) (Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston)<br />[CoreNLP Universal Dependencies Converter](https://nlp.stanford.edu/software/stanford-dependencies.html) (Stanford NLP Group)<br />[bert-base-chinese](https://huggingface.co/bert-base-chinese) (Hugging Face) |
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| **License** | `MIT` |
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| **Author** | [Explosion](https://explosion.ai) |
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### Label Scheme
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<details>
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<summary>View label scheme (99 labels for 3 components)</summary>
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| Component | Labels |
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| --- | --- |
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| **`tagger`** | `AD`, `AS`, `BA`, `CC`, `CD`, `CS`, `DEC`, `DEG`, `DER`, `DEV`, `DT`, `ETC`, `FW`, `IJ`, `INF`, `JJ`, `LB`, `LC`, `M`, `MSP`, `NN`, `NR`, `NT`, `OD`, `ON`, `P`, `PN`, `PU`, `SB`, `SP`, `URL`, `VA`, `VC`, `VE`, `VV`, `X` |
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| **`parser`** | `ROOT`, `acl`, `advcl:loc`, `advmod`, `advmod:dvp`, `advmod:loc`, `advmod:rcomp`, `amod`, `amod:ordmod`, `appos`, `aux:asp`, `aux:ba`, `aux:modal`, `aux:prtmod`, `auxpass`, `case`, `cc`, `ccomp`, `compound:nn`, `compound:vc`, `conj`, `cop`, `dep`, `det`, `discourse`, `dobj`, `etc`, `mark`, `mark:clf`, `name`, `neg`, `nmod`, `nmod:assmod`, `nmod:poss`, `nmod:prep`, `nmod:range`, `nmod:tmod`, `nmod:topic`, `nsubj`, `nsubj:xsubj`, `nsubjpass`, `nummod`, `parataxis:prnmod`, `punct`, `xcomp` |
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| **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
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</details>
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### Accuracy
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| Type | Score |
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| --- | --- |
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| `TOKEN_ACC` | 97.88 |
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| `TAG_ACC` | 92.44 |
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| `DEP_UAS` | 76.62 |
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| `DEP_LAS` | 72.80 |
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| `ENTS_P` | 67.45 |
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| `ENTS_R` | 74.14 |
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| `ENTS_F` | 70.64 |
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| `SENTS_P` | 69.18 |
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| `SENTS_R` | 65.54 |
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| `SENTS_F` | 67.31 |
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accuracy.json
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{
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"token_acc": 0.9788303388,
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"tag_acc": 0.92444533,
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"dep_uas": 0.7661671924,
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"dep_las": 0.727981345,
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"ents_p": 0.6744976507,
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"ents_r": 0.7414285714,
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"ents_f": 0.7063811967,
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"sents_p": 0.6917940608,
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"sents_r": 0.655402031,
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"sents_f": 0.6731065139,
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"speed": 4304.7686585922,
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"dep_las_per_type": {
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"dep": {
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"p": 0.5611908839,
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"r": 0.4304334647,
