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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+medical-ner-task2/ner/model filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,28 @@
+---
+tags:
+- spacy
+- ner
+- medical-ner
+library_name: spacy
+pipeline_tag: ner
+language: en
+license: mit
+---
+
+# Medical NER Model - medical-ner-task2
+
+This model is trained to recognize medical entities including treatments, chronic diseases, cancers, and allergies.
+
+## Model Details
+- Task: medical-ner-task2
+- Framework: spaCy
+- Entity Types: TREATMENT, CHRONIC DISEASE, CANCER, ALLERGY, OTHER
+
+## Usage
+```python
+import spacy
+nlp = spacy.load("nitinyadav/continual_learning_ner_task2")
+doc = nlp("Patient has been diagnosed with Type 2 Diabetes")
+for ent in doc.ents:
+    print(ent.text, ent.label_)
+```

medical-ner-task2/config.cfg

@@ -0,0 +1,130 @@
+[paths]
+train = null
+dev = null
+vectors = null
+init_tok2vec = null
+
+[system]
+seed = 0
+gpu_allocator = null
+
+[nlp]
+lang = "en"
+pipeline = ["ner"]
+disabled = []
+before_creation = null
+after_creation = null
+after_pipeline_creation = null
+batch_size = 1000
+tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
+vectors = {"@vectors":"spacy.Vectors.v1"}
+
+[components]
+
+[components.ner]
+factory = "ner"
+incorrect_spans_key = null
+moves = null
+scorer = {"@scorers":"spacy.ner_scorer.v1"}
+update_with_oracle_cut_size = 100
+
+[components.ner.model]
+@architectures = "spacy.TransitionBasedParser.v2"
+state_type = "ner"
+extra_state_tokens = false
+hidden_width = 64
+maxout_pieces = 2
+use_upper = true
+nO = null
+
+[components.ner.model.tok2vec]
+@architectures = "spacy.HashEmbedCNN.v2"
+pretrained_vectors = null
+width = 96
+depth = 4
+embed_size = 2000
+window_size = 1
+maxout_pieces = 3
+subword_features = true
+
+[corpora]
+
+[corpora.dev]
+@readers = "spacy.Corpus.v1"
+path = ${paths.dev}
+gold_preproc = false
+max_length = 0
+limit = 0
+augmenter = null
+
+[corpora.train]
+@readers = "spacy.Corpus.v1"
+path = ${paths.train}
+gold_preproc = false
+max_length = 0
+limit = 0
+augmenter = null
+
+[training]
+seed = ${system.seed}
+gpu_allocator = ${system.gpu_allocator}
+dropout = 0.1
+accumulate_gradient = 1
+patience = 1600
+max_epochs = 0
+max_steps = 20000
+eval_frequency = 200
+frozen_components = []
+annotating_components = []
+dev_corpus = "corpora.dev"
+train_corpus = "corpora.train"
+before_to_disk = null
+before_update = null
+
+[training.batcher]
+@batchers = "spacy.batch_by_words.v1"
+discard_oversize = false
+tolerance = 0.2
+get_length = null
+
+[training.batcher.size]
+@schedules = "compounding.v1"
+start = 100
+stop = 1000
+compound = 1.001
+t = 0.0
+
+[training.logger]
+@loggers = "spacy.ConsoleLogger.v1"
+progress_bar = false
+
+[training.optimizer]
+@optimizers = "Adam.v1"
+beta1 = 0.9
+beta2 = 0.999
+L2_is_weight_decay = true
+L2 = 0.01
+grad_clip = 1.0
+use_averages = false
+eps = 0.00000001
+learn_rate = 0.001
+
+[training.score_weights]
+ents_f = 1.0
+ents_p = 0.0
+ents_r = 0.0
+ents_per_type = null
+
+[pretraining]
+
+[initialize]
+vectors = ${paths.vectors}
+init_tok2vec = ${paths.init_tok2vec}
+vocab_data = null
+lookups = null
+before_init = null
+after_init = null
+
+[initialize.components]
+
+[initialize.tokenizer]

