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README.md

@@ -12,40 +12,19 @@ dataset_info:
   - name: tokens
     sequence: string
   - name: ner_tags
-    sequence:
-      class_label:
-        names:
-          '0': B-Date
-          '1': B-Indicator
-          '2': B-Location
-          '3': B-Malware
-          '4': B-Organization
-          '5': B-System
-          '6': B-Threat_group
-          '7': B-Vulnerability
-          '8': I-Date
-          '9': I-Indicator
-          '10': I-Location
-          '11': I-Malware
-          '12': I-Organization
-          '13': I-System
-          '14': I-Threat_group
-          '15': I-Vulnerability
-          '16': O
-  - name: __index_level_0__
-    dtype: int64
+    sequence: int64
   splits:
   - name: train
-    num_bytes: 3773244
+    num_bytes: 3711236
     num_examples: 7751
   - name: validation
-    num_bytes: 810240
+    num_bytes: 796952
     num_examples: 1661
   - name: test
-    num_bytes: 797853
+    num_bytes: 784557
     num_examples: 1662
-  download_size: 1642952
-  dataset_size: 5381337
+  download_size: 1579340
+  dataset_size: 5292745
 configs:
 - config_name: default
   data_files:
@@ -55,9 +34,6 @@ configs:
     path: data/validation-*
   - split: test
     path: data/test-*
-tags:
-- cybersecurity
-- ner
 ---
 # CyNER 2.0 Augmented Dataset
 *CyNER 2.0 Augmented Dataset* is a comprehensive dataset designed for Named Entity Recognition (NER) tasks, specifically tailored for cybersecurity-related text. This dataset combines an original cybersecurity NER dataset (bnsapa/cybersecurity-ner) with additional augmented data (taken from OPENCTI using AlienValut Connect), resulting in a robust resource for training and evaluating models on cybersecurity entity recognition.

data/test-00000-of-00001.parquet

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data/train-00000-of-00001.parquet

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data/validation-00000-of-00001.parquet

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