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@@ -35,3 +35,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 parser/model filter=lfs diff=lfs merge=lfs -text
 tok2vec/model filter=lfs diff=lfs merge=lfs -text
+vocab/key2row filter=lfs diff=lfs merge=lfs -text
+vocab/vectors filter=lfs diff=lfs merge=lfs -text

config.cfg

@@ -1,7 +1,7 @@
 [paths]
 train = "./train.spacy"
 dev = "./train.spacy"
-vectors = "en_core_web_trf"
+vectors = "en_core_web_lg"
 init_tok2vec = null
 
 [system]

meta.json

@@ -2,18 +2,18 @@
   "lang":"en",
   "name":"pipeline",
   "version":"0.0.0",
-  "spacy_version":">=3.7.5,<3.8.0",
-  "description":"",
-  "author":"",
+  "spacy_version":">3.0.0",
+  "description":"A custom NER model for recognizing couese entities.",
+  "author":"Pravin Senta",
   "email":"",
   "url":"",
   "license":"",
-  "spacy_git_version":"a6d0fc360",
+  "spacy_git_version":"319e025",
   "vectors":{
-    "width":0,
-    "vectors":0,
-    "keys":0,
-    "name":null,
+    "width":300,
+    "vectors":514157,
+    "keys":514157,
+    "name":"en_vectors",
     "mode":"default"
   },
   "labels":{
@@ -32,10 +32,12 @@
       "COURSE_NAME",
       "COURSE_OVERVIEW",
       "COURSE_STRUCTURE",
+      "ENGLISH_LANGUAGE_REQUIREMENT",
       "INSTITUTE_CODE",
       "INSTITUTE_NAME",
       "INTAKES",
       "NUMBER_OF_SUBJECTS",
+      "RESULT_MIN_PERCENTAGE",
       "SUBJECT_CODE",
       "SUBJECT_NAME",
       "TUITION_FEE"
@@ -59,14 +61,14 @@
 
   ],
   "performance":{
-    "ents_f":0.9763779528,
-    "ents_p":1.0,
-    "ents_r":0.9538461538,
+    "ents_f":0.9519450801,
+    "ents_p":0.9497716895,
+    "ents_r":0.9541284404,
     "ents_per_type":{
       "COURSE_NAME":{
-        "p":1.0,
-        "r":0.9696969697,
-        "f":0.9846153846
+        "p":0.962962963,
+        "r":0.9397590361,
+        "f":0.9512195122
       },
       "COURSE_LINK":{
         "p":1.0,
@@ -74,24 +76,24 @@
         "f":1.0
       },
       "INSTITUTE_NAME":{
-        "p":1.0,
+        "p":0.8823529412,
         "r":1.0,
-        "f":1.0
+        "f":0.9375
       },
       "ACADEMIC_QUALIFICATION":{
-        "p":1.0,
+        "p":0.96,
         "r":1.0,
-        "f":1.0
+        "f":0.9795918367
       },
       "COURSE_CODE":{
         "p":1.0,
-        "r":1.0,
-        "f":1.0
+        "r":0.9444444444,
+        "f":0.9714285714
       },
       "COURSE_DURATION":{
-        "p":1.0,
-        "r":0.8571428571,
-        "f":0.9230769231
+        "p":0.9666666667,
+        "r":0.90625,
+        "f":0.935483871
       },
       "COURSE_STRUCTURE":{
         "p":1.0,
@@ -109,14 +111,19 @@
         "f":0.0
       },
       "INTAKES":{
-        "p":1.0,
-        "r":0.9166666667,
-        "f":0.9565217391
+        "p":0.8518518519,
+        "r":0.8846153846,
+        "f":0.8679245283
+      },
+      "COURSE_OVERVIEW":{
+        "p":0.7,
+        "r":0.875,
+        "f":0.7777777778
       },
       "CAMPUS_LOCATION":{
-        "p":1.0,
-        "r":0.8181818182,
-        "f":0.9
+        "p":0.9696969697,
+        "r":0.9411764706,
+        "f":0.9552238806
       },
       "COURSE_LEVEL":{
         "p":1.0,
@@ -138,11 +145,6 @@
         "r":1.0,
         "f":1.0
       },
-      "COURSE_OVERVIEW":{
-        "p":1.0,
-        "r":1.0,
-        "f":1.0
-      },
       "COURSE_LEARNING_OUTCOMES":{
         "p":1.0,
         "r":1.0,
@@ -152,6 +154,16 @@
         "p":1.0,
         "r":1.0,
         "f":1.0
+      },
+      "ENGLISH_LANGUAGE_REQUIREMENT":{
+        "p":0.8888888889,
+        "r":0.96,
+        "f":0.9230769231
+      },
+      "RESULT_MIN_PERCENTAGE":{
+        "p":0.9436619718,
+        "r":0.9571428571,
+        "f":0.9503546099
       }
     },
     "dep_uas":0.0,
@@ -160,8 +172,9 @@
     "sents_p":0.0,
     "sents_r":0.0,
     "sents_f":0.0,
-    "tok2vec_loss":3505.2871297434,
-    "ner_loss":1150.2701899913,
+    "tok2vec_loss":34738.0146326002,
+    "ner_loss":9034.5114021174,
     "parser_loss":0.0
-  }
+  },
+  "language":"en"
 }

ner/moves

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parser/model

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 size 1721120

parser/moves

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tok2vec/model

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+size 34434008

vocab/key2row

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