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"f": 0.4871912168
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},
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"case": {
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"p": 0.9069435432,
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"r": 0.8472356935,
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"f": 0.8760734658
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},
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"nmod:tmod": {
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"p": 0.8046448087,
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"r": 0.8013605442,
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"f": 0.8029993183
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},
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"nummod": {
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"p": 0.9012345679,
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"r": 0.583610926,
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"f": 0.7084512738
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},
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"mark:clf": {
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"p": 0.9517326733,
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"r": 0.5736665423,
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"f": 0.7158482662
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},
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"auxpass": {
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"p": 0.9293478261,
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"r": 0.9243243243,
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|
329 |
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|
330 |
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}
|
331 |
+
}
|
332 |
+
}
|
attribute_ruler/patterns
ADDED
Binary file (1.93 kB). View file
|
|
config.cfg
ADDED
@@ -0,0 +1,217 @@
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|
1 |
+
[paths]
|
2 |
+
train = "corpus/zh-core-news/train.spacy"
|
3 |
+
dev = "corpus/zh-core-news/dev.spacy"
|
4 |
+
vectors = null
|
5 |
+
raw = null
|
6 |
+
init_tok2vec = null
|
7 |
+
vocab_data = null
|
8 |
+
|
9 |
+
[system]
|
10 |
+
gpu_allocator = "pytorch"
|
11 |
+
seed = 1
|
12 |
+
|
13 |
+
[nlp]
|
14 |
+
lang = "zh"
|
15 |
+
pipeline = ["transformer","tagger","parser","attribute_ruler","ner"]
|
16 |
+
disabled = []
|
17 |
+
before_creation = null
|
18 |
+
after_creation = null
|
19 |
+
after_pipeline_creation = null
|
20 |
+
batch_size = 64
|
21 |
+
|
22 |
+
[nlp.tokenizer]
|
23 |
+
@tokenizers = "spacy.zh.ChineseTokenizer"
|
24 |
+
segmenter = "pkuseg"
|
25 |
+
|
26 |
+
[components]
|
27 |
+
|
28 |
+
[components.attribute_ruler]
|
29 |
+
factory = "attribute_ruler"
|
30 |
+
validate = false
|
31 |
+
|
32 |
+
[components.ner]
|
33 |
+
factory = "ner"
|
34 |
+
incorrect_spans_key = null
|
35 |
+
moves = null
|
36 |
+
update_with_oracle_cut_size = 100
|
37 |
+
|
38 |
+
[components.ner.model]
|
39 |
+
@architectures = "spacy.TransitionBasedParser.v2"
|
40 |
+
state_type = "ner"
|
41 |
+
extra_state_tokens = false
|
42 |
+
hidden_width = 64
|
43 |
+
maxout_pieces = 2
|
44 |
+
use_upper = false
|
45 |
+
nO = null
|
46 |
+
|
47 |
+
[components.ner.model.tok2vec]
|
48 |
+
@architectures = "spacy-transformers.TransformerListener.v1"
|
49 |
+
grad_factor = 1.0
|
50 |
+
upstream = "transformer"
|
51 |
+
pooling = {"@layers":"reduce_mean.v1"}
|
52 |
+
|
53 |
+
[components.parser]
|
54 |
+
factory = "parser"
|
55 |
+
learn_tokens = false
|
56 |
+
min_action_freq = 30
|
57 |
+
moves = null
|
58 |
+
update_with_oracle_cut_size = 100
|
59 |
+
|
60 |
+
[components.parser.model]
|
61 |
+
@architectures = "spacy.TransitionBasedParser.v2"
|
62 |
+
state_type = "parser"
|
63 |
+
extra_state_tokens = false
|
64 |
+
hidden_width = 64
|
65 |
+
maxout_pieces = 2
|
66 |
+
use_upper = false
|
67 |
+
nO = null
|
68 |
+
|
69 |
+
[components.parser.model.tok2vec]
|
70 |
+
@architectures = "spacy-transformers.TransformerListener.v1"
|
71 |
+
grad_factor = 1.0
|
72 |
+
upstream = "transformer"
