magepol commited on
Commit
1e535a9
·
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1 Parent(s): 235ad53

Update spaCy pipeline

Browse files
.gitattributes CHANGED
@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ en_generic_big-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
37
+ textcat/model filter=lfs diff=lfs merge=lfs -text
38
+ tok2vec/model filter=lfs diff=lfs merge=lfs -text
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+ vocab/key2row filter=lfs diff=lfs merge=lfs -text
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+ vocab/vectors filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,67 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - spacy
4
+ - token-classification
5
+ - text-classification
6
+ language:
7
+ - en
8
+ model-index:
9
+ - name: en_generic_big
10
+ results:
11
+ - task:
12
+ name: NER
13
+ type: token-classification
14
+ metrics:
15
+ - name: NER Precision
16
+ type: precision
17
+ value: 0.9469753547
18
+ - name: NER Recall
19
+ type: recall
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+ value: 0.9399555226
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+ - name: NER F Score
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+ type: f_score
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+ value: 0.943452381
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+ ---
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+ | Feature | Description |
26
+ | --- | --- |
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+ | **Name** | `en_generic_big` |
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+ | **Version** | `0.0.1` |
29
+ | **spaCy** | `>=3.7.5,<3.8.0` |
30
+ | **Default Pipeline** | `tok2vec`, `ner`, `textcat` |
31
+ | **Components** | `tok2vec`, `ner`, `textcat` |
32
+ | **Vectors** | 514157 keys, 514157 unique vectors (300 dimensions) |
33
+ | **Sources** | n/a |
34
+ | **License** | n/a |
35
+ | **Author** | [n/a]() |
36
+
37
+ ### Label Scheme
38
+
39
+ <details>
40
+
41
+ <summary>View label scheme (35 labels for 2 components)</summary>
42
+
43
+ | Component | Labels |
44
+ | --- | --- |
45
+ | **`ner`** | `AGE`, `BRAND`, `CLOCK_SPEED`, `COLOR`, `CORE_COUNT`, `DECORATION`, `FEATURE`, `FIT`, `GENDER`, `GRAPHICS`, `GRAPHICS_RAM`, `MATERIAL`, `MEASUREMENT`, `MEASUREMENT_AREA`, `MEM_TYPE`, `MODEL_NUMBER`, `NECKLINE`, `OPERATING_SYSTEM`, `PROCESSOR`, `PROCESSOR_MODEL`, `PRODUCT_SERIES`, `RAM`, `RESOLUTION`, `SCREEN_SIZE`, `SCREEN_TYPE`, `SIZE`, `SLEEVE`, `STORAGE`, `STORAGE_TYPE`, `TAG`, `TYPE`, `ZIP` |
46
+ | **`textcat`** | `212`, `297`, `328` |
47
+
48
+ </details>
49
+
50
+ ### Accuracy
51
+
52
+ | Type | Score |
53
+ | --- | --- |
54
+ | `ENTS_F` | 94.35 |
55
+ | `ENTS_P` | 94.70 |
56
+ | `ENTS_R` | 94.00 |
57
+ | `CATS_SCORE` | 100.00 |
58
+ | `CATS_MICRO_P` | 100.00 |
59
+ | `CATS_MICRO_R` | 100.00 |
60
+ | `CATS_MICRO_F` | 100.00 |
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+ | `CATS_MACRO_P` | 100.00 |
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+ | `CATS_MACRO_R` | 100.00 |
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+ | `CATS_MACRO_F` | 100.00 |
64
+ | `CATS_MACRO_AUC` | 100.00 |
65
+ | `TOK2VEC_LOSS` | 28927.81 |
66
+ | `NER_LOSS` | 63903.29 |
67
+ | `TEXTCAT_LOSS` | 0.08 |
config.cfg ADDED
@@ -0,0 +1,176 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [paths]
2
+ train = "data/big-cat/train.spacy"
3
+ dev = "data/big-cat/dev.spacy"
4
+ vectors = "en_core_web_lg"
5
+ init_tok2vec = null
6
+
7
+ [system]
8
+ gpu_allocator = null
9
+ seed = 0
10
+
11
+ [nlp]
12
+ lang = "en"
13
+ pipeline = ["tok2vec","ner","textcat"]
14
+ batch_size = 1000
15
+ disabled = []
16
+ before_creation = null
17
+ after_creation = null
18
+ after_pipeline_creation = null
19
+ tokenizer = {"@tokenizers":"custom_tokenizer"}
20
+ vectors = {"@vectors":"spacy.Vectors.v1"}
21
+
22
+ [components]
23
+
24
+ [components.ner]
25
+ factory = "ner"
26
+ incorrect_spans_key = null
27
+ moves = null
28
+ scorer = {"@scorers":"spacy.ner_scorer.v1"}
29
+ update_with_oracle_cut_size = 100
30
+
31
+ [components.ner.model]
32
+ @architectures = "spacy.TransitionBasedParser.v2"
33
+ state_type = "ner"
34
+ extra_state_tokens = false
35
+ hidden_width = 64
36
+ maxout_pieces = 2
37
+ use_upper = true
38
+ nO = null
39
+
40
+ [components.ner.model.tok2vec]
41
+ @architectures = "spacy.Tok2VecListener.v1"
42
+ width = ${components.tok2vec.model.encode.width}
43
+ upstream = "*"
44
+
45
+ [components.textcat]
46
+ factory = "textcat"
47
+ scorer = {"@scorers":"spacy.textcat_scorer.v2"}
48
+ threshold = 0.0
49
+
50
+ [components.textcat.model]
51
+ @architectures = "spacy.TextCatEnsemble.v2"
52
+ nO = null
53
+
54
+ [components.textcat.model.linear_model]
55
+ @architectures = "spacy.TextCatBOW.v2"
56
