Update README.md

README.md

@@ -1,31 +1,31 @@
----
-pretty_name: BioBERT-ITA
-license: cc-by-sa-4.0
-dataset_info:
-  features:
-  - name: text
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 27319024484
-    num_examples: 17203146
-  download_size: 14945984639
-  dataset_size: 27319024484
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-task_categories:
-- text-generation
-language:
-- it
-tags:
-- medical
-- biology
-size_categories:
-- 10B<n<100B
----
+---
+pretty_name: BioBERT-ITA
+license: cc-by-sa-4.0
+dataset_info:
+  features:
+  - name: text
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 27319024484
+    num_examples: 17203146
+  download_size: 14945984639
+  dataset_size: 27319024484
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+task_categories:
+- text-generation
+language:
+- it
+tags:
+- medical
+- biology
+size_categories:
+- 10B<n<100B
+---
 
 From this repository you can download the **BioBERT_Italian** dataset.
 
@@ -33,6 +33,8 @@ From this repository you can download the **BioBERT_Italian** dataset.
 
 Due to the unavailability of an Italian equivalent for the millions of abstracts and full-text scientific papers used by English, BERT-based biomedical models, we leveraged machine translation to obtain an Italian biomedical corpus based on PubMed abstracts and train [**BioBIT**](https://www.sciencedirect.com/science/article/pii/S1532046423001521).
 
+**BioBIT Model**
+
 [**BioBIT**](https://www.sciencedirect.com/science/article/pii/S1532046423001521) has been evaluated on 3 downstream tasks: **NER** (Named Entity Recognition), extractive **QA** (Question Answering), **RE** (Relation Extraction).
 Here are the results, summarized:
 - NER:
@@ -50,7 +52,7 @@ Here are the results, summarized:
   - [CHEMPROT](http://refhub.elsevier.com/S1532-0464(23)00152-1/sb36) = 38.16%
   - [BioRED](http://refhub.elsevier.com/S1532-0464(23)00152-1/sb37) = 67.15%
 
-**MedPsyNIT**
+**MedPsyNIT Model**
 
 We also [**fine-tuned BioBIT**](https://www.sciencedirect.com/science/article/pii/S1532046423002782) on [**PsyNIT**](IVN-RIN/PsyNIT) (Psychiatric Ner for ITalian), a native Italian **NER** (Named Entity Recognition) dataset, composed by [Italian Research Hospital Centro San Giovanni Di Dio Fatebenefratelli](https://www.fatebenefratelli.it/strutture/irccs-brescia).