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Commit
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Update spaCy pipeline

Browse files
.gitattributes CHANGED
@@ -25,3 +25,8 @@ saved_model/**/* 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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+ model filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,85 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ - en
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+ license: mit
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+ model-index:
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+ - name: en_healthsea
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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: 0.0
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+ - name: NER Recall
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+ type: recall
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+ value: 0.0
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+ - name: NER F Score
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+ type: f_score
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+ value: 0.0
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+ - task:
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+ name: SENTER
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+ type: token-classification
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+ metrics:
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+ - name: SENTER Precision
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+ type: precision
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+ value: 1.0
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+ - name: SENTER Recall
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+ type: recall
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+ value: 1.0
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+ - name: SENTER F Score
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+ type: f_score
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+ value: 1.0
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+ ---
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+ Healthsea pipeline for analyzing reviews to supplement products
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+
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+ | Feature | Description |
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+ | --- | --- |
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+ | **Name** | `en_healthsea` |
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+ | **Version** | `0.0.1` |
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+ | **spaCy** | `>=3.2.0,<3.3.0` |
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+ | **Default Pipeline** | `sentencizer`, `tok2vec`, `ner`, `benepar`, `segmentation`, `clausecat`, `aggregation` |
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+ | **Components** | `sentencizer`, `tok2vec`, `ner`, `benepar`, `segmentation`, `clausecat`, `aggregation` |
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+ | **Vectors** | 684830 keys, 684830 unique vectors (300 dimensions) |
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+ | **Sources** | n/a |
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+ | **License** | `MIT` |
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+ | **Author** | [Explosion](explosion.ai) |
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+
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+ ### Label Scheme
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+
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+ <details>
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+
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+ <summary>View label scheme (6 labels for 2 components)</summary>
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+
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+ | Component | Labels |
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+ | --- | --- |
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+ | **`ner`** | `BENEFIT`, `CONDITION` |
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+ | **`clausecat`** | `POSITIVE`, `NEUTRAL`, `NEGATIVE`, `ANAMNESIS` |
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+
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+ </details>
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+
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+ ### Accuracy
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+
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+ | Type | Score |
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+ | --- | --- |
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+ | `SENTS_F` | 100.00 |
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+ | `SENTS_P` | 100.00 |
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+ | `SENTS_R` | 100.00 |
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+ | `ENTS_F` | 0.00 |
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+ | `ENTS_P` | 0.00 |
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+ | `ENTS_R` | 0.00 |
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+ | `ENTS_PER_TYPE` | 0.00 |
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+ | `CATS_SCORE` | 74.87 |
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+ | `CATS_MICRO_P` | 82.39 |
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+ | `CATS_MICRO_R` | 80.93 |
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+ | `CATS_MICRO_F` | 81.66 |
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+ | `CATS_MACRO_P` | 78.43 |
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+ | `CATS_MACRO_R` | 72.16 |
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+ | `CATS_MACRO_F` | 74.87 |
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+ | `CATS_MACRO_AUC` | 92.78 |
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+ | `CATS_MACRO_AUC_PER_TYPE` | 0.00 |
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+ | `CLAUSECAT_LOSS` | 339.11 |
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+ {
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+ "labels":[
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+ "POSITIVE",
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+ "NEUTRAL",
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+ "NEGATIVE",
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+ "ANAMNESIS"
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+ ],
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+ "threshold":0.5
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+ }
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+ [paths]
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+ train = "assets/clausecat/train.spacy"
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+ dev = "assets/clausecat/dev.spacy"
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+ vectors = ${paths.ner_model}
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+ init_tok2vec = "assets/pretrained_weights_clausecat.bin"
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+ ner_model = "training/ner/config_tok2vec/model-best"
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+
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+ [system]
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+ gpu_allocator = "pytorch"
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+ seed = 0
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+
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+ [nlp]
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+ lang = "en"