+ exclusive_classes = true
57
+ ngram_size = 1
58
+ no_output_layer = false
59
+ nO = null
60
+
61
+ [components.textcat.model.tok2vec]
62
+ @architectures = "spacy.Tok2VecListener.v1"
63
+ width = ${components.tok2vec.model.encode.width}
64
+ upstream = "*"
65
+
66
+ [components.tok2vec]
67
+ factory = "tok2vec"
68
+
69
+ [components.tok2vec.model]
70
+ @architectures = "spacy.Tok2Vec.v2"
71
+
72
+ [components.tok2vec.model.embed]
73
+ @architectures = "spacy.MultiHashEmbed.v2"
74
+ width = ${components.tok2vec.model.encode.width}
75
+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
76
+ rows = [5000,1000,2500,2500]
77
+ include_static_vectors = true
78
+
79
+ [components.tok2vec.model.encode]
80
+ @architectures = "spacy.MaxoutWindowEncoder.v2"
81
+ width = 256
82
+ depth = 8
83
+ window_size = 1
84
+ maxout_pieces = 3
85
+
86
+ [corpora]
87
+
88
+ [corpora.dev]
89
+ @readers = "spacy.Corpus.v1"
90
+ path = ${paths.dev}
91
+ max_length = 0
92
+ gold_preproc = false
93
+ limit = 0
94
+ augmenter = null
95
+
96
+ [corpora.train]
97
+ @readers = "spacy.Corpus.v1"
98
+ path = ${paths.train}
99
+ max_length = 0
100
+ gold_preproc = false
101
+ limit = 0
102
+ augmenter = null
103
+
104
+ [training]
105
+ dev_corpus = "corpora.dev"
106
+ train_corpus = "corpora.train"
107
+ seed = ${system.seed}
108
+ gpu_allocator = ${system.gpu_allocator}
109
+ dropout = 0.1
110
+ accumulate_gradient = 1
111
+ patience = 1600
112
+ max_epochs = 0
113
+ max_steps = 20000
114
+ eval_frequency = 200
115
+ frozen_components = []
116
+ annotating_components = []
117
+ before_to_disk = null
118
+ before_update = null
119
+
120
+ [training.batcher]
121
+ @batchers = "spacy.batch_by_words.v1"
122
+ discard_oversize = false
123
+ tolerance = 0.2
124
+ get_length = null
125
+
126
+ [training.batcher.size]
127
+ @schedules = "compounding.v1"
128
+ start = 100
129
+ stop = 1000
130
+ compound = 1.001
131
+ t = 0.0
132
+
133
+ [training.logger]
134
+ @loggers = "spacy.ConsoleLogger.v1"
135
+ progress_bar = true
136
+
137
+ [training.optimizer]
138
+ @optimizers = "Adam.v1"
139
+ beta1 = 0.9
140
+ beta2 = 0.999
141
+ L2_is_weight_decay = true
142
+ L2 = 0.01
143
+ grad_clip = 1.0
144
+ use_averages = false
145
+ eps = 0.00000001
146
+ learn_rate = 0.001
147
+
148
+ [training.score_weights]
149
+ ents_f = 0.5
150
+ ents_p = 0.0
151
+ ents_r = 0.0
152
+ ents_per_type = null
153
+ cats_score = 0.5
154
+ cats_score_desc = null
155
+ cats_micro_p = null
156
+ cats_micro_r = null
157
+ cats_micro_f = null
158
+ cats_macro_p = null
159
+ cats_macro_r = null
160
+ cats_macro_f = null
161
+ cats_macro_auc = null
162
+ cats_f_per_type = null
163
+
164
+ [pretraining]
165
+
166
+ [initialize]
167
+ vectors = ${paths.vectors}
168
+ init_tok2vec = ${paths.init_tok2vec}
169
+ vocab_data = null
170
+ lookups = null
171
+ before_init = null
172
+ after_init = null
173
+
174
+ [initialize.components]
175
+
176
+ [initialize.tokenizer]
custom_functions.py ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import spacy
2
+ from spacy.tokenizer import Tokenizer
3
+
4
+
5
+ @spacy.registry.tokenizers("custom_tokenizer")
6
+ def create_custom_tokenizer():
7
+ def create_tokenizer(nlp):
8
+ infixes = nlp.Defaults.infixes + [
9
+ r"/",
10
+ r"-",
11
+ r",",
12
+ r":",
13
+ ]
14
+ prefixes = nlp.Defaults.prefixes + [
15
+ r"-",
16
+ ]
17
+ prefix_regex = spacy.util.compile_prefix_regex(prefixes)
18
+ infix_regex = spacy.util.compile_infix_regex(infixes)
19
+ return Tokenizer(
20
+ nlp.vocab,
21
+ prefix_search=prefix_regex.search,
22
+ infix_finditer=infix_regex.finditer,
23
+ )
24
+
25
+ return create_tokenizer
en_generic_big-any-py3-none-any.whl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:0edada086e814f896c1560cd23ab2296bb25a4488dedc4bbd0fcdf1ba01eeef2
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+ size 607630799
meta.json ADDED
@@ -0,0 +1,274 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "lang":"en",
3
+ "name":"generic_big",
4
+ "version":"0.0.1",
5
+ "description":"",
6
+ "author":"",
7
+ "email":"",
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+ "url":"",
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+ "license":"",
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+ "spacy_version":">=3.7.5,<3.8.0",
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+ "spacy_git_version":"a6d0fc360",
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+ "vectors":{
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+ "width":300,
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+ "vectors":514157,
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+ "keys":514157,
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+ "name":"en_vectors"
17
+ },
18
+ "labels":{
19
+ "tok2vec":[
20
+
21
+ ],
22
+ "ner":[
23
+ "AGE",