|
73 |
+
pooling = {"@layers":"reduce_mean.v1"}
|
74 |
+
|
75 |
+
[components.tagger]
|
76 |
+
factory = "tagger"
|
77 |
+
|
78 |
+
[components.tagger.model]
|
79 |
+
@architectures = "spacy.Tagger.v1"
|
80 |
+
nO = null
|
81 |
+
|
82 |
+
[components.tagger.model.tok2vec]
|
83 |
+
@architectures = "spacy-transformers.TransformerListener.v1"
|
84 |
+
grad_factor = 1.0
|
85 |
+
upstream = "transformer"
|
86 |
+
pooling = {"@layers":"reduce_mean.v1"}
|
87 |
+
|
88 |
+
[components.transformer]
|
89 |
+
factory = "transformer"
|
90 |
+
max_batch_items = 4096
|
91 |
+
set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
|
92 |
+
|
93 |
+
[components.transformer.model]
|
94 |
+
@architectures = "spacy-transformers.TransformerModel.v1"
|
95 |
+
name = "bert-base-chinese"
|
96 |
+
|
97 |
+
[components.transformer.model.get_spans]
|
98 |
+
@span_getters = "spacy-transformers.strided_spans.v1"
|
99 |
+
window = 128
|
100 |
+
stride = 96
|
101 |
+
|
102 |
+
[components.transformer.model.tokenizer_config]
|
103 |
+
use_fast = true
|
104 |
+
|
105 |
+
[corpora]
|
106 |
+
|
107 |
+
[corpora.dev]
|
108 |
+
@readers = "spacy.Corpus.v1"
|
109 |
+
limit = 0
|
110 |
+
max_length = 0
|
111 |
+
path = ${paths:dev}
|
112 |
+
gold_preproc = false
|
113 |
+
augmenter = null
|
114 |
+
|
115 |
+
[corpora.train]
|
116 |
+
@readers = "spacy.Corpus.v1"
|
117 |
+
path = ${paths:train}
|
118 |
+
max_length = 500
|
119 |
+
gold_preproc = false
|
120 |
+
limit = 0
|
121 |
+
augmenter = null
|
122 |
+
|
123 |
+
[training]
|
124 |
+
train_corpus = "corpora.train"
|
125 |
+
dev_corpus = "corpora.dev"
|
126 |
+
seed = ${system:seed}
|
127 |
+
gpu_allocator = ${system:gpu_allocator}
|
128 |
+
dropout = 0.1
|
129 |
+
accumulate_gradient = 3
|
130 |
+
patience = 5000
|
131 |
+
max_epochs = 0
|
132 |
+
max_steps = 20000
|
133 |
+
eval_frequency = 1000
|
134 |
+
frozen_components = []
|
135 |
+
before_to_disk = null
|
136 |
+
annotating_components = []
|
137 |
+
|
138 |
+
[training.batcher]
|
139 |
+
@batchers = "spacy.batch_by_padded.v1"
|
140 |
+
discard_oversize = true
|
141 |
+
get_length = null
|
142 |
+
size = 2000
|
143 |
+
buffer = 256
|
144 |
+
|
145 |
+
[training.logger]
|
146 |
+
@loggers = "spacy.ConsoleLogger.v1"
|
147 |
+
progress_bar = false
|
148 |
+
|
149 |
+
[training.optimizer]
|
150 |
+
@optimizers = "Adam.v1"
|
151 |
+
beta1 = 0.9
|
152 |
+
beta2 = 0.999
|
153 |
+
L2_is_weight_decay = true
|
154 |
+
L2 = 0.01
|
155 |
+
grad_clip = 1.0
|
156 |
+
use_averages = true
|
157 |
+
eps = 0.00000001
|
158 |
+
|
159 |
+
[training.optimizer.learn_rate]
|
160 |
+
@schedules = "warmup_linear.v1"
|
161 |
+
warmup_steps = 250
|
162 |
+
total_steps = 20000
|
163 |
+
initial_rate = 0.00005
|
164 |
+
|
165 |
+
[training.score_weights]
|
166 |
+
tag_acc = 0.32
|
167 |
+
dep_uas = 0.0
|
168 |
+
dep_las = 0.32
|
169 |
+
dep_las_per_type = null
|
170 |
+
sents_p = null
|
171 |
+
sents_r = null
|
172 |
+
sents_f = 0.04
|
173 |
+
ents_f = 0.32
|
174 |
+
ents_p = 0.0
|
175 |
+
ents_r = 0.0
|
176 |
+
ents_per_type = null
|
177 |
+
|
178 |
+
[pretraining]
|
179 |
+
|
180 |
+
[initialize]
|
181 |
+
vocab_data = ${paths.vocab_data}
|
182 |
+
vectors = ${paths.vectors}
|
183 |
+
init_tok2vec = ${paths.init_tok2vec}
|
184 |
+
before_init = null
|
185 |
+
after_init = null
|
186 |
+
|
187 |
+
[initialize.components]
|
188 |
+
|
189 |
+
[initialize.components.ner]
|
190 |
+
|
191 |
+
[initialize.components.ner.labels]
|
192 |
+
@readers = "spacy.read_labels.v1"
|
193 |
+
path = "corpus/labels/ner.json"
|
194 |
+
require = false
|
195 |
+
|
196 |
+
[initialize.components.parser]
|
197 |
+
|
198 |
+
[initialize.components.parser.labels]
|
199 |
+
@readers = "spacy.read_labels.v1"
|
200 |
+
path = "corpus/labels/parser.json"
|
201 |
+
require = false
|
202 |
+
|
203 |
+
[initialize.components.tagger]
|
204 |
+
|
205 |
+
[initialize.components.tagger.labels]
|
206 |
+
@readers = "spacy.read_labels.v1"
|
207 |
+
path = "corpus/labels/tagger.json"
|
208 |
+
require = false
|
209 |
+
|
210 |
+
[initialize.lookups]
|
211 |
+
@misc = "spacy.LookupsDataLoader.v1"
|
212 |
+
lang = ${nlp.lang}
|
213 |
+
tables = []