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+ pipeline = ["sentencizer","tok2vec","ner","benepar","segmentation","clausecat","aggregation"]
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+ batch_size = 128
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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":"spacy.Tokenizer.v1"}
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+
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+ [components]
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+
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+ [components.aggregation]
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+ factory = "healthsea.aggregation.v1"
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+
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+ [components.benepar]
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+ factory = "benepar"
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+ disable_tagger = false
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+ model = "benepar_en3"
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+ subbatch_max_tokens = 500
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+
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+ [components.clausecat]
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+ factory = "healthsea.clausecat.v1"
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+ threshold = 0.5
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+
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+ [components.clausecat.model]
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+ @architectures = "healthsea.clausecat_model.v1"
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+ blinder = {"@layers":"healthsea.blinder.v1"}
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+
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+ [components.clausecat.model.textcat]
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+ @architectures = "spacy.TextCatEnsemble.v2"
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+ nO = null
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+
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+ [components.clausecat.model.textcat.linear_model]
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+ @architectures = "spacy.TextCatBOW.v2"
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+ exclusive_classes = true
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+ ngram_size = 1
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+ no_output_layer = false
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+ nO = null
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+ [components.clausecat.model.textcat.tok2vec]
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+ @architectures = "spacy.Tok2Vec.v2"
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+
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+ [components.clausecat.model.textcat.tok2vec.embed]
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+ @architectures = "spacy.MultiHashEmbed.v2"
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+ width = 64
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+ rows = [2000,2000,1000,1000,1000,1000]
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+ attrs = ["ORTH","LOWER","PREFIX","SUFFIX","SHAPE","ID"]
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+ include_static_vectors = false
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+
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+ [components.clausecat.model.textcat.tok2vec.encode]
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+ @architectures = "spacy.MaxoutWindowEncoder.v2"
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+ width = ${components.clausecat.model.textcat.tok2vec.embed.width}
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+ window_size = 1
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+ maxout_pieces = 3
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+ depth = 2
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+
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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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+
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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 = 64
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+ maxout_pieces = 2
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+ use_upper = false
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+ nO = null
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+
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+ [components.ner.model.tok2vec]
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+ @architectures = "spacy.Tok2VecListener.v1"
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+ width = 256
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+ upstream = "tok2vec"
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+
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+ [components.segmentation]
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+ factory = "healthsea.segmentation.v1"
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+
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+ [components.sentencizer]
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+ factory = "sentencizer"
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+ overwrite = false
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+ punct_chars = null
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+ scorer = {"@scorers":"spacy.senter_scorer.v1"}
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+
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+ [components.tok2vec]
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+ factory = "tok2vec"
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+
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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.v2"
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+ width = 256
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+ attrs = ["ORTH","SHAPE"]
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+ rows = [5000,2500]
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+ include_static_vectors = true
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+
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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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+
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+ [corpora]
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+
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+ [corpora.dev]
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+ @readers = "healthsea.clausecat_reader.v1"
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+ path = ${paths.dev}
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+
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+ [corpora.train]
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+ @readers = "healthsea.clausecat_reader.v1"
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+ path = ${paths.train}
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+
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+ [training]
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+ accumulate_gradient = 3
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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 = 0.1
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+ patience = 1600
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+ max_epochs = 0
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+ max_steps = 20000
139