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+ "BRAND",
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+ "CLOCK_SPEED",
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+ "COLOR",
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+ "CORE_COUNT",
28
+ "DECORATION",
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+ "FEATURE",
30
+ "FIT",
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+ "GENDER",
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+ "GRAPHICS",
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+ "GRAPHICS_RAM",
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+ "MATERIAL",
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+ "MEASUREMENT",
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+ "MEASUREMENT_AREA",
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+ "MEM_TYPE",
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+ "MODEL_NUMBER",
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+ "NECKLINE",
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+ "OPERATING_SYSTEM",
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+ "PROCESSOR",
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+ "PROCESSOR_MODEL",
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+ "PRODUCT_SERIES",
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+ "RAM",
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+ "RESOLUTION",
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+ "SCREEN_SIZE",
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+ "SCREEN_TYPE",
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+ "SIZE",
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+ "SLEEVE",
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+ "STORAGE",
51
+ "STORAGE_TYPE",
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+ "TAG",
53
+ "TYPE",
54
+ "ZIP"
55
+ ],
56
+ "textcat":[
57
+ "212",
58
+ "297",
59
+ "328"
60
+ ]
61
+ },
62
+ "pipeline":[
63
+ "tok2vec",
64
+ "ner",
65
+ "textcat"
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+ ],
67
+ "components":[
68
+ "tok2vec",
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+ "ner",
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+ "textcat"
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+ ],
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+ "disabled":[
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+
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+ ],
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+ "performance":{
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+ "ents_f":0.943452381,
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+ "ents_p":0.9469753547,
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+ "ents_r":0.9399555226,
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+ "ents_per_type":{
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+ "r":0.9803278689,
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+ "SIZE":{
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+ "COLOR":{
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+ "PRODUCT_SERIES":{
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+ "MODEL_NUMBER":{
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+ "PROCESSOR":{
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+ "RAM":{
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+ "TAG":{
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+ "NECKLINE":{
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+ "r":1.0,
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+ "SCREEN_SIZE":{
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+ "p":0.9325153374,
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+ "RESOLUTION":{
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+ },
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+ "SCREEN_TYPE":{
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+ "r":0.85,
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+ "f":0.8717948718
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+ },
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+ "GRAPHICS":{
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+ "p":0.9047619048,
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+ "r":0.9172413793,
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+ "f":0.9109589041
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+ },
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+ "MATERIAL":{
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+ },
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+ "GRAPHICS_RAM":{
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+ "f":0.9690721649
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+ },
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+ "MEM_TYPE":{
