Update README.md

README.md

@@ -1,3 +1,35 @@
 ---
+tags:
+- spacy
+- token-classification
+language: uk
+datasets:
+- ner-uk
 license: mit
+model-index:
+- name: roberta-uk-ner-base
+  results:
+  - task:
+      name: NER
+      type: token-classification
+    metrics:
+    - name: NER Precision
+      type: precision
+      value: 0.8987742191
+    - name: NER Recall
+      type: recall
+      value: 0.8810077519
+    - name: NER F Score
+      type: f_score
+      value: 0.8898023096
 ---
+# roberta-uk-ner-base
+
+## Model description
+
+**roberta-uk-ner-base** is a fine-tuned [XLM-Roberta model](https://huggingface.co/xlm-roberta-base) that is ready to use for **Named Entity Recognition** and achieves **state-of-the-art performance** for the NER task for Ukrainian language. It has been trained to recognize four types of entities: location (LOC), organizations (ORG), person (PERS) and Miscellaneous (MISC). 
+
+The model was fine-tuned on the [NER-UK dataset](https://github.com/lang-uk/ner-uk), released by the [lang-uk](https://lang.org.ua).
+
+
+Copyright: Dmytro Chaplynskyi, [lang-uk project](https://lang.org.ua), 2022