Create README.md

README.md

@@ -0,0 +1,48 @@
+---
+
+tags:
+- token-classification
+datasets:
+- conll2012_ontonotesv5
+widget:
+- text: "On September 1st George won 1 dollar while watching Game of Thrones."
+---
+
+# (NER) bert-base-cased : conll2012_ontonotesv5-english-v4
+
+This `bert-base-cased` NER model was finetuned on `conll2012_ontonotesv5` version `english-v4` dataset. <br>
+Check out [NER-System Repository](https://github.com/djagatiya/NER-System) for more information.
+
+## Evaluation
+- Precision: 87.85
+- Recall: 89.63
+- F1-Score: 88.73
+
+> check out this [eval.log](eval.log) file for evaluation metrics and classification report.
+
+```
+               precision    recall  f1-score   support
+
+    CARDINAL       0.86      0.87      0.86       935
+        DATE       0.84      0.88      0.86      1602
+       EVENT       0.65      0.67      0.66        63
+         FAC       0.69      0.71      0.70       135
+         GPE       0.97      0.93      0.95      2240
+    LANGUAGE       0.76      0.73      0.74        22
+         LAW       0.54      0.55      0.54        40
+         LOC       0.73      0.80      0.76       179
+       MONEY       0.87      0.90      0.88       314
+        NORP       0.93      0.96      0.94       841
+     ORDINAL       0.80      0.87      0.83       195
+         ORG       0.88      0.90      0.89      1795
+     PERCENT       0.88      0.90      0.89       349
+      PERSON       0.94      0.95      0.94      1988
+     PRODUCT       0.62      0.76      0.69        76
+    QUANTITY       0.74      0.81      0.77       105
+        TIME       0.61      0.67      0.64       212
+ WORK_OF_ART       0.56      0.66      0.61       166
+
+   micro avg       0.88      0.90      0.89     11257
+   macro avg       0.77      0.81      0.79     11257
+weighted avg       0.88      0.90      0.89     11257
+```