osiria commited on
Commit
413a8a4
1 Parent(s): 32aeea3

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +4 -0
README.md CHANGED
@@ -29,6 +29,10 @@ widget:
29
 
30
  This is a <b>DistilBERT</b> <b>[1]</b> cased model for the <b>Italian</b> language, fine-tuned for <b>Named Entity Recognition</b> (<b>Person</b>, <b>Location</b>, <b>Organization</b> and <b>Miscellanea</b> classes) on the [WikiNER](https://figshare.com/articles/dataset/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500) dataset <b>[2]</b>, using <b>DistilBERT-ITALIAN</b> ([distilbert-base-italian-cased](https://huggingface.co/osiria/distilbert-base-italian-cased)) as a pre-trained model.
31
 
 
 
 
 
32
  <h3>Training and Performances</h3>
33
 
34
  The model is trained to perform entity recognition over 4 classes: <b>PER</b> (persons), <b>LOC</b> (locations), <b>ORG</b> (organizations), <b>MISC</b> (miscellanea, mainly events, products and services). It has been fine-tuned for Named Entity Recognition, using the WikiNER Italian dataset plus an additional custom dataset of manually annotated Wikipedia paragraphs.
 
29
 
30
  This is a <b>DistilBERT</b> <b>[1]</b> cased model for the <b>Italian</b> language, fine-tuned for <b>Named Entity Recognition</b> (<b>Person</b>, <b>Location</b>, <b>Organization</b> and <b>Miscellanea</b> classes) on the [WikiNER](https://figshare.com/articles/dataset/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500) dataset <b>[2]</b>, using <b>DistilBERT-ITALIAN</b> ([distilbert-base-italian-cased](https://huggingface.co/osiria/distilbert-base-italian-cased)) as a pre-trained model.
31
 
32
+ This is a cased DistilBERT model. If you are looking for a more accurate (but heavier) cased model, you can refer to: https://huggingface.co/osiria/bert-italian-cased-ner
33
+
34
+ If you are looking for an uncased model, you can refer to: https://huggingface.co/osiria/bert-italian-uncased-ner
35
+
36
  <h3>Training and Performances</h3>
37
 
38
  The model is trained to perform entity recognition over 4 classes: <b>PER</b> (persons), <b>LOC</b> (locations), <b>ORG</b> (organizations), <b>MISC</b> (miscellanea, mainly events, products and services). It has been fine-tuned for Named Entity Recognition, using the WikiNER Italian dataset plus an additional custom dataset of manually annotated Wikipedia paragraphs.