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 +1,56 @@
+---
+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: 0.9308734236
+    - name: NER Recall
+      type: recall
+      value: 0.9133822181
+    - name: NER F Score
+      type: f_score
+      value: 0.9220448762
+---
+| Feature | Description |
+| --- | --- |
+| **Name** | `en_pipeline` |
+| **Version** | `0.0.0` |
+| **spaCy** | `>=3.7.5,<3.8.0` |
+| **Default Pipeline** | `transformer`, `ner` |
+| **Components** | `transformer`, `ner` |
+| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
+| **Sources** | n/a |
+| **License** | n/a |
+| **Author** | [n/a]() |
+
+### Label Scheme
+
+<details>
+
+<summary>View label scheme (8 labels for 1 components)</summary>
+
+| Component | Labels |
+| --- | --- |
+| **`ner`** | `B-LAW`, `B-VIOLATED BY`, `B-VIOLATED ON`, `B-VIOLATION`, `I-LAW`, `I-VIOLATED BY`, `I-VIOLATED ON`, `I-VIOLATION` |
+
+</details>
+
+### Accuracy
+
+| Type | Score |
+| --- | --- |
+| `ENTS_F` | 92.20 |
+| `ENTS_P` | 93.09 |
+| `ENTS_R` | 91.34 |
+| `TRANSFORMER_LOSS` | 16253.98 |
+| `NER_LOSS` | 13899.54 |

config.cfg

@@ -0,0 +1,147 @@
+[paths]
+train = "/content/files_v1.0/train_data.spacy"
+dev = "/content/files_v1.0/test_data.spacy"
+vectors = null
+init_tok2vec = null
+
+[system]
+gpu_allocator = "pytorch"
+seed = 0
+
+[nlp]
+lang = "en"
+pipeline = ["transformer","ner"]
+batch_size = 16
+disabled = []
+before_creation = null
+after_creation = null
+after_pipeline_creation = null
+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 = 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 = "microsoft/deberta-v3-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 = 0
+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]

en_pipeline-any-py3-none-any.whl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fe2b4909106d66f1f6e5b9bee25e42cdffd7826706fbc07cd6b713f8ed2a0a38
+size 577032794

meta.json

@@ -0,0 +1,96 @@
+{
+  "lang":"en",
+  "name":"pipeline",
+  "version":"0.0.0",
+  "description":"",
+  "author":"",
+  "email":"",
+  "url":"",
+  "license":"",
+  "spacy_version":">=3.7.5,<3.8.0",
+  "spacy_git_version":"a6d0fc360",
+  "vectors":{
+    "width":0,
+    "vectors":0,
+    "keys":0,
+    "name":null
+  },
+  "labels":{
+    "transformer":[
+
+    ],
+    "ner":[
+      "B-LAW",
+      "B-VIOLATED BY",
+      "B-VIOLATED ON",
+      "B-VIOLATION",
+      "I-LAW",
+      "I-VIOLATED BY",
+      "I-VIOLATED ON",
+      "I-VIOLATION"
+    ]
+  },
+  "pipeline":[
+    "transformer",
+    "ner"
+  ],
+  "components":[
+    "transformer",
+    "ner"
+  ],
+  "disabled":[
+
+  ],
+  "performance":{
+    "ents_f":0.9220448762,
+    "ents_p":0.9308734236,
+    "ents_r":0.9133822181,
+    "ents_per_type":{
+      "B-VIOLATION":{
+        "p":0.9014084507,
+        "r":0.9014084507,
+        "f":0.9014084507
+      },
+      "I-VIOLATION":{
+        "p":0.9433481859,
+        "r":0.9153798641,
+        "f":0.929153605
+      },
+      "B-LAW":{
+        "p":0.8888888889,
+        "r":0.9302325581,
+        "f":0.9090909091
+      },
+      "I-LAW":{
+        "p":0.9406779661,
+        "r":0.9652173913,
+        "f":0.9527896996
+      },
+      "B-VIOLATED BY":{
+        "p":0.9523809524,
+        "r":0.9302325581,
+        "f":0.9411764706
+      },
+      "I-VIOLATED BY":{
+        "p":0.9493670886,
+        "r":0.9615384615,
+        "f":0.9554140127
+      },
+      "B-VIOLATED ON":{
+        "p":0.6829268293,
+        "r":0.6511627907,
+        "f":0.6666666667
+      },
+      "I-VIOLATED ON":{
+        "p":0.8640776699,
+        "r":0.898989899,
+        "f":0.8811881188
+      }
+    },
+    "transformer_loss":162.5397746471,
+    "ner_loss":138.9954125388
+  },
+  "requirements":[
+    "spacy-transformers>=1.3.5,<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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tokenizer