|
214 |
+
|
215 |
+
[initialize.tokenizer]
|
216 |
+
pkuseg_model = "assets/pkuseg_model"
|
217 |
+
pkuseg_user_dict = "default"
|
meta.json
ADDED
@@ -0,0 +1,504 @@
|
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|
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|
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|
|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"lang":"zh",
|
3 |
+
"name":"core_web_trf",
|
4 |
+
"version":"3.1.0",
|
5 |
+
"description":"Chinese transformer pipeline (bert-base-chinese). Components: transformer, tagger, parser, ner, attribute_ruler.",
|
6 |
+
"author":"Explosion",
|
7 |
+
"email":"contact@explosion.ai",
|
8 |
+
"url":"https://explosion.ai",
|
9 |
+
"license":"MIT",
|
10 |
+
"spacy_version":">=3.1.0,<3.2.0",
|
11 |
+
"spacy_git_version":"caba63b74",
|
12 |
+
"vectors":{
|
13 |
+
"width":0,
|
14 |
+
"vectors":0,
|
15 |
+
"keys":0,
|
16 |
+
"name":null
|
17 |
+
},
|
18 |
+
"labels":{
|
19 |
+
"transformer":[
|
20 |
+
|
21 |
+
],
|
22 |
+
"tagger":[
|
23 |
+
"AD",
|
24 |
+
"AS",
|
25 |
+
"BA",
|
26 |
+
"CC",
|
27 |
+
"CD",
|
28 |
+
"CS",
|
29 |
+
"DEC",
|
30 |
+
"DEG",
|
31 |
+
"DER",
|
32 |
+
"DEV",
|
33 |
+
"DT",
|
34 |
+
"ETC",
|
35 |
+
"FW",
|
36 |
+
"IJ",
|
37 |
+
"INF",
|
38 |
+
"JJ",
|
39 |
+
"LB",
|
40 |
+
"LC",
|
41 |
+
"M",
|
42 |
+
"MSP",
|
43 |
+
"NN",
|
44 |
+
"NR",
|
45 |
+
"NT",
|
46 |
+
"OD",
|
47 |
+
"ON",
|
48 |
+
"P",
|
49 |
+
"PN",
|
50 |
+
"PU",
|
51 |
+
"SB",
|
52 |
+
"SP",
|
53 |
+
"URL",
|
54 |
+
"VA",
|
55 |
+
"VC",
|
56 |
+
"VE",
|
57 |
+
"VV",
|
58 |
+
"X"
|
59 |
+
],
|
60 |
+
"parser":[
|
61 |
+
"ROOT",
|
62 |
+
"acl",
|
63 |
+
"advcl:loc",
|
64 |
+
"advmod",
|
65 |
+
"advmod:dvp",
|
66 |
+
"advmod:loc",
|
67 |
+
"advmod:rcomp",
|
68 |
+
"amod",
|
69 |
+
"amod:ordmod",
|
70 |
+
"appos",
|
71 |
+
"aux:asp",
|
72 |
+
"aux:ba",
|
73 |
+
"aux:modal",
|
74 |
+
"aux:prtmod",
|
75 |
+
"auxpass",
|
76 |
+
"case",
|
77 |
+
"cc",
|
78 |
+
"ccomp",
|
79 |
+
"compound:nn",
|
80 |
+
"compound:vc",
|
81 |
+
"conj",
|
82 |
+
"cop",
|
83 |
+
"dep",
|
84 |
+
"det",
|
85 |
+
"discourse",
|
86 |
+
"dobj",
|
87 |
+
"etc",
|
88 |
+
"mark",
|
89 |
+
"mark:clf",
|
90 |
+
"name",
|
91 |
+
"neg",
|
92 |
+
"nmod",
|
93 |
+
"nmod:assmod",
|
94 |
+
"nmod:poss",
|
95 |
+
"nmod:prep",
|
96 |
+
"nmod:range",
|
97 |
+
"nmod:tmod",
|
98 |
+
"nmod:topic",
|
99 |
+
"nsubj",
|
100 |
+
"nsubj:xsubj",
|
101 |
+
"nsubjpass",
|
102 |
+
"nummod",
|
103 |
+
"parataxis:prnmod",
|
104 |
+
"punct",
|
105 |
+
"xcomp"
|
106 |
+
],
|
107 |
+
"attribute_ruler":[
|
108 |
+
|
109 |
+
],
|
110 |
+
"ner":[
|
111 |
+
"CARDINAL",
|
112 |
+
"DATE",
|
113 |
+
"EVENT",
|
114 |
+
"FAC",
|
115 |
+
"GPE",
|
116 |
+
"LANGUAGE",
|
117 |
+
"LAW",
|
118 |
+
"LOC",
|
119 |
+
"MONEY",
|
120 |
+
"NORP",
|
121 |
+
"ORDINAL",
|
122 |
+
"ORG",
|
123 |
+
"PERCENT",
|
124 |
+
"PERSON",
|
125 |
+
"PRODUCT",
|
126 |
+
"QUANTITY",
|
127 |
+
"TIME",
|
128 |
+
"WORK_OF_ART"
|
129 |
+
]
|
130 |
+
},
|
131 |
+
"pipeline":[
|
132 |
+
"transformer",
|
133 |
+
"tagger",
|
134 |
+
"parser",
|
135 |
+
"attribute_ruler",
|
136 |
+
"ner"
|
137 |
+
],
|
138 |
+
"components":[
|
139 |
+
"transformer",
|
140 |
+
"tagger",
|
141 |
+
"parser",
|
142 |
+
"attribute_ruler",
|
143 |
+
"ner"
|
144 |
+
],
|
145 |
+
"disabled":[
|
146 |
+
|
147 |
+
],
|
148 |
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"performance":{
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ner/cfg
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@@ -0,0 +1,13 @@
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|
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{
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ner/model
ADDED
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ner/moves
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parser/cfg
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@@ -0,0 +1,13 @@
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|
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{
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parser/model
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parser/moves
