Update spaCy pipeline

.gitattributes

@@ -33,3 +33,5 @@ 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
+en_pipeline-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
+transformer/model filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,23 @@
+---
+tags:
+- spacy
+- token-classification
+language:
+- en
+model-index:
+- name: en_pipeline
+  results:
+  - task:
+      name: NER
+      type: token-classification
+    metrics:
+    - name: NER Precision
+      type: precision
+      value: 0.96
+    - name: NER Recall
+      type: recall
+      value: 0.9696969697
+    - name: NER F Score
+      type: f_score
+      value: 0.9648241206
+---

config.cfg

@@ -0,0 +1,146 @@
+[paths]
+train = "/content/training_data.spacy"
+dev = "/content/training_data.spacy"
+vectors = null
+init_tok2vec = null
+
+[system]
+gpu_allocator = "pytorch"
+seed = 0
+
+[nlp]
+lang = "en"
+pipeline = ["transformer","ner"]
+batch_size = 128
+disabled = []
+before_creation = null
+after_creation = null
+after_pipeline_creation = null
+tokenizer = {"@tokenizers":"spacy.Tokenizer.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 = false
+nO = null
+
+[components.ner.model.tok2vec]
+@architectures = "spacy-transformers.TransformerListener.v1"
+grad_factor = 1.0
+pooling = {"@layers":"reduce_mean.v1"}
+upstream = "*"
+
+[components.transformer]
+factory = "transformer"
+max_batch_items = 4096
+set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
+
+[components.transformer.model]
+@architectures = "spacy-transformers.TransformerModel.v3"
+name = "roberta-base"
+mixed_precision = false
+
+[components.transformer.model.get_spans]
+@span_getters = "spacy-transformers.strided_spans.v1"
+window = 128
+stride = 96
+
+[components.transformer.model.grad_scaler_config]
+
+[components.transformer.model.tokenizer_config]
+use_fast = true
+
+[components.transformer.model.transformer_config]
+
+[corpora]
+
+[corpora.dev]
+@readers = "spacy.Corpus.v1"
+path = ${paths.dev}
+max_length = 0
+gold_preproc = false
+limit = 0
+augmenter = null
+
+[corpora.train]
+@readers = "spacy.Corpus.v1"
+path = ${paths.train}
+max_length = 0
+gold_preproc = false
+limit = 0
+augmenter = null
+
+[training]
+accumulate_gradient = 3
+dev_corpus = "corpora.dev"
+train_corpus = "corpora.train"
+seed = ${system.seed}
+gpu_allocator = ${system.gpu_allocator}
+dropout = 0.1
+patience = 1600
+max_epochs = 30
+max_steps = 20000
+eval_frequency = 200
+frozen_components = []
+annotating_components = []
+before_to_disk = null
+before_update = null
+
+[training.batcher]
+@batchers = "spacy.batch_by_padded.v1"
+discard_oversize = true
+size = 2000
+buffer = 256
+get_length = null
+
+[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
+
+[training.optimizer.learn_rate]
+@schedules = "warmup_linear.v1"
+warmup_steps = 250
+total_steps = 20000
+initial_rate = 0.00005
+
+[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]

dist/fine_tuned_spacy_model-0.1.0.tar.gz

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+size 761

dist/industry_sector_ner-0.0.0.tar.gz

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+size 746

dist/industry_sector_ner_fine-tune-0.1.0.tar.gz

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+oid sha256:3ea434f13e9fa900b27c4c7c9cebb979bf9345706c6735881406cb873ab6231f
+size 837

dist/spacy_fine_tune_news-0.1.0.tar.gz

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+oid sha256:30b500c62156673b070e23d01864ec9be2a8f01ce314f38a2dac42643f388f34
+size 856

dist/your_spacy_model-0.1.0.tar.gz

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+size 743

dist/your_spacy_model_name-0.1.0.tar.gz

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+oid sha256:6b2d177164abb3c47d30a3e029e7398db7b1bd48f444db967473c97cf12d959b
+size 787

