Update README.md

README.md

@@ -51,32 +51,40 @@ widget:
 
 # Catalan BERTa-v2 (roberta-base-ca-v2) finetuned for Named Entity Recognition.
 
-## Table of Contents
-- [Model Description](#model-description)
-- [Intended Uses and Limitations](#intended-uses-and-limitations)
-- [How to Use](#how-to-use)
+## Table of ContentsContents
+<details>
+<summary>Click to expand</summary>
+
+- [Model description](#model-description)
+- [Intended uses and limitations](#intended-use)
+- [How to use](#how-to-use)
+- [Limitations and bias](#limitations-and-bias)
 - [Training](#training)
-  - [Training Data](#training-data)
-  - [Training Procedure](#training-procedure)
+  - [Training data](#training-data)
+  - [Training procedure](#training-procedure)
 - [Evaluation](#evaluation)
-   - [Variable and Metrics](#variable-and-metrics)
-   - [Evaluation Results](#evaluation-results)
-- [Licensing Information](#licensing-information)
-- [Citation Information](#citation-information)
-- [Funding](#funding)
-- [Contributions](#contributions)
-- [Disclaimer](#disclaimer)
+   - [Variable and metrics](#variable-and-metrics)
+   - [Evaluation results](#evaluation-results)
+- [Additional information](#additional-information)
+  - [Author](#author)
+  - [Contact information](#contact-information)
+  - [Copyright](#copyright)
+  - [Licensing information](#licensing-information)
+  - [Funding](#funding)
+  - [Citing information](#citing-information)
+  - [Disclaimer](#disclaimer)
+</details>
 
 
 ## Model description
 
 The **roberta-base-ca-v2-cased-ner** is a Named Entity Recognition (NER) model for the Catalan language fine-tuned from the [roberta-base-ca-v2](https://huggingface.co/projecte-aina/roberta-base-ca-v2) model, a [RoBERTa](https://arxiv.org/abs/1907.11692) base model pre-trained on a medium-size corpus collected from publicly available corpora and crawlers (check the roberta-base-ca-v2 model card for more details).
 
-## Intended Uses and Limitations
+## Intended uses and limitations
 
 **roberta-base-ca-v2-cased-ner** model can be used to recognize Named Entities in the provided text. The model is limited by its training dataset and may not generalize well for all use cases.
 
-## How to Use
+## How to use
 
 Here is how to use this model:
 
@@ -91,17 +99,20 @@ ner_results = nlp(example)
 pprint(ner_results)
 ```
 
+## Limitations and bias
+At the time of submission, no measures have been taken to estimate the bias embedded in the model. However, we are well aware that our models may be biased since the corpora have been collected using crawling techniques on multiple web sources. We intend to conduct research in these areas in the future, and if completed, this model card will be updated.
+
 ## Training
 
 ### Training data
 We used the NER dataset in Catalan called [AnCora-Ca-NER](https://huggingface.co/datasets/projecte-aina/ancora-ca-ner) for training and evaluation.
 
-### Training Procedure
+### Training procedure
 The model was trained with a batch size of 16 and a learning rate of 5e-5 for 5 epochs. We then selected the best checkpoint using the downstream task metric in the corresponding development set and then evaluated it on the test set.
 
 ## Evaluation
 
-### Variable and Metrics
+### Variable and metrics
 
 This model was finetuned maximizing F1 score.
 
@@ -117,11 +128,25 @@ We evaluated the _roberta-base-ca-v2-cased-ner_ on the AnCora-Ca-NER test set ag
 
 For more details, check the fine-tuning and evaluation scripts in the official [GitHub repository](https://github.com/projecte-aina/club).
 
-## Licensing Information
 
+## Additional information
+
+### Author
+Text Mining Unit (TeMU) at the Barcelona Supercomputing Center (bsc-temu@bsc.es)
+
+### Contact information
+For further information, send an email to aina@bsc.es
+
+### Copyright
+Copyright (c) 2022 Text Mining Unit at Barcelona Supercomputing Center 
+
+### Licensing information
 [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)
 
-## Citation Information 
+### Funding
+This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).
+
+### Citation Information 
 
 If you use any of these resources (datasets or models) in your work, please cite our latest paper:
 ```bibtex
@@ -146,14 +171,7 @@ If you use any of these resources (datasets or models) in your work, please cite
 }
 ```
 
-## Funding
-This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).
-
-## Contributions
-
-[N/A]
-
-## Disclaimer
+### Disclaimer
 
 <details>
 <summary>Click to expand</summary>