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οΏ½οΏ½movesοΏ½οΏ½{"0":{"":406724},"1":{"":267280},"2":{"advmod":56948,"nsubj":53528,"compound:nn":43922,"dep":40127,"punct":36036,"case":23985,"nmod:assmod":21598,"nmod:prep":20097,"amod":16922,"acl":11976,"conj":10687,"cop":7237,"det":7209,"nummod":6994,"cc":6236,"aux:modal":5566,"nmod:tmod":5335,"nmod":4914,"neg":4364,"xcomp":3881,"appos":2954,"nmod:topic":2411,"discourse":2163,"advmod:loc":1590,"aux:prtmod":1539,"aux:ba":1311,"auxpass":1220,"advmod:dvp":1142,"advcl:loc":1046,"name":1032,"compound:vc":830,"nmod:poss":560,"amod:ordmod":511,"dobj":406,"nsubjpass":263,"nsubj:xsubj||ccomp":62,"parataxis:prnmod":34,"nsubj:xsubj":32},"3":{"punct":74030,"dobj":45389,"conj":30046,"case":30027,"dep":18664,"ccomp":17217,"mark":16601,"mark:clf":11552,"aux:asp":7896,"discourse":3998,"advmod:rcomp":2388,"nmod:range":1885,"cc":1675,"nmod:prep":1595,"advmod":1117,"etc":941,"compound:vc":790,"parataxis:prnmod":694,"advmod:loc":522,"neg":69,"advcl:loc":39,"acl":39},"4":{"ROOT":34547}}οΏ½cfgοΏ½οΏ½neg_keyοΏ½
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tagger/cfg
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{
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"labels":[
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"AD",
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"AS",
|
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"BA",
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"CC",
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"CD",
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"CS",
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"DEC",
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"DEG",
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"DER",
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"DEV",
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"DT",
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"ETC",
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"FW",
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"IJ",
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"INF",
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"JJ",
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"LB",
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"LC",
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21 |
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"M",
|
22 |
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"MSP",
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"NN",
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24 |
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"NR",
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"NT",
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26 |
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"OD",
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"ON",
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28 |
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"P",
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29 |
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"PN",
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30 |
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"PU",
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31 |
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"SB",
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32 |
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"SP",
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"URL",
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34 |
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"VA",
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35 |
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"VC",
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36 |
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"VE",
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37 |
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"VV",
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38 |
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"X"
