Commit
•
23f21b7
1
Parent(s):
7063253
Update spaCy pipeline
Browse files- .gitattributes +5 -0
- README.md +56 -0
- config.cfg +194 -0
- he_ref_ner-any-py3-none-any.whl +3 -0
- meta.json +54 -0
- ner/cfg +13 -0
- ner/model +0 -0
- ner/moves +1 -0
- spacy_function_registry.py +21 -0
- tok2vec/cfg +3 -0
- tok2vec/model +3 -0
- tokenizer +1 -0
- vocab/key2row +3 -0
- vocab/lookups.bin +3 -0
- vocab/strings.json +3 -0
- vocab/vectors +3 -0
- vocab/vectors.cfg +3 -0
.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
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*tfevents* 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
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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he_ref_ner-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
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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/strings.json filter=lfs diff=lfs merge=lfs -text
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vocab/vectors filter=lfs diff=lfs merge=lfs -text
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README.md
ADDED
@@ -0,0 +1,56 @@
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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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- he
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model-index:
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- name: he_ref_ner
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results:
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- task:
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name: NER
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type: token-classification
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metrics:
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- name: NER Precision
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type: precision
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value: 0.8642149929
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- name: NER Recall
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type: recall
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value: 0.7976501305
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- name: NER F Score
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type: f_score
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value: 0.8295994569
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---
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| Feature | Description |
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| --- | --- |
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| **Name** | `he_ref_ner` |
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| **Version** | `1.0.0` |
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| **spaCy** | `>=3.4.1,<3.5.0` |
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| **Default Pipeline** | `tok2vec`, `ner` |
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| **Components** | `tok2vec`, `ner` |
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| **Vectors** | 391957 keys, 391957 unique vectors (50 dimensions) |
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| **Sources** | n/a |
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| **License** | n/a |
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| **Author** | [n/a]() |
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### Label Scheme
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<details>
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<summary>View label scheme (1 labels for 1 components)</summary>
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| Component | Labels |
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| --- | --- |
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| **`ner`** | `מקור` |
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</details>
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### Accuracy
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| Type | Score |
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| --- | --- |
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| `ENTS_F` | 82.96 |
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| `ENTS_P` | 86.42 |
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| `ENTS_R` | 79.77 |
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| `TOK2VEC_LOSS` | 44775.36 |
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| `NER_LOSS` | 4561.19 |
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config.cfg
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@@ -0,0 +1,194 @@
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[paths]
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train = null
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dev = null
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vectors = "vectors/all_text_he_fasttext_model_50"
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init_tok2vec = "models/pretrain_ref_he_50/model8.bin"
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raw_text = null
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input_collection = "merged_output"
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output_collection = "gilyon_input"
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[system]
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gpu_allocator = null
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seed = 61
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min_len = 20
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train_perc = 0.5
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[nlp]
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lang = "he"
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pipeline = ["tok2vec","ner"]
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batch_size = 200
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disabled = []
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before_creation = null
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after_creation = null
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after_pipeline_creation = null
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tokenizer = {"@tokenizers":"inner_punct_tokenizer"}
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[components]
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[components.ner]
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factory = "ner"
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incorrect_spans_key = null
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moves = null
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scorer = {"@scorers":"spacy.ner_scorer.v1"}
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update_with_oracle_cut_size = 100
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[components.ner.model]
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@architectures = "spacy.TransitionBasedParser.v2"
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state_type = "ner"
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extra_state_tokens = false
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hidden_width = 32
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maxout_pieces = 3
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use_upper = true
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nO = null
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[components.ner.model.tok2vec]
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@architectures = "spacy.Tok2VecListener.v1"
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width = ${components.tok2vec.model.encode.width}
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upstream = "*"
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[components.tok2vec]
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factory = "tok2vec"
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[components.tok2vec.model]
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@architectures = "spacy.Tok2Vec.v2"
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[components.tok2vec.model.embed]
