Update spaCy pipeline

.gitattributes

@@ -30,3 +30,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *strings.json filter=lfs diff=lfs merge=lfs -text
 vectors filter=lfs diff=lfs merge=lfs -text
 model filter=lfs diff=lfs merge=lfs -text
+vocab/key2row filter=lfs diff=lfs merge=lfs -text

README.md

@@ -14,25 +14,25 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.8778156997
+      value: 0.8649613325
     - name: NER Recall
       type: recall
-      value: 0.8840918466
+      value: 0.8892966361
     - name: NER F Score
       type: f_score
-      value: 0.8809425949
+      value: 0.876960193
 ---
 | Feature | Description |
 | --- | --- |
 | **Name** | `en_core_med7_lg` |
-| **Version** | `3.1.3.1` |
-| **spaCy** | `>=3.1.4,<3.2.0` |
+| **Version** | `3.4.2.1` |
+| **spaCy** | `>=3.4.2,<3.5.0` |
 | **Default Pipeline** | `tok2vec`, `ner` |
 | **Components** | `tok2vec`, `ner` |
-| **Vectors** | 684830 keys, 684830 unique vectors (300 dimensions) |
+| **Vectors** | 514157 keys, 514157 unique vectors (300 dimensions) |
 | **Sources** | n/a |
 | **License** | `MIT` |
-| **Author** | [Andrey Kormilitzin](kormilitzin.com) |
+| **Author** | [Andrey Kormilitzin](https://www.kormilitzin.com/) |
 
 ### Label Scheme
 
@@ -50,22 +50,8 @@ model-index:
 
 | Type | Score |
 | --- | --- |
-| `ENTS_F` | 88.09 |
-| `ENTS_P` | 87.78 |
-| `ENTS_R` | 88.41 |
-| `TOK2VEC_LOSS` | 115648.09 |
-| `NER_LOSS` | 279069.77 |
-
-### BibTeX entry and citation info
-
-```bibtex
-@article{kormilitzin2021med7,
-  title={Med7: A transferable clinical natural language processing model for electronic health records},
-  author={Kormilitzin, Andrey and Vaci, Nemanja and Liu, Qiang and Nevado-Holgado, Alejo},
-  journal={Artificial Intelligence in Medicine},
-  volume={118},
-  pages={102086},
-  year={2021},
-  publisher={Elsevier}
-}
-```
+| `ENTS_F` | 87.70 |
+| `ENTS_P` | 86.50 |
+| `ENTS_R` | 88.93 |
+| `TOK2VEC_LOSS` | 226109.53 |
+| `NER_LOSS` | 302222.55 |

config.cfg

@@ -1,8 +1,9 @@
 [paths]
-train = "./data/spacy_format/train_443.spacy"
-dev = "./data/spacy_format/dev_443.spacy"
-vectors = null
-init_tok2vec = null
+train = "/mnt/sdf/andrey/projects/med7_v3/data/spacy_format/train_med7_v34.spacy"
+dev = "/mnt/sdf/andrey/projects/med7_v3/data/spacy_format/dev_med7_v34.spacy"
+raw_text = "/mnt/sdf/andrey/projects/med7_v3/data/pretrain_mimic.jsonl"
+vectors = "en_core_web_lg"
+init_tok2vec = "/mnt/sdf/andrey/projects/med7_v3/output_pretrain_lg/model169.bin"
 
 [system]
 gpu_allocator = null
@@ -24,13 +25,14 @@ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
 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
+hidden_width = 128
 maxout_pieces = 2
 use_upper = true
 nO = null
@@ -49,8 +51,8 @@ factory = "tok2vec"
 [components.tok2vec.model.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = ${components.tok2vec.model.encode.width}
-attrs = ["ORTH","SHAPE"]
-rows = [5000,2500]
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
+rows = [5000,1000,2500,2500]
 include_static_vectors = true
 
 [components.tok2vec.model.encode]
@@ -85,7 +87,7 @@ seed = ${system.seed}
 gpu_allocator = ${system.gpu_allocator}
 dropout = 0.1
 accumulate_gradient = 1
-patience = 1600
+patience = 3600
 max_epochs = 0
 max_steps = 20000
 eval_frequency = 200
@@ -108,7 +110,7 @@ t = 0.0
 
