Madhana commited on
Commit
a714855
1 Parent(s): bb56821

Update spaCy pipeline

Browse files
.gitattributes CHANGED
@@ -32,3 +32,5 @@ 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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+ en_pipeline-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
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+ transformer/model filter=lfs diff=lfs merge=lfs -text
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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+ - en
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+ model-index:
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+ - name: en_pipeline
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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: 0.9970588235
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+ - name: NER Recall
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+ type: recall
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+ value: 0.9985272459
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+ - name: NER F Score
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+ type: f_score
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+ value: 0.9977924945
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+ ---
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+ | Feature | Description |
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+ | --- | --- |
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+ | **Name** | `en_pipeline` |
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+ | **Version** | `0.0.0` |
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+ | **spaCy** | `>=3.5.1,<3.6.0` |
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+ | **Default Pipeline** | `transformer`, `ner` |
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+ | **Components** | `transformer`, `ner` |
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+ | **Vectors** | 0 keys, 0 unique vectors (0 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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+
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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 1 components)</summary>
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+
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+ | Component | Labels |
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+ | --- | --- |
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+ | **`ner`** | `BUILDING`, `CITY`, `NAME`, `NEIGHBORHOOD`, `PHONE NUMBER`, `STREET` |
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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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+ | `ENTS_F` | 99.78 |
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+ | `ENTS_P` | 99.71 |
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+ | `ENTS_R` | 99.85 |
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+ | `TRANSFORMER_LOSS` | 21301.86 |
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+ | `NER_LOSS` | 25081.95 |
config.cfg ADDED
@@ -0,0 +1,151 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ [paths]
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+ train = "./training_data.spacy"
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+ dev = "./training_data.spacy"
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+ vectors = null
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+ init_tok2vec = null
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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 = ["transformer","ner"]
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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.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-transformers.TransformerListener.v1"
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+ grad_factor = 1.0
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+ pooling = {"@layers":"reduce_mean.v1"}
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+ upstream = "*"
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+
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+ [components.transformer]
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+ factory = "transformer"
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+ max_batch_items = 4096
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+ set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
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+
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+ [components.transformer.model]
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+ @architectures = "spacy-transformers.TransformerModel.v3"
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+ name = "roberta-base"
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+ mixed_precision = false
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+
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+ [components.transformer.model.get_spans]
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+ @span_getters = "spacy-transformers.strided_spans.v1"
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+ window = 128
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+ stride = 96
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+
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+ [components.transformer.model.grad_scaler_config]
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+
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+ [components.transformer.model.tokenizer_config]
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+ use_fast = true