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@architectures = "spacy.MultiHashEmbed.v1"
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width = ${components.tok2vec.model.encode.width}
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attrs = ["NORM","PREFIX","SUFFIX","ORTH"]
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rows = [5000,5000,5000,5000]
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include_static_vectors = true
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[components.tok2vec.model.encode]
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@architectures = "spacy.MaxoutWindowEncoder.v2"
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width = 256
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depth = 8
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window_size = 1
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maxout_pieces = 3
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[corpora]
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[corpora.dev]
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@readers = "mongo_reader"
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db_host = "localhost"
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db_port = 27017
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input_collection = ${paths.input_collection}
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output_collection = ${paths.output_collection}
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train_perc = ${system.train_perc}
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corpus_type = "test"
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min_len = ${system.min_len}
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random_state = ${system.seed}
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unique_by_metadata = true
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[corpora.pretrain]
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@readers = "spacy.JsonlCorpus.v1"
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path = ${paths.raw_text}
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min_length = 5
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max_length = 512
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limit = 0
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[corpora.train]
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@readers = "mongo_reader"
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db_host = "localhost"
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db_port = 27017
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input_collection = ${paths.input_collection}
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output_collection = ${paths.output_collection}
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train_perc = ${system.train_perc}
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corpus_type = "train"
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min_len = ${system.min_len}
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random_state = ${system.seed}
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unique_by_metadata = true
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[training]
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dev_corpus = "corpora.dev"
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train_corpus = "corpora.train"
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seed = ${system.seed}
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gpu_allocator = ${system.gpu_allocator}
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dropout = 0.5
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accumulate_gradient = 1
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patience = 1600
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max_epochs = 0
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max_steps = 20000
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eval_frequency = 200
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frozen_components = []
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before_to_disk = null
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annotating_components = []
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[training.batcher]
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@batchers = "spacy.batch_by_words.v1"
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discard_oversize = false
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tolerance = 0.2
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get_length = null
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[training.batcher.size]
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@schedules = "compounding.v1"
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start = 100
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stop = 2000
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compound = 1.001
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t = 0.0
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[training.logger]
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@loggers = "spacy.ConsoleLogger.v1"
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progress_bar = false
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[training.optimizer]
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@optimizers = "Adam.v1"
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beta1 = 0.9
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beta2 = 0.999
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L2_is_weight_decay = true
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L2 = 0.01
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grad_clip = 1.0
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use_averages = false
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eps = 0.00000001
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learn_rate = 0.0007
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[training.score_weights]
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ents_f = 1.0
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ents_p = 0.0
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ents_r = 0.0
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ents_per_type = null
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[pretraining]
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max_epochs = 9
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dropout = 0.5
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n_save_every = null
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n_save_epoch = null
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component = "tok2vec"
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layer = ""
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corpus = "corpora.pretrain"
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[pretraining.batcher]
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@batchers = "spacy.batch_by_words.v1"
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size = 10000
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discard_oversize = false
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tolerance = 0.2
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get_length = null
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[pretraining.objective]
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@architectures = "spacy.PretrainCharacters.v1"
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maxout_pieces = 3
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hidden_size = 50
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n_characters = 4
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[pretraining.optimizer]
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@optimizers = "Adam.v1"
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beta1 = 0.9
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beta2 = 0.999
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L2_is_weight_decay = true
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L2 = 0.01
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grad_clip = 1.0
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use_averages = true