medical-ner-task2/meta.json

@@ -0,0 +1,36 @@
+{
+  "lang":"en",
+  "name":"pipeline",
+  "version":"0.0.0",
+  "spacy_version":">=3.7.5,<3.8.0",
+  "description":"",
+  "author":"",
+  "email":"",
+  "url":"",
+  "license":"",
+  "spacy_git_version":"a6d0fc360",
+  "vectors":{
+    "width":0,
+    "vectors":0,
+    "keys":0,
+    "name":null,
+    "mode":"default"
+  },
+  "labels":{
+    "ner":[
+      "ALLERGY",
+      "CANCER",
+      "CHRONIC DISEASE",
+      "TREATMENT"
+    ]
+  },
+  "pipeline":[
+    "ner"
+  ],
+  "components":[
+    "ner"
+  ],
+  "disabled":[
+
+  ]
+}

medical-ner-task2/ner/cfg

@@ -0,0 +1,13 @@
+{
+  "moves":null,
+  "update_with_oracle_cut_size":100,
+  "multitasks":[
+
+  ],
+  "min_action_freq":1,
+  "learn_tokens":false,
+  "beam_width":1,
+  "beam_density":0.0,
+  "beam_update_prob":0.0,
+  "incorrect_spans_key":null
+}

medical-ner-task2/ner/model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:45f6a7b9cca349458346d75ad81be6b68bdcfb3e8c4c5a61b46e2b2c796295de
+size 3836040

medical-ner-task2/ner/moves

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medical-ner-task2/tokenizer

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+  "}",
+  "\u00a0",
+  "\u00ac",
+  "\u00ac_\u00ac",
+  "\u00ae",
+  "\u00af",
+  "\u00af\\(x)/\u00af",
+  "\u00af\\(\u30c4)/\u00af",
+  "\u00b0",
+  "\u00b0C.",
+  "\u00b0F.",
+  "\u00b0K.",
+  "\u00b0X.",
+  "\u00b0c.",
+  "\u00b0f.",
+  "\u00b0k.",
+  "\u00b0x.",
+  "\u00d7",
+  "\u00e4",
+  "\u00e4.",
+  "\u00f6",
+  "\u00f6.",
+  "\u00fc",
+  "\u00fc.",
+  "\u03b2",
+  "\u03b2+",
+  "\u03b20",
+  "\u03b2S",
+  "\u03b2s",
+  "\u03bc",
+  "\u03bcL",
+  "\u03bcM",
+  "\u03bcl",
+  "\u03bcm",
+  "\u0ca0",
+  "\u0ca0_\u0ca0",
+  "\u0ca0\ufe35\u0ca0",
+  "\u2010RT",
+  "\u2014",
+  "\u2018",
+  "\u2018S",
+  "\u2018X",
+  "\u2018s",
+  "\u2018x",
+  "\u2019",
+  "\u2019-(",
+  "\u2019-)",
+  "\u2019Cause",
+  "\u2019Cos",
+  "\u2019Coz",
+  "\u2019Cuz",
+  "\u2019S",
+  "\u2019X",
+  "\u2019Xxx",
+  "\u2019Xxxxx",
+  "\u2019am",
+  "\u2019bout",
+  "\u2019cause",
+  "\u2019cos",
+  "\u2019coz",
+  "\u2019cuz",
+  "\u2019d",
+  "\u2019em",
+  "\u2019ll",
+  "\u2019m",
+  "\u2019nuff",
+  "\u2019re",
+  "\u2019s",
+  "\u2019ve",
+  "\u2019x",
+  "\u2019xx",
+  "\u2019xxx",
+  "\u2019xxxx",
+  "\u2019y",
+  "\u2019\u2019",
+  "\u2022",
+  "\u2264",
+  "\u226411",
+  "\u226414",
+  "\u22647",
+  "\u2264d",
+  "\u2264dd",
+  "\u2265",
+  "\u22651",
+  "\u22651.0",
+  "\u226514",
+  "\u226515",
+  "\u22652.0",
+  "\u22653",
+  "\u2265300",
+  "\u22655",
+  "\u226550",
+  "\u22655mcg",
+  "\u2265d",
+  "\u2265d.d",
+  "\u2265dd",
+  "\u2265ddd",
+  "\u2265dxxx",
+  "\u2501",
+  "\u253b",
+  "\u253b\u2501\u253b",
+  "\u256f",
+  "\u25a1",
+  "\ufe35",
+  "\uff09"
+]

medical-ner-task2/vocab/vectors.cfg

@@ -0,0 +1,3 @@
+{
+  "mode":"default"
+}