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+
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+ [components.transformer.model.transformer_config]
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+
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+ [corpora]
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+
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+ [corpora.dev]
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+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.dev}
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+ max_length = 0
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+ gold_preproc = false
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+ limit = 0
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+ augmenter = null
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+
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+ [corpora.train]
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+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.train}
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+ max_length = 0
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+ gold_preproc = false
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+ limit = 0
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+ augmenter = null
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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
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+ eval_frequency = 200
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+ frozen_components = []
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+ annotating_components = []
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+ before_to_disk = null
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+ before_update = null
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+
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+ [training.batcher]
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+ @batchers = "spacy.batch_by_padded.v1"
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+ discard_oversize = true
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+ size = 2000
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+ buffer = 256
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+ get_length = null
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+
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+ [training.logger]
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+ @loggers = "spacy.WandbLogger.v3"
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+ project_name = "Named_Entity_Recognition"
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+ remove_config_values = ["paths.train","paths.dev","corpora.train.path","corpora.dev.path"]
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+ run_name = "spacy-flood-ner-v01"
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+ model_log_interval = null
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+ log_dataset_dir = null
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+ entity = null
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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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+
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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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+
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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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+
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+ [pretraining]
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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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+
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+ [initialize.components]
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+
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+ [initialize.tokenizer]
en_pipeline-any-py3-none-any.whl ADDED
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meta.json ADDED
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+ {
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+ "lang":"en",
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+ "name":"pipeline",
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+ "version":"0.0.0",
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+ "description":"",
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+ "author":"",
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+ "email":"",
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+ "url":"",
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+ "license":"",
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+ "spacy_version":">=3.5.1,<3.6.0",
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+ "spacy_git_version":"Unknown",
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+ "vectors":{
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+ "width":0,
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+ "name":null
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+ },
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+ "labels":{
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+ "transformer":[
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+
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+ ],
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+ "ner":[
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+ "BUILDING",
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+ "CITY",