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+  "uys",
+  "v",
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+  "v.s",
+  "v.s.",
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+  "v_v",
+  "va",
+  "va.",
+  "val",
+  "validated",
+  "validating",
+  "valuable",
+  "value",
+  "values",
+  "variable",
+  "variety",
+  "various",
+  "vaults",
+  "ve",
+  "ved",
+  "vel",
+  "ven",
+  "ver",
+  "version",
+  "versions",
+  "ves",
+  "via",
+  "vials",
+  "vicariously",
+  "victimized",
+  "victims",
+  "vid",
+  "video",
+  "videos",
+  "vie",
+  "viewers",
+  "viewing",
+  "vigilant",
+  "vin",
+  "violated",
+  "violates",
+  "violating",
+  "violation",
+  "violations",
+  "violent",
+  "virtual",
+  "visibility",
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+  "vital",
+  "volatile",
+  "voyager",
+  "vs",
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+  "vulnerable",
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+  "wage",
+  "waivers",
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+  "wall",
+  "wallet",
+  "want",
+  "wanted",
+  "wants",
+  "warn",
+  "warned",
+  "warning",
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+  "warranties",
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+  "was",
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+  "wastage",
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+  "wastes",
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+  "water",
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+  "wear",
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+  "wed",
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+  "weight",
+  "weird",
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+  "when",
+  "when's",
+  "when\u2019s",
+  "where",
+  "where's",
+  "where\u2019s",
+  "which",
+  "while",
+  "who",
+  "who's",
+  "whole",
+  "wholesome",
+  "whom",
+  "whose",
+  "who\u2019s",
+  "why",
+  "why's",
+  "why\u2019s",
+  "widely",
+  "wider",
+  "widespread",
+  "will",
+  "willfully",
+  "win",
+  "wiring",
+  "wis",
+  "wis.",
+  "with",
+  "withdrawing",
+  "withdrawn",
+  "withheld",
+  "withholding",
+  "within",
+  "without",
+  "wo",
+  "woes",
+  "wondering",
+  "work",
+  "worked",
+  "workers",
+  "working",
+  "workplace",
+  "works",
+  "world",
+  "worried",
+  "worse",
+  "worsened",
+  "worst",
+  "worth",
+  "would",
+  "wow",
+  "write",
+  "writing",
+  "written",
+  "wrong",
+  "wrongdoing",
+  "wrongfully",
+  "wrongly",
+  "wth",
+  "w\u2019s",
+  "x",
+  "x'",
+  "x'x",
+  "x'xxxx",
+  "x.",
+  "x.X",
+  "x.d",
+  "x.x",
+  "x.x.",
+  "x/x",
+  "xD",
+  "xDD",
+  "xX",
+  "xXX",
+  "x_X",
+  "x_d",
+  "x_x",
+  "xas",
+  "xd",
+  "xdd",
+  "xed",
+  "xes",
+  "xx",
+  "xx'",
+  "xx'x",
+  "xx'xx",
+  "xx.",
+  "xxdddd.dd",
+  "xxx",
+  "xxx'x",
+  "xxx/xx",
+  "xxxx",
+  "xxxx'",
+  "xxxx'x",
+  "xxxxdddd.dd",
+  "xxxx\u2019",
+  "xxxx\u2019x",
+  "xxx\u2019x",
+  "xx\u2019",
+  "xx\u2019x",
+  "xx\u2019xx",
+  "xyz",
+  "x\u2019",
+  "x\u2019x",
+  "x\u2019xxxx",
+  "x\ufe35x",
+  "y",
+  "y'",
+  "y's",
+  "y.",
+  "ya",
+  "yal",
+  "year",
+  "years",
+  "yed",
+  "yee",
+  "yer",
+  "yes",
+  "yet",
+  "yield",
+  "yly",
+  "yna",
+  "you",
+  "young",
+  "your",
+  "ype",
+  "y\u2019",
+  "y\u2019s",
+  "z",
+  "z.",
+  "zed",
+  "zes",
+  "zon",
+  "|",
+  "}",
+  "\u00a0",
+  "\u00ac",
+  "\u00ac_\u00ac",
+  "\u00af",
+  "\u00af\\(x)/\u00af",
+  "\u00af\\(\u30c4)/\u00af",
+  "\u00b0",
+  "\u00b0C.",
+  "\u00b0F.",
+  "\u00b0K.",
+  "\u00b0X.",
+  "\u00b0c.",
+  "\u00b0f.",
+  "\u00b0k.",
+  "\u00b0x.",
+  "\u00e4",
+  "\u00e4.",
+  "\u00f6",
+  "\u00f6.",
+  "\u00fc",
+  "\u00fc.",
+  "\u0ca0",
+  "\u0ca0_\u0ca0",
+  "\u0ca0\ufe35\u0ca0",
+  "\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",
+  "\u2501",
+  "\u253b",
+  "\u253b\u2501\u253b",
+  "\u256f",
+  "\u25a1",
+  "\ufe35",
+  "\uff09"
+]

vocab/vectors.cfg

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