Update spaCy pipeline
Browse files- .gitattributes +2 -0
- README.md +57 -0
- config.cfg +149 -0
- es_neg_uncert_ehr_ner-any-py3-none-any.whl +3 -0
- meta.json +72 -0
- ner/cfg +13 -0
- ner/model +0 -0
- ner/moves +1 -0
- tokenizer +3 -0
- transformer/cfg +3 -0
- transformer/model +3 -0
- vocab/key2row +1 -0
- vocab/lookups.bin +3 -0
- vocab/strings.json +0 -0
- vocab/vectors +0 -0
- vocab/vectors.cfg +3 -0
.gitattributes
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@@ -33,3 +33,5 @@ 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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es_neg_uncert_ehr_ner-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
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README.md
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---
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tags:
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- spacy
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- token-classification
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language:
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- es
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license: mit
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model-index:
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- name: es_neg_uncert_ehr_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: 0.8964797136
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- name: NER Recall
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type: recall
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value: 0.8997005988
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- name: NER F Score
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type: f_score
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value: 0.8980872684
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---
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| Feature | Description |
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| --- | --- |
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| **Name** | `es_neg_uncert_ehr_ner` |
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| **Version** | `0.0.0` |
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| **spaCy** | `>=3.7.2,<3.8.0` |
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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** | `mit` |
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| **Author** | [Álvaro García Barragán](Alvaro8gb/NegUncertaintyNER) |
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### Label Scheme
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<details>
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<summary>View label scheme (4 labels for 1 components)</summary>
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| Component | Labels |
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| --- | --- |
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| **`ner`** | `NEG`, `NSCO`, `UNC`, `USCO` |
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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` | 89.81 |
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| `ENTS_P` | 89.65 |
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| `ENTS_R` | 89.97 |
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| `TRANSFORMER_LOSS` | 34598.52 |
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| `NER_LOSS` | 35036.89 |
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config.cfg
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[paths]
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train = ""
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dev = ""
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vectors = null
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init_tok2vec = null
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[system]
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gpu_allocator = "pytorch"
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seed = 0
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[nlp]
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lang = "es"
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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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vectors = {"@vectors":"spacy.Vectors.v1"}
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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 = 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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[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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[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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[components.transformer.model]
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@architectures = "spacy-transformers.TransformerModel.v3"
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name = "bert-base-multilingual-cased"
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mixed_precision = false
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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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[components.transformer.model.grad_scaler_config]
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[components.transformer.model.tokenizer_config]
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use_fast = true
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[components.transformer.model.transformer_config]
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[corpora]
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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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[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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[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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[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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[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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[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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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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[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.components.ner]
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[initialize.tokenizer]
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es_neg_uncert_ehr_ner-any-py3-none-any.whl
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version https://git-lfs.github.com/spec/v1
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oid sha256:f1fdf6b3154a16ac1f5bc482dabc9d3824c59632135c19d41b32e718c298e1ad
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size 662043245
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meta.json
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{
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"lang":"es",
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"name":"neg_uncert_ehr_ner",
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"version":"0.0.0",
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"description":"",
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"author":"\u00c1lvaro Garc\u00eda Barrag\u00e1n",
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"email":"alvaro8gb@gmail.com",
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"url":"Alvaro8gb/NegUncertaintyNER",
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"license":"mit",
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"spacy_version":">=3.7.2,<3.8.0",
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"spacy_git_version":"a89eae928",
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"vectors":{
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"width":0,
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"vectors":0,
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"keys":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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"ner":[
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"NEG",
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"NSCO",
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"UNC",
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"USCO"
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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":0.8980872684,
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"ents_p":0.8964797136,
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"ents_r":0.8997005988,
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"ents_per_type":{
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"NEG":{
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"p":0.9592857143,
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"r":0.9760174419,
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"f":0.9675792507
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},
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"NSCO":{
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"p":0.8782608696,
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"r":0.8845541401,
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"f":0.8813962713
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},
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"UNC":{
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"p":0.8703170029,
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"r":0.8603988604,
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"f":0.8653295129
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},
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"USCO":{
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"p":0.7323529412,
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"r":0.6974789916,
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"f":0.7144906743
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}
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},
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"transformer_loss":345.985210621,
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"ner_loss":350.368920027
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},
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"requirements":[
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"spacy-transformers>=1.3.5,<1.4.0"
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]
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}
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ner/cfg
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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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"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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}
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ner/model
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Binary file (226 kB). View file
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ner/moves
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��moves��{"0":{},"1":{"NSCO":28659,"USCO":10967,"NEG":8636,"UNC":3071},"2":{"NSCO":28659,"USCO":10967,"NEG":8636,"UNC":3071},"3":{"NSCO":28659,"USCO":10967,"NEG":8636,"UNC":3071},"4":{"NSCO":28659,"USCO":10967,"NEG":8636,"UNC":3071,"":1},"5":{"":1}}�cfg��neg_key�
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tokenizer
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transformer/cfg
ADDED
@@ -0,0 +1,3 @@
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|
1 |
+
{
|
2 |
+
"max_batch_items":4096
|
3 |
+
}
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transformer/model
ADDED
@@ -0,0 +1,3 @@
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|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
+
oid sha256:9f2c0b0673ddfd765711736d9e3a61e8164aadd9a2f326c06f271a4139dcd250
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3 |
+
size 715413441
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vocab/key2row
ADDED
@@ -0,0 +1 @@
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|
|
|
|
1 |
+
�
|
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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2 |
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oid sha256:76be8b528d0075f7aae98d6fa57a6d3c83ae480a8469e668d7b0af968995ac71
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3 |
+
size 1
|
vocab/strings.json
ADDED
The diff for this file is too large to render.
See raw diff
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|
vocab/vectors
ADDED
Binary file (128 Bytes). View file
|
|
vocab/vectors.cfg
ADDED
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"mode":"default"
|
3 |
+
}
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