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+ "NAME",
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+ "NEIGHBORHOOD",
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+ "PHONE NUMBER",
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+ "STREET"
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+ ]
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+ },
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+ "pipeline":[
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+ "transformer",
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+ "ner"
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+ ],
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+ "components":[
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+ "transformer",
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+ "ner"
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+ ],
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+ "disabled":[
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+ ],
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+ "performance":{
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+ "ents_f":0.9977924945,
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+ "ents_p":0.9970588235,
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+ "ents_r":0.9985272459,
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+ "ents_per_type":{
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+ "r":1.0,
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+ "STREET":{
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+ "r":0.9952380952,
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+ },
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+ "BUILDING":{
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+ "p":0.9861111111,
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+ "r":1.0,
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+ "f":0.993006993
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+ },
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+ "CITY":{
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+ },
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+ "NAME":{
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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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+ "PHONE NUMBER":{
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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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+ "transformer_loss":213.0186185096,
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+ "ner_loss":250.8195002671
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+ },
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+ "requirements":[
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+ "spacy-transformers>=1.2.3,<1.3.0"
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+ ]
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+ }
ner/cfg ADDED
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+ {
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+ "moves":null,
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+ "update_with_oracle_cut_size":100,
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+ "multitasks":[
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+
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+ ],
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+ "min_action_freq":1,
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+ "learn_tokens":false,
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+ "beam_width":1,
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+ "beam_density":0.0,
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+ "beam_update_prob":0.0,
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+ "incorrect_spans_key":null
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+ }
ner/model ADDED
Binary file (239 kB). View file
 
ner/moves ADDED
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tokenizer ADDED
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1612
+ "outskirts",
1613
+ "ov.",
1614
+ "o\u2019clock",
1615
+ "o\u2019s",
1616
+ "p",
1617
+ "p.",
1618
+ "p.m",
1619
+ "p.m.",
1620
+ "pa",
1621
+ "pa.",
1622
+ "pak",
1623
+ "pal",
1624
+ "panchkula",
1625
+ "parents",
1626
+ "park",
1627
+ "parul",
1628
+ "patel",
1629
+ "pathai",
1630
+ "ped",
1631
+ "periyar",
1632
+ "perungalathur",
1633
+ "pet",
1634
+ "ph",
1635
+ "ph.d.",
1636
+ "phone number",
1637
+ "ple",
1638
+ "please",
1639
+ "pls",
1640
+ "pm",
1641
+ "poes",
1642
+ "porur",
1643
+ "pr.",
1644
+ "pradeep",
1645
+ "prakash",
1646
+ "prasad",
1647
+ "prashant",
1648
+ "praveen",
1649
+ "preethi",
1650
+ "preeti",
1651
+ "priya",
1652
+ "priyanka",
1653
+ "prof",
1654
+ "prof.",
1655
+ "pt.",
1656
+ "pta",
1657
+ "pune",
1658
+ "pur",
1659
+ "purasawalkam",
1660
+ "q",
1661
+ "q.",
1662
+ "r",
1663
+ "r.",
1664
+ "race",
1665
+ "radhakrishnan",
1666
+ "rahul",
1667
+ "rai",
1668
+ "rains",
1669
+ "raj",
1670
+ "raja",
1671
+ "rajaji",
1672
+ "rajan",
1673
+ "rajesh",
1674
+ "rajeshwari",
1675
+ "ral",
1676
+ "ram",
1677
+ "raman",
1678
+ "ramaswamy",
1679
+ "ramesh",
1680
+ "ramya",
1681
+ "ran",
1682
+ "rana",
1683
+ "ranganathan",
1684
+ "ravi",
1685
+ "re",
1686
+ "re.",
1687
+ "recent",
1688
+ "reddy",
1689
+ "ree",
1690
+ "reena",
1691
+ "relatives",
1692
+ "rep",
1693
+ "rep.",
1694
+ "rescue",
1695
+ "rescuing",
1696
+ "residence",
1697
+ "rev",
1698
+ "rev.",
1699
+ "rga",
1700
+ "rim",
1701
+ "ris",
1702
+ "rising",
1703
+ "riz",
1704
+ "rk.",
1705
+ "rma",
1706
+ "road",
1707
+ "rof",