 [training.logger]
 @loggers = "spacy.ConsoleLogger.v1"
-progress_bar = false
+progress_bar = true
 
 [training.optimizer]
 @optimizers = "Adam.v1"
@@ -130,13 +132,17 @@ ents_per_type = null
 [pretraining]
 
 [initialize]
-vectors = "en_core_web_lg"
+vectors = ${paths.vectors}
 init_tok2vec = ${paths.init_tok2vec}
 vocab_data = null
-lookups = null
 before_init = null
 after_init = null
 
 [initialize.components]
 
+[initialize.lookups]
+@misc = "spacy.LookupsDataLoader.v1"
+lang = ${nlp.lang}
+tables = ["lexeme_norm"]
+
 [initialize.tokenizer]

en_core_med7_lg-any-py3-none-any.whl

@@ -1,3 +1,3 @@
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-size 790703817
+oid sha256:2c8ce371b7ee8b3c42cce7c05031ab165e6e88cc3ed136797eb3c492af96001f
+size 607352778

meta.json

@@ -1,18 +1,18 @@
 {
   "lang":"en",
   "name":"core_med7_lg",
-  "version":"3.1.3.1",
+  "version":"3.4.2.1",
   "description":"",
   "author":"Andrey Kormilitzin",
   "email":"kormilitzin@gmail.com",
-  "url":"kormilitzin.com",
+  "url":"https://www.kormilitzin.com/",
   "license":"MIT",
-  "spacy_version":">=3.1.4,<3.2.0",
-  "spacy_git_version":"8bda39f08",
+  "spacy_version":">=3.4.2,<3.5.0",
+  "spacy_git_version":"Unknown",
   "vectors":{
     "width":300,
-    "vectors":684830,
-    "keys":684830,
+    "vectors":514157,
+    "keys":514157,
     "name":"en_vectors"
   },
   "labels":{
@@ -41,48 +41,48 @@
 
   ],
   "performance":{
-    "ents_f":0.8809425949,
-    "ents_p":0.8778156997,
-    "ents_r":0.8840918466,
+    "ents_f":0.876960193,
+    "ents_p":0.8649613325,
+    "ents_r":0.8892966361,
     "ents_per_type":{
       "DRUG":{
-        "p":0.8897203623,
-        "r":0.8855350843,
-        "f":0.8876227898
+        "p":0.8638497653,
+        "r":0.8761904762,
+        "f":0.8699763593
       },
-      "DOSAGE":{
-        "p":0.8563134978,
-        "r":0.8885542169,
-        "f":0.8721359941
+      "ROUTE":{
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+        "r":0.9427083333,
+        "f":0.9427083333
       },
       "STRENGTH":{
-        "p":0.9299065421,
-        "r":0.9307764266,
-        "f":0.930341281
+        "p":0.8814229249,
+        "r":0.9214876033,
+        "f":0.901010101
       },
-      "DURATION":{
-        "p":0.6741573034,
-        "r":0.625,
-        "f":0.6486486486
+      "FREQUENCY":{
+        "p":0.7222222222,
+        "r":0.8210526316,
+        "f":0.7684729064
       },
       "FORM":{
-        "p":0.9318637275,
-        "r":0.8635097493,
-        "f":0.8963855422
+        "p":0.9400921659,
+        "r":0.9400921659,
+        "f":0.9400921659
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-      "FREQUENCY":{
-        "p":0.7181544634,
-        "r":0.8211009174,
-        "f":0.7661851257
+      "DOSAGE":{
+        "p":0.8671328671,
+        "r":0.8671328671,
+        "f":0.8671328671
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-      "ROUTE":{
-        "p":0.9331919406,
-        "r":0.9322033898,
-        "f":0.9326974033
+      "DURATION":{
+        "p":0.6666666667,
+        "r":0.6666666667,
+        "f":0.6666666667
       }
     },
-    "tok2vec_loss":1156.4809109417,
-    "ner_loss":2790.6977062746
+    "tok2vec_loss":2261.0953059313,
+    "ner_loss":3022.2254596124
   },
   "requirements":[
 

ner/model

@@ -1,3 +1,3 @@
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ner/moves

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-��moves�
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+��moves�
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tok2vec/model

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+size 34434008

vocab/lookups.bin

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+size 69982

vocab/strings.json

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vocab/vectors

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vocab/vectors.cfg

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