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+ "r":1.0,
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+ },
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+ "FEATURE":{
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+ },
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+ "MEASUREMENT_AREA":{
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+ "f":0.9666666667
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+ "MEASUREMENT":{
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+ "p":1.0,
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+ "r":0.88,
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+ "f":0.9361702128
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+ },
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+ "ZIP":{
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+ "p":1.0,
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+ "r":1.0,
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+ "f":1.0
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+ },
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+ "CORE_COUNT":{
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+ "p":0.6666666667,
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+ "r":0.4444444444,
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+ "OPERATING_SYSTEM":{
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+ "f":0.9814814815
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+ },
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+ "AGE":{
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+ "p":0.8846153846,
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+ "r":0.92,
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+ "f":0.9019607843
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+ },
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+ "CLOCK_SPEED":{
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+ "r":0.9,
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+ "f":0.9473684211
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+ },
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+ "FIT":{
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+ "r":0.6666666667,
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+ "f":0.8
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+ }
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+ },
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+ "cats_score":1.0,
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+ "cats_score_desc":"macro F",
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+ "cats_micro_p":1.0,
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+ "cats_micro_r":1.0,
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+ "cats_micro_f":1.0,
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+ "cats_macro_p":1.0,
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+ "cats_macro_r":1.0,
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+ "cats_macro_f":1.0,
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+ "cats_macro_auc":1.0,
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+ "cats_f_per_type":{
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+ "212":{
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+ "p":1.0,
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+ "r":1.0,
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+ "f":1.0
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+ },
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+ "297":{
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+ "p":1.0,
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+ "r":1.0,
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+ "f":1.0
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+ },
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+ "328":{
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+ "p":1.0,
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+ "r":1.0,
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+ "f":1.0
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+ }
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+ },
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+ "tok2vec_loss":289.2781015132,
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+ "ner_loss":639.0328665705,
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+ "textcat_loss":0.0007871191
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+ },
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+ "requirements":[
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+
273
+ ]
274
+ }
ner/cfg ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "moves":null,
3
+ "update_with_oracle_cut_size":100,
4
+ "multitasks":[
5
+
6
+ ],
7
+ "min_action_freq":1,
8
+ "learn_tokens":false,
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