1708
+ "rohit",
1709
+ "roof",
1710
+ "ros",
1711
+ "roy",
1712
+ "royapettah",
1713
+ "rp.",
1714
+ "rs.",
1715
+ "rse",
1716
+ "rts",
1717
+ "rul",
1718
+ "rur",
1719
+ "rya",
1720
+ "s",
1721
+ "s's",
1722
+ "s.",
1723
+ "s.c.",
1724
+ "sad",
1725
+ "sai",
1726
+ "salai",
1727
+ "salem",
1728
+ "salt",
1729
+ "san",
1730
+ "sanjay",
1731
+ "saravanan",
1732
+ "sardar",
1733
+ "sarika",
1734
+ "searchandrescue",
1735
+ "sed",
1736
+ "sen",
1737
+ "sen.",
1738
+ "send",
1739
+ "senthil",
1740
+ "sep",
1741
+ "sep.",
1742
+ "sept",
1743
+ "sept.",
1744
+ "sh.",
1745
+ "sha",
1746
+ "shah",
1747
+ "shall",
1748
+ "shankar",
1749
+ "shanmuga",
1750
+ "sharma",
1751
+ "she",
1752
+ "she's",
1753
+ "she\u2019s",
1754
+ "shi",
1755
+ "shiva",
1756
+ "should",
1757
+ "shyama",
1758
+ "sin",
1759
+ "singanallur",
1760
+ "singh",
1761
+ "sion",
1762
+ "sister",
1763
+ "smith",
1764
+ "somethin",
1765
+ "somethin'",
1766
+ "something",
1767
+ "somethin\u2019",
1768
+ "son",
1769
+ "south",
1770
+ "space",
1771
+ "srinivasan",
1772
+ "srs",
1773
+ "ss.",
1774
+ "st",
1775
+ "st.",
1776
+ "stranded",
1777
+ "street",
1778
+ "stuck",
1779
+ "sundaram",
1780
+ "sunita",
1781
+ "suresh",
1782
+ "sushma",
1783
+ "swami",
1784
+ "swamy",
1785
+ "s\u2019s",
1786
+ "t",
1787
+ "t's",
1788
+ "t.",
1789
+ "ta",
1790
+ "tah",
1791
+ "tay",
1792
+ "td.",
1793
+ "tel",
1794
+ "tenn",
1795
+ "tenn.",
1796
+ "ter",
1797
+ "tha",
1798
+ "thadagam",
1799
+ "that",
1800
+ "that's",
1801
+ "that\u2019s",
1802
+ "the",
1803
+ "their",
1804
+ "them",
1805
+ "there",
1806
+ "there's",
1807
+ "there\u2019s",
1808
+ "these",
1809
+ "they",
1810
+ "thi",
1811
+ "this",
1812
+ "this's",
1813
+ "this\u2019s",
1814
+ "those",
1815
+ "thunderstorm",
1816
+ "thy",
1817
+ "tilak",
1818
+ "tly",
1819
+ "to",
1820
+ "tondiarpet",
1821
+ "tornado",
1822
+ "trapped",
1823
+ "trichy",
1824
+ "tulsi",
1825
+ "tuncay",
1826
+ "t\u2019s",
1827
+ "u",
1828
+ "u.",
1829
+ "uck",
1830
+ "udh",
1831
+ "uff",
1832
+ "ug.",
1833
+ "uga",
1834
+ "ul.",
1835
+ "ula",
1836
+ "uld",
1837
+ "un.",
1838
+ "uncle",
1839
+ "und",
1840
+ "under",
1841
+ "une",
1842
+ "unt",
1843
+ "urgent",
1844
+ "urgently",
1845
+ "us",
1846
+ "use",
1847
+ "ust",
1848
+ "uth",
1849
+ "v",
1850
+ "v.",
1851
+ "v.s",
1852
+ "v.s.",
1853
+ "v.v",
1854
+ "v_v",
1855
+ "va",
1856
+ "va.",
1857
+ "vadapalani",
1858
+ "vasudev",
1859
+ "ve",
1860
+ "velachery",
1861
+ "veli",
1862
+ "vellore",
1863
+ "venkatadri",
1864
+ "venkataraman",
1865
+ "venkatesh",
1866
+ "venkatraman",
1867
+ "venugopal",
1868
+ "vepery",
1869
+ "verma",
1870
+ "ves",
1871
+ "vidya",
1872
+ "vignesh",
1873
+ "vijay",
1874
+ "villupuram",
1875
+ "vimala",
1876
+ "vin",
1877
+ "vishnu",
1878
+ "vivekananda",
1879
+ "vs",
1880
+ "vs.",
1881
+ "vya",
1882
+ "w",
1883
+ "w's",
1884
+ "w.",
1885
+ "w/o",
1886
+ "was",
1887
+ "wash",
1888
+ "wash.",
1889
+ "we",
1890
+ "were",
1891
+ "what",
1892
+ "what's",
1893
+ "what\u2019s",
1894
+ "when",
1895
+ "when's",
1896
+ "when\u2019s",
1897
+ "where",
1898
+ "where's",
1899
+ "where\u2019s",
1900
+ "who",
1901
+ "who's",
1902
+ "who\u2019s",
1903
+ "why",
1904
+ "why's",
1905
+ "why\u2019s",
1906
+ "will",
1907
+ "wind",
1908
+ "wis",
1909
+ "wis.",
1910
+ "without",
1911
+ "wo",
1912
+ "would",
1913
+ "w\u2019s",
1914
+ "x",
1915
+ "x'",
1916
+ "x'x",
1917
+ "x'xxxx",
1918
+ "x.",
1919
+ "x.X",
1920
+ "x.d",
1921
+ "x.x",
1922
+ "x.x.",
1923
+ "x/x",
1924
+ "xD",
1925
+ "xDD",
1926
+ "xX",
1927
+ "xXX",
1928
+ "x_X",
1929
+ "x_d",
1930
+ "x_x",
1931
+ "xd",
1932
+ "xdd",
1933
+ "xx",
1934
+ "xx'",
1935
+ "xx'x",
1936
+ "xx'xx",
1937
+ "xx.",
1938
+ "xxd",
1939
+ "xxx",
1940
+ "xxx'x",
1941
+ "xxx/xx",
1942
+ "xxxx",
1943
+ "xxxx'",
1944
+ "xxxx'x",
1945
+ "xxxx\u2019",
1946
+ "xxxx\u2019x",
1947
+ "xxx\u2019x",
1948
+ "xx\u2019",
1949
+ "xx\u2019x",
1950
+ "xx\u2019xx",
1951
+ "x\u2019",
1952
+ "x\u2019x",
1953
+ "x\u2019xxxx",
1954
+ "x\ufe35x",
1955
+ "y",
1956
+ "y'",
1957
+ "y's",
1958
+ "y.",
1959
+ "yam",
1960
+ "yan",
1961
+ "yar",
1962
+ "you",
1963
+ "y\u2019",
1964
+ "y\u2019s",
1965
+ "z",
1966
+ "z.",
1967
+ "|",
1968
+ "}",
1969
+ "\u00a0",
1970
+ "\u00ac",
1971
+ "\u00ac_\u00ac",
1972
+ "\u00af",
1973
+ "\u00af\\(x)/\u00af",
1974
+ "\u00af\\(\u30c4)/\u00af",
1975
+ "\u00b0",
1976
+ "\u00b0C.",
1977
+ "\u00b0F.",
1978
+ "\u00b0K.",
1979
+ "\u00b0X.",
1980
+ "\u00b0c.",
1981
+ "\u00b0f.",
1982
+ "\u00b0k.",
1983
+ "\u00b0x.",
1984
+ "\u00e4",
1985
+ "\u00e4.",
1986
+ "\u00f6",
1987
+ "\u00f6.",
1988
+ "\u00fc",
1989
+ "\u00fc.",
1990
+ "\u0ca0",
1991
+ "\u0ca0_\u0ca0",
1992
+ "\u0ca0\ufe35\u0ca0",
1993
+ "\u2014",
1994
+ "\u2018",
1995
+ "\u2018S",
1996
+ "\u2018X",
1997
+ "\u2018s",
1998
+ "\u2018x",
1999
+ "\u2019",
2000
+ "\u2019-(",
2001
+ "\u2019-)",
2002
+ "\u2019Cause",
2003
+ "\u2019Cos",
2004
+ "\u2019Coz",
2005
+ "\u2019Cuz",
2006
+ "\u2019S",
2007
+ "\u2019X",
2008
+ "\u2019Xxx",
2009
+ "\u2019Xxxxx",
2010
+ "\u2019am",
2011
+ "\u2019bout",
2012
+ "\u2019cause",
2013
+ "\u2019cos",
2014
+ "\u2019coz",
2015
+ "\u2019cuz",
2016
+ "\u2019d",
2017
+ "\u2019em",
2018
+ "\u2019ll",
2019
+ "\u2019m",
2020
+ "\u2019nuff",
2021
+ "\u2019re",
2022
+ "\u2019s",
2023
+ "\u2019ve",
2024
+ "\u2019x",
2025
+ "\u2019xx",
2026
+ "\u2019xxx",
2027
+ "\u2019xxxx",
2028
+ "\u2019y",
2029
+ "\u2019\u2019",
2030
+ "\u2501",
2031
+ "\u253b",
2032
+ "\u253b\u2501\u253b",
2033
+ "\u256f",
2034
+ "\u25a1",
2035
+ "\ufe35",
2036
+ "\uff09"
2037
+ ]
vocab/vectors ADDED
Binary file (128 Bytes). View file
 
vocab/vectors.cfg ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ {
2
+ "mode":"default"
3
+ }