|
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]
|
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}
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tagger/model
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tokenizer/cfg
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{
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2 |
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"segmenter":"pkuseg"
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}
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tokenizer/pkuseg_model/features.msgpack
ADDED
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tokenizer/pkuseg_model/weights.npz
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tokenizer/pkuseg_processors
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transformer/cfg
ADDED
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{
|
2 |
+
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|
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}
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transformer/model/config.json
ADDED
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1 |
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{
|
2 |
+
"_name_or_path": "/mnt/scratch/tmp/zh_core_web_trf/d999ed1d-d7a0-4c09-b6e1-c8df4f70f55c/training/core/model-best/transformer/model",
|
3 |
+
"architectures": [
|
4 |
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"BertForMaskedLM"
|
5 |
+
],
|
6 |
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"attention_probs_dropout_prob": 0.1,
|
7 |
+
"directionality": "bidi",
|
8 |
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"gradient_checkpointing": false,
|
9 |
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"hidden_act": "gelu",
|
10 |
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"hidden_dropout_prob": 0.1,
|
11 |
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"hidden_size": 768,
|
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"initializer_range": 0.02,
|
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"pooler_fc_size": 768,
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"pooler_num_attention_heads": 12,
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"pooler_num_fc_layers": 3,
|
23 |
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"pooler_size_per_head": 128,
|
24 |
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"pooler_type": "first_token_transform",
|
25 |
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"position_embedding_type": "absolute",
|
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"transformers_version": "4.6.1",
|
27 |
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"type_vocab_size": 2,
|
28 |
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"use_cache": true,
|
29 |
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"vocab_size": 21128
|
30 |
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}
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transformer/model/pytorch_model.bin
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transformer/model/special_tokens_map.json
ADDED
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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transformer/model/tokenizer.json
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transformer/model/tokenizer_config.json
ADDED
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+
{"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "/mnt/scratch/tmp/zh_core_web_trf/d999ed1d-d7a0-4c09-b6e1-c8df4f70f55c/training/core/model-best/transformer/model"}
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transformer/model/vocab.txt
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vocab/key2row
ADDED
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οΏ½
|
vocab/lookups.bin
ADDED
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vocab/strings.json
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vocab/vectors
ADDED
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zh_core_web_trf-any-py3-none-any.whl
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