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eps = 0.00000001
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learn_rate = 0.001
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[initialize]
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vectors = ${paths.vectors}
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init_tok2vec = ${paths.init_tok2vec}
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vocab_data = null
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lookups = null
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before_init = null
|
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after_init = null
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[initialize.components]
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[initialize.tokenizer]
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he_ref_ner-any-py3-none-any.whl
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:37ff5191562e86559e0600b2bb83b7ed634454ad283d0da5a4527c0877855e2d
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size 119010387
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meta.json
ADDED
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{
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"lang":"he",
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"name":"ref_ner",
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"version":"1.0.0",
|
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"description":"",
|
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"author":"",
|
7 |
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"email":"",
|
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"url":"",
|
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"license":"",
|
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"spacy_version":">=3.4.1,<3.5.0",
|
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"spacy_git_version":"Unknown",
|
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"vectors":{
|
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"width":50,
|
14 |
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"vectors":391957,
|
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"keys":391957,
|
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"name":"he_pipeline.vectors"
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},
|
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"labels":{
|
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"tok2vec":[
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|
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],
|
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"ner":[
|
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"\u05de\u05e7\u05d5\u05e8"
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]
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},
|
26 |
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"pipeline":[
|
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"tok2vec",
|
28 |
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"ner"
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29 |
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],
|
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"components":[
|
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"tok2vec",
|
32 |
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"ner"
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],
|
34 |
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"disabled":[
|
35 |
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|
36 |
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],
|
37 |
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"performance":{
|
38 |
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"ents_f":0.8295994569,
|
39 |
+
"ents_p":0.8642149929,
|
40 |
+
"ents_r":0.7976501305,
|
41 |
+
"ents_per_type":{
|
42 |
+
"\u05de\u05e7\u05d5\u05e8":{
|
43 |
+
"p":0.8642149929,
|
44 |
+
"r":0.7976501305,
|
45 |
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"f":0.8295994569
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}
|
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},
|
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"tok2vec_loss":447.7536238551,
|
49 |
+
"ner_loss":45.6119190443
|
50 |
+
},
|
51 |
+
"requirements":[
|
52 |
+
|
53 |
+
]
|
54 |
+
}
|
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,
|
9 |
+
"beam_width":1,
|
10 |
+
"beam_density":0.0,
|
11 |
+
"beam_update_prob":0.0,
|
12 |
+
"incorrect_spans_key":null
|
13 |
+
}
|
ner/model
ADDED
Binary file (72.9 kB). View file
|
|
ner/moves
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
��movesٰ{"0":{},"1":{"\u05de\u05e7\u05d5\u05e8":4590},"2":{"\u05de\u05e7\u05d5\u05e8":4590},"3":{"\u05de\u05e7\u05d5\u05e8":4590},"4":{"\u05de\u05e7\u05d5\u05e8":4590,"":1},"5":{"":1}}�cfg��neg_key�
|
spacy_function_registry.py
ADDED
@@ -0,0 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import spacy, re
|
2 |
+
from spacy.tokenizer import Tokenizer
|
3 |
+
|
4 |
+
"""
|
5 |
+
python -m spacy package ref_he packages -c /Users/nss/sefaria/project/sefaria/spacy_function_registry.py -b wheel,sdist -n ref_ner -v 1.0.0
|
6 |
+
python -m spacy huggingface-hub push packages/en_torah_ner-1.0.0/dist/en_torah_ner-1.0.0-py3-none-any.whl -o Sefaria
|
7 |
+
"""
|
8 |
+
|
9 |
+
@spacy.registry.tokenizers("inner_punct_tokenizer")
|
10 |
+
def inner_punct_tokenizer_factory():
|
11 |
+
def inner_punct_tokenizer(nlp):
|
12 |
+
# infix_re = spacy.util.compile_infix_regex(nlp.Defaults.infixes)
|
13 |
+
infix_re = re.compile(r'''[.,?!:;…‘’`“”"'~–\-/()<>]''')
|
14 |
+
prefix_re = spacy.util.compile_prefix_regex(nlp.Defaults.prefixes)
|
15 |
+
suffix_re = spacy.util.compile_suffix_regex(nlp.Defaults.suffixes)
|
16 |
+
|
17 |
+
return Tokenizer(nlp.vocab, prefix_search=prefix_re.search,
|
18 |
+
suffix_search=suffix_re.search,
|
19 |
+
infix_finditer=infix_re.finditer,
|
20 |
+
token_match=None)
|
21 |
+
return inner_punct_tokenizer
|
tok2vec/cfg
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
|
3 |
+
}
|
tok2vec/model
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5c162006fbebb7915acb4a6dcd6a1c007dc005c4f8f9f3210a28a028d643a907
|
3 |
+
size 43394001
|
tokenizer
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
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vocab/key2row
ADDED
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1 |
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version https://git-lfs.github.com/spec/v1
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2 |
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oid sha256:de251682140a84dbf265a9a3731a086b5395df835cfb17a6e6c0b51916e47a50
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3 |
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size 5355883
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vocab/lookups.bin
ADDED
@@ -0,0 +1,3 @@
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|
1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:76be8b528d0075f7aae98d6fa57a6d3c83ae480a8469e668d7b0af968995ac71
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3 |
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size 1
|
vocab/strings.json
ADDED
@@ -0,0 +1,3 @@
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1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:ccaaee428b51c1335316f1c1aac38ff55e33f79d3ac431eb31a1639c68fffd4d
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3 |
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size 16101360
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vocab/vectors
ADDED
@@ -0,0 +1,3 @@
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1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
+
oid sha256:4ca8adc620b9d1317c97aba3a062777eff9200cc64d2c88e1785a20004414b82
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3 |
+
size 78391528
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vocab/vectors.cfg
ADDED
@@ -0,0 +1,3 @@
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1 |
+
{
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2 |
+
"mode":"default"
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3 |
+
}
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