en_pipeline-any-py3-none-any.whl

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+version https://git-lfs.github.com/spec/v1
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+size 428621803

meta.json

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+{
+  "lang":"en",
+  "name":"pipeline",
+  "version":"0.0.0",
+  "description":"",
+  "author":"",
+  "email":"",
+  "url":"",
+  "license":"",
+  "spacy_version":">=3.6.1,<3.7.0",
+  "spacy_git_version":"458bc5f45",
+  "vectors":{
+    "width":0,
+    "vectors":0,
+    "keys":0,
+    "name":null
+  },
+  "labels":{
+    "transformer":[
+
+    ],
+    "ner":[
+      "SECTOR"
+    ]
+  },
+  "pipeline":[
+    "transformer",
+    "ner"
+  ],
+  "components":[
+    "transformer",
+    "ner"
+  ],
+  "disabled":[
+
+  ],
+  "performance":{
+    "ents_f":0.9648241206,
+    "ents_p":0.96,
+    "ents_r":0.9696969697,
+    "ents_per_type":{
+      "SECTOR":{
+        "p":0.96,
+        "r":0.9696969697,
+        "f":0.9648241206
+      }
+    },
+    "transformer_loss":354.7826454542,
+    "ner_loss":450.1430266494
+  },
+  "requirements":[
+    "spacy-transformers>=1.3.4,<1.4.0"
+  ]
+}

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
+}

ner/moves

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+��moves�d{"0":{},"1":{"SECTOR":214},"2":{"SECTOR":214},"3":{"SECTOR":214},"4":{"SECTOR":214,"":1},"5":{"":1}}�cfg��neg_key�

setup.py

@@ -0,0 +1,13 @@
+from setuptools import setup, find_packages
+
+setup(
+  name='spacy_fine_tune_news',
+  version='0.1.0',
+  packages=find_packages(),
+  package_data={'spacy_fine_tune_news': ['/content/drive/MyDrive/industry_sector_NER/model/model-best/transformer/*']},  # Include model data
+  include_package_data=True,
+  install_requires=[
+    'spacy>=3.0.0',  # Declare spaCy dependency
+    # Other dependencies if needed
+  ],
+)

tokenizer

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+  "yet",
+  "yields",
+  "yms",
+  "yog",
+  "yogi",
+  "yojana",
+  "you",
+  "ype",
+  "yst",
+  "ytd",
+  "y\u2019",
+  "y\u2019s",
+  "z",
+  "z.",
+  "zakir",
+  "zed",
+  "zes",
+  "zon",
+  "zone",
+  "zones",
+  "zoramthanga",
+  "zov",
+  "|",
+  "}",
+  "\u00a0",
+  "\u00ac",
+  "\u00ac_\u00ac",
+  "\u00af",
+  "\u00af\\(x)/\u00af",
+  "\u00af\\(\u30c4)/\u00af",
+  "\u00b0",
+  "\u00b0C.",
+  "\u00b0F.",
+  "\u00b0K.",
+  "\u00b0X.",
+  "\u00b0c.",
+  "\u00b0f.",
+  "\u00b0k.",
+  "\u00b0x.",
+  "\u00e0",
+  "\u00e4",
+  "\u00e4.",
+  "\u00f6",
+  "\u00f6.",
+  "\u00fc",
+  "\u00fc.",
+  "\u0ca0",
+  "\u0ca0_\u0ca0",
+  "\u0ca0\ufe35\u0ca0",
+  "\u2013",
+  "\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",
+  "\u201c",
+  "\u201cThe",
+  "\u201cXxx",
+  "\u201cthe",
+  "\u201cxxx",
+  "\u201d",
+  "\u201dFinance",
+  "\u201dSince",
+  "\u201dXxxxx",
+  "\u201dfinance",
+  "\u201dsince",
+  "\u201dxxxx",
+  "\u2501",
+  "\u253b",
+  "\u253b\u2501\u253b",
+  "\u256f",
+  "\u25a1",
+  "\ufe35",
+  "\uff09"
+]

vocab/vectors.cfg

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