+ eval_frequency = 200
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+ frozen_components = ["tok2vec","ner"]
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+ annotating_components = []
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+ before_to_disk = null
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+
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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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+
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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 = 1000
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+ compound = 1.001
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+ t = 0.0
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+
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+ [training.logger]
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+ @loggers = "spacy.ConsoleLogger.v1"
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+ progress_bar = true
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+
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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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+ [training.optimizer.learn_rate]
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+ @schedules = "warmup_linear.v1"
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+ warmup_steps = 250
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+ total_steps = 20000
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+ initial_rate = 0.00005
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+ [training.score_weights]
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+ sents_f = null
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+ sents_p = null
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+ sents_r = null
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+ ents_f = null
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+ ents_r = null
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+ ents_per_type = null
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+ cats_score = 1.0
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+ cats_micro_p = null
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+ cats_micro_r = null
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+ cats_micro_f = null
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+ cats_macro_p = null
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+ cats_macro_r = null
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+ cats_macro_auc = null
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+ cats_f_per_type = null
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+ cats_macro_auc_per_type = null
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+
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+ [pretraining]
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+ max_epochs = 100
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+ dropout = 0.2
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+ n_save_every = null
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+ n_save_epoch = 1
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+ component = "clausecat"
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+ layer = "tok2vec"
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+ corpus = "corpora.pretrain"
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+ [pretraining.batcher]
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+ size = 10000
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+ [pretraining.objective]
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+ @architectures = "spacy.PretrainVectors.v1"
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+ maxout_pieces = 3
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+ hidden_size = 300
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+ loss = "cosine"
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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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+
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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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+
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+ [initialize.tokenizer]
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+ {
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+ "lang":"en",
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+ "name":"healthsea",
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+ "version":"0.0.1",
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+ "description":"Healthsea pipeline for analyzing reviews to supplement products",
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+ "author":"Explosion",
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+ "email":"edward@explosion.ai",
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+ "url":"explosion.ai",
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+ "license":"MIT",
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+ "spacy_version":">=3.2.0,<3.3.0",
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+ "ner":[
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+ "BENEFIT",
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+ "CONDITION"
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+ ],
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+ "clausecat":[
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+ "POSITIVE",
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+ "NEUTRAL",
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+ "NEGATIVE",
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+ "ANAMNESIS"
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+ "pipeline":[
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+ "sentencizer",
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+ "tok2vec",
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+ "ner",
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+ "clausecat",
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+ "benepar>=0.2.0,<0.3.0"
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+ }
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+ "\ud805\udc4b",
70
+ "\ua9c8",
71
+ "\ud805\uddcf",
72
+ "\ud804\ude39",
73
+ "\ud805\uddcc",
74
+ "\ua8cf",
75
+ "\ud805\uddd3",
76
+ "\ud806\ude9b",
77
+ "\ud81a\ude6e",
78
+ "\ud804\udcc0",
79
+ "\ud805\uddca",
80
+ "\u2048",
81
+ "\ud804\udc47",
82
+ "\u1aab",
83
+ "\ud804\udd43",
84
+ "\ud807\udc41",
85
+ "!",
86
+ "\uff1f",
87
+ "\u1809",
88
+ "\ud805\udf3c",
89
+ "\ud805\uddd2",
90
+ "\ua6f7",
91
+ "\u06d4",
92
+ "\ud804\udea9",
93
+ "\ud81a\udf44",
94
+ "\ua60e",
95
+ "\u061f",
96
+ "\u104b",
97
+ "\u1368",
98
+ "\u2e2e",
99
+ "\ua6f3",
100
+ "?",
101
+ "\u1945",
102
+ "\ufe57",
103
+ "\ud81a\udf37",
104
+ "\u0965",
105
+ "\ud81a\udef5",
106
+ "\u203d",
107
+ "\ud805\uddce",
108
+ "\ud805\uddd6",
109
+ ".",
110
+ "\ud804\uddcd",
111
+ "\u0702",
112
+ "\ud805\udf3d",
113
+ "\ua60f",
114
+ "\ud805\uddd4",
115
+ "\ua92f",
116
+ "\ud804\ude38",
117
+ "\uaa5d",
118
+ "\ud805\uddcb",
119
+ "\ud806\ude43",
120
+ "\u0700",
121
+ "\u1367",
122
+ "\u1362",
123
+ "\ud804\udd41",
124
+ "\ud805\ude42",
125
+ "\u1aa9",
126
+ "\u07f9",
127
+ "\ud805\uddd0",
128
+ "\u1735",
129
+ "\uff0e",
130
+ "\u203c"
131
+ ],
132
+ "overwrite":false
133
+ }
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 sha256:4d06bb1fab516d8a22392d96802edadbdfae4edbfb6ae622ea587d696f77618a
3
+ size 29276330
tokenizer ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
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