Update README.md

README.md

@@ -10,8 +10,28 @@ base_model:
 - urchade/gliner_small-v2.1
 ---
 
-# GliNER PII Detection 🚀
+# Gravitee GliNER PII Detection 🚀
+GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.
+The list of entities is provided in Evaluation results; however, due to the model's nature, it has the capability to identify other entity types as well.
 
+Evaluation results:
+
+| Entity                    | Precision | Recall    | F1 Score  |
+|---------------------------|-----------|-----------|-----------|
+| email                     | 0.937213  | 0.925870  | 0.931507  |
+| phone_number              | 0.898515  | 0.876812  | 0.887531  |
+| name                      | 0.929052  | 0.824776  | 0.873814  |
+| date_of_birth             | 0.813953  | 0.937500  | 0.871369  |
+| date                      | 0.888942  | 0.839801  | 0.863673  |
+| location                  | 0.881579  | 0.829833  | 0.854924  |
+| company                   | 0.821222  | 0.873162  | 0.846396  |
+| ipv4                      | 0.791667  | 0.890625  | 0.838235  |
+| ssn                       | 0.897959  | 0.785714  | 0.838095  |
+| bank_routing_number       | 0.898305  | 0.746479  | 0.815385  |
+| driver_license_number     | 0.918367  | 0.725806  | 0.810811  |
+| passport_number           | 0.918367  | 0.714286  | 0.803571  |
+| credit_card_security_code | 0.830986  | 0.756410  | 0.791946  |
+| time                      | 0.834297  | 0.674455  | 0.745909  |
 
 ## Installation
 To use this model, you must install the GLiNER Python library:
@@ -34,7 +54,6 @@ model = GLiNER.from_pretrained(
 text = """
 Hey, just a quick update — I talked to David yesterday. 
 He sent over the files from his private email ([email protected]), and we should be careful with his SSN: 123-45-6789.
-Also, please don't push the GitHub repo until we remove the API key: ghp_abcdEfgh1234567890.
 He mentioned his new address is 123 Maple Street in New York. 
 His PC adress is 192.168.1.100.
 """
@@ -42,7 +61,6 @@ His PC adress is 192.168.1.100.
 labels = ["name",
           "email",
           "ssn",
-          "api_key",
           "street_address",
           "date",
           "ipv4"]
@@ -58,7 +76,6 @@ David => name => 0.9066112041473389
 yesterday => date => 0.9482080340385437
 [email protected] => email => 0.9911587834358215
 123-45-6789 => ssn => 0.8612598180770874
-ghp_abcdEfgh1234567890 => api_key => 0.6934646964073181
 123 Maple Street in New York => street_address => 0.9869663715362549
 192.168.1.100 => ipv4 => 0.